llama.cpp/ggml/src/ggml-metal/ggml-metal.metal
Georgi Gerganov cf32a9b93a
metal : refactor kernel args into structs (#10238)
* metal : add kernel arg structs (wip)

* metal : fattn args

ggml-ci

* metal : cont + avoid potential int overflow [no ci]

* metal : mul mat struct (wip)

* cont : mul mat vec

* cont : pass by reference

* cont : args is first argument

* cont : use char ptr

* cont : shmem style

* cont : thread counters style

* cont : mul mm id

ggml-ci

* cont : int safety + register optimizations

ggml-ci

* metal : GGML_OP_CONCAT

ggml-ci

* metal : GGML_OP_ADD, GGML_OP_SUB, GGML_OP_MUL, GGML_OP_DIV

* metal : GGML_OP_REPEAT

* metal : GGML_OP_CPY

* metal : GGML_OP_RMS_NORM

* metal : GGML_OP_NORM

* metal : add TODOs for rest of ops

* ggml : add ggml-metal-impl.h

ggml-ci
2024-11-17 11:23:01 +02:00

6084 lines
231 KiB
Metal

#define GGML_COMMON_DECL_METAL
#define GGML_COMMON_IMPL_METAL
#if defined(GGML_METAL_EMBED_LIBRARY)
__embed_ggml-common.h__
#else
// TODO: this should not be a relative path, but can't figure out how to set Metal include paths in Package.swift
#include "../ggml-common.h"
#endif
#include "ggml-metal-impl.h"
#include <metal_stdlib>
using namespace metal;
#define MAX(x, y) ((x) > (y) ? (x) : (y))
#define MIN(x, y) ((x) < (y) ? (x) : (y))
#define SWAP(x, y) { auto tmp = (x); (x) = (y); (y) = tmp; }
#define N_SIMDWIDTH 32 // assuming SIMD group size is 32
// ref: https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf
//
// cmd:
// .../usr/bin/metal -dM -E -c ggml/src/ggml-metal/ggml-metal.metal
// .../usr/bin/metal -dM -E -c -target air64-apple-ios14.0 ggml/src/ggml-metal/ggml-metal.metal
//
#if __METAL_VERSION__ < 310 && defined(GGML_METAL_USE_BF16)
#undef GGML_METAL_USE_BF16
#endif
#if defined(GGML_METAL_USE_BF16)
typedef matrix<bfloat, 4, 4> bfloat4x4;
#endif
constexpr constant static float kvalues_iq4nl_f[16] = {
-127.f, -104.f, -83.f, -65.f, -49.f, -35.f, -22.f, -10.f, 1.f, 13.f, 25.f, 38.f, 53.f, 69.f, 89.f, 113.f
};
// NOTE: this is not dequantizing - we are simply fitting the template
template <typename type4x4>
void dequantize_f32(device const float4x4 * src, short il, thread type4x4 & reg) {
reg = (type4x4)(*src);
}
template <typename type4x4>
void dequantize_f16(device const half4x4 * src, short il, thread type4x4 & reg) {
reg = (type4x4)(*src);
}
#if defined(GGML_METAL_USE_BF16)
template <typename type4x4>
void dequantize_bf16(device const bfloat4x4 * src, short il, thread type4x4 & reg) {
reg = (type4x4)(*src);
}
#endif
template <typename type4x4>
void dequantize_q4_0(device const block_q4_0 *xb, short il, thread type4x4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 1);
const float d1 = il ? (xb->d / 16.h) : xb->d;
const float d2 = d1 / 256.f;
const float md = -8.h * xb->d;
const ushort mask0 = il ? 0x00F0 : 0x000F;
const ushort mask1 = mask0 << 8;
float4x4 reg_f;
for (int i = 0; i < 8; i++) {
reg_f[i/2][2*(i%2) + 0] = d1 * (qs[i] & mask0) + md;
reg_f[i/2][2*(i%2) + 1] = d2 * (qs[i] & mask1) + md;
}
reg = (type4x4) reg_f;
}
template <typename type4x4>
void dequantize_q4_1(device const block_q4_1 *xb, short il, thread type4x4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 2);
const float d1 = il ? (xb->d / 16.h) : xb->d;
const float d2 = d1 / 256.f;
const float m = xb->m;
const ushort mask0 = il ? 0x00F0 : 0x000F;
const ushort mask1 = mask0 << 8;
float4x4 reg_f;
for (int i = 0; i < 8; i++) {
reg_f[i/2][2*(i%2) + 0] = ((qs[i] & mask0) * d1) + m;
reg_f[i/2][2*(i%2) + 1] = ((qs[i] & mask1) * d2) + m;
}
reg = (type4x4) reg_f;
}
template <typename type4x4>
void dequantize_q5_0(device const block_q5_0 *xb, short il, thread type4x4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 3);
const float d = xb->d;
const float md = -16.h * xb->d;
const ushort mask = il ? 0x00F0 : 0x000F;
const uint32_t qh = *((device const uint32_t *)xb->qh);
const int x_mv = il ? 4 : 0;
const int gh_mv = il ? 12 : 0;
const int gh_bk = il ? 0 : 4;
float4x4 reg_f;
for (int i = 0; i < 8; i++) {
// extract the 5-th bits for x0 and x1
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
// combine the 4-bits from qs with the 5th bit
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
reg_f[i/2][2*(i%2) + 0] = d * x0 + md;
reg_f[i/2][2*(i%2) + 1] = d * x1 + md;
}
reg = (type4x4) reg_f;
}
template <typename type4x4>
void dequantize_q5_1(device const block_q5_1 *xb, short il, thread type4x4 & reg) {
device const uint16_t * qs = ((device const uint16_t *)xb + 4);
const float d = xb->d;
const float m = xb->m;
const ushort mask = il ? 0x00F0 : 0x000F;
const uint32_t qh = *((device const uint32_t *)xb->qh);
const int x_mv = il ? 4 : 0;
const int gh_mv = il ? 12 : 0;
const int gh_bk = il ? 0 : 4;
float4x4 reg_f;
for (int i = 0; i < 8; i++) {
// extract the 5-th bits for x0 and x1
const uint8_t xh_0 = ((qh >> (gh_mv + 2*i )) << gh_bk) & 0x10;
const uint8_t xh_1 = ((qh >> (gh_mv + 2*i+1)) << gh_bk) & 0x10;
// combine the 4-bits from qs with the 5th bit
const int32_t x0 = ((((qs[i] ) & mask) >> x_mv) | xh_0);
const int32_t x1 = ((((qs[i] >> 8) & mask) >> x_mv) | xh_1);
reg_f[i/2][2*(i%2) + 0] = d * x0 + m;
reg_f[i/2][2*(i%2) + 1] = d * x1 + m;
}
reg = (type4x4) reg_f;
}
template <typename type4x4>
void dequantize_q8_0(device const block_q8_0 *xb, short il, thread type4x4 & reg) {
device const int8_t * qs = ((device const int8_t *)xb->qs);
const half d = xb->d;
float4x4 reg_f;
for (int i = 0; i < 16; i++) {
reg_f[i/4][i%4] = (qs[i + 16*il] * d);
}
reg = (type4x4) reg_f;
}
template <typename type4x4>
void dequantize_q2_K(device const block_q2_K *xb, short il, thread type4x4 & reg) {
const float d = xb->d;
const float min = xb->dmin;
device const uint8_t * q = (device const uint8_t *)xb->qs;
float dl, ml;
uint8_t sc = xb->scales[il];
q = q + 32*(il/8) + 16*(il&1);
il = (il/2)%4;
half coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
uchar mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
dl = d * (sc & 0xF) * coef, ml = min * (sc >> 4);
for (int i = 0; i < 16; ++i) {
reg[i/4][i%4] = dl * (q[i] & mask) - ml;
}
}
template <typename type4x4>
void dequantize_q3_K(device const block_q3_K *xb, short il, thread type4x4 & reg) {
const half d_all = xb->d;
device const uint8_t * q = (device const uint8_t *)xb->qs;
device const uint8_t * h = (device const uint8_t *)xb->hmask;
device const int8_t * scales = (device const int8_t *)xb->scales;
q = q + 32 * (il/8) + 16 * (il&1);
h = h + 16 * (il&1);
uint8_t m = 1 << (il/2);
uint16_t kmask1 = (il/4)>1 ? ((il/4)>2 ? 192 : 48) : \
((il/4)>0 ? 12 : 3);
uint16_t kmask2 = il/8 ? 0xF0 : 0x0F;
uint16_t scale_2 = scales[il%8], scale_1 = scales[8 + il%4];
int16_t dl_int = (il/4)&1 ? (scale_2&kmask2) | ((scale_1&kmask1) << 2)
: (scale_2&kmask2) | ((scale_1&kmask1) << 4);
float dl = il<8 ? d_all * (dl_int - 32.f) : d_all * (dl_int / 16.f - 32.f);
const float ml = 4.f * dl;
il = (il/2) & 3;
const half coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
const uint8_t mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
dl *= coef;
for (int i = 0; i < 16; ++i) {
reg[i/4][i%4] = dl * (q[i] & mask) - (h[i] & m ? 0 : ml);
}
}
static inline uchar2 get_scale_min_k4_just2(int j, int k, device const uchar * q) {
return j < 4 ? uchar2{uchar(q[j+0+k] & 63), uchar(q[j+4+k] & 63)}
: uchar2{uchar((q[j+4+k] & 0xF) | ((q[j-4+k] & 0xc0) >> 2)), uchar((q[j+4+k] >> 4) | ((q[j-0+k] & 0xc0) >> 2))};
}
template <typename type4x4>
void dequantize_q4_K(device const block_q4_K *xb, short il, thread type4x4 & reg) {
device const uchar * q = xb->qs;
short is = (il/4) * 2;
q = q + (il/4) * 32 + 16 * (il&1);
il = il & 3;
const uchar2 sc = get_scale_min_k4_just2(is, il/2, xb->scales);
const float d = il < 2 ? xb->d : xb->d / 16.h;
const float min = xb->dmin;
const float dl = d * sc[0];
const float ml = min * sc[1];
const ushort mask = il<2 ? 0x0F : 0xF0;
for (int i = 0; i < 16; ++i) {
reg[i/4][i%4] = dl * (q[i] & mask) - ml;
}
}
template <typename type4x4>
void dequantize_q5_K(device const block_q5_K *xb, short il, thread type4x4 & reg) {
device const uint8_t * q = xb->qs;
device const uint8_t * qh = xb->qh;
short is = (il/4) * 2;
q = q + 32 * (il/4) + 16 * (il&1);
qh = qh + 16 * (il&1);
uint8_t ul = 1 << (il/2);
il = il & 3;
const uchar2 sc = get_scale_min_k4_just2(is, il/2, xb->scales);
const float d = il < 2 ? xb->d : xb->d / 16.f;
const float min = xb->dmin;
const float dl = d * sc[0];
const float ml = min * sc[1];
const ushort mask = il<2 ? 0x0F : 0xF0;
const float qh_val = il<2 ? 16.f : 256.f;
for (int i = 0; i < 16; ++i) {
reg[i/4][i%4] = dl * ((q[i] & mask) + (qh[i] & ul ? qh_val : 0)) - ml;
}
}
template <typename type4x4>
void dequantize_q6_K(device const block_q6_K *xb, short il, thread type4x4 & reg) {
const half d_all = xb->d;
device const uint8_t * ql = (device const uint8_t *)xb->ql;
device const uint8_t * qh = (device const uint8_t *)xb->qh;
device const int8_t * scales = (device const int8_t *)xb->scales;
ql = ql + 64*(il/8) + 32*((il/2)&1) + 16*(il&1);
qh = qh + 32*(il/8) + 16*(il&1);
float sc = scales[(il%2) + 2 * ((il/2))];
il = (il/2) & 3;
const uint16_t kmask1 = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3);
const uint16_t kmask2 = il>1 ? 0xF0 : 0x0F;
const float coef = il>1 ? 1.f/16.f : 1.f;
const float ml = d_all * sc * 32.f;
const float dl = d_all * sc * coef;
for (int i = 0; i < 16; ++i) {
const half q = il&1 ? ((ql[i] & kmask2) | ((qh[i] & kmask1) << 2))
: ((ql[i] & kmask2) | ((qh[i] & kmask1) << 4));
reg[i/4][i%4] = dl * q - ml;
}
}
template <typename type4x4>
void dequantize_iq2_xxs(device const block_iq2_xxs * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
// each block of 32 needs 2 uint32_t's for the quants & scale, so 4 uint16_t's.
device const uint16_t * q2 = xb->qs + 4*ib32;
const uint32_t aux32_g = q2[0] | (q2[1] << 16);
const uint32_t aux32_s = q2[2] | (q2[3] << 16);
thread const uint8_t * aux8 = (thread const uint8_t *)&aux32_g;
const float dl = d * (0.5f + (aux32_s >> 28)) * 0.25f;
constant uint8_t * grid = (constant uint8_t *)(iq2xxs_grid + aux8[2*il+0]);
uint8_t signs = ksigns_iq2xs[(aux32_s >> 14*il) & 127];
for (int i = 0; i < 8; ++i) {
reg[i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
}
grid = (constant uint8_t *)(iq2xxs_grid + aux8[2*il+1]);
signs = ksigns_iq2xs[(aux32_s >> (14*il+7)) & 127];
for (int i = 0; i < 8; ++i) {
reg[2+i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
}
}
template <typename type4x4>
void dequantize_iq2_xs(device const block_iq2_xs * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint16_t * q2 = xb->qs + 4*ib32;
const float dl = d * (0.5f + ((xb->scales[ib32] >> 4*il) & 0xf)) * 0.25f;
constant uint8_t * grid = (constant uint8_t *)(iq2xs_grid + (q2[2*il+0] & 511));
uint8_t signs = ksigns_iq2xs[q2[2*il+0] >> 9];
for (int i = 0; i < 8; ++i) {
reg[i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
}
grid = (constant uint8_t *)(iq2xs_grid + (q2[2*il+1] & 511));
signs = ksigns_iq2xs[q2[2*il+1] >> 9];
for (int i = 0; i < 8; ++i) {
reg[2+i/4][i%4] = dl * grid[i] * (signs & kmask_iq2xs[i] ? -1.f : 1.f);
}
}
template <typename type4x4>
void dequantize_iq3_xxs(device const block_iq3_xxs * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint8_t * q3 = xb->qs + 8*ib32;
device const uint16_t * gas = (device const uint16_t *)(xb->qs + QK_K/4) + 2*ib32;
const uint32_t aux32 = gas[0] | (gas[1] << 16);
const float dl = d * (0.5f + (aux32 >> 28)) * 0.5f;
constant uint8_t * grid1 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+0]);
constant uint8_t * grid2 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+1]);
uint8_t signs = ksigns_iq2xs[(aux32 >> 14*il) & 127];
for (int i = 0; i < 4; ++i) {
reg[0][i] = dl * grid1[i] * (signs & kmask_iq2xs[i+0] ? -1.f : 1.f);
reg[1][i] = dl * grid2[i] * (signs & kmask_iq2xs[i+4] ? -1.f : 1.f);
}
grid1 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+2]);
grid2 = (constant uint8_t *)(iq3xxs_grid + q3[4*il+3]);
signs = ksigns_iq2xs[(aux32 >> (14*il+7)) & 127];
for (int i = 0; i < 4; ++i) {
reg[2][i] = dl * grid1[i] * (signs & kmask_iq2xs[i+0] ? -1.f : 1.f);
reg[3][i] = dl * grid2[i] * (signs & kmask_iq2xs[i+4] ? -1.f : 1.f);
}
}
template <typename type4x4>
void dequantize_iq3_s(device const block_iq3_s * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint8_t * qs = xb->qs + 8*ib32;
device const uint8_t * signs = xb->signs + 4*ib32 + 2*il;
const uint8_t qh = xb->qh[ib32] >> 4*il;
const float dl = d * (1 + 2*((xb->scales[ib32/2] >> 4*(ib32%2)) & 0xf));
constant uint8_t * grid1 = (constant uint8_t *)(iq3s_grid + (qs[4*il+0] | ((qh << 8) & 256)));
constant uint8_t * grid2 = (constant uint8_t *)(iq3s_grid + (qs[4*il+1] | ((qh << 7) & 256)));
for (int i = 0; i < 4; ++i) {
reg[0][i] = dl * grid1[i] * select(1, -1, signs[0] & kmask_iq2xs[i+0]);
reg[1][i] = dl * grid2[i] * select(1, -1, signs[0] & kmask_iq2xs[i+4]);
}
grid1 = (constant uint8_t *)(iq3s_grid + (qs[4*il+2] | ((qh << 6) & 256)));
grid2 = (constant uint8_t *)(iq3s_grid + (qs[4*il+3] | ((qh << 5) & 256)));
for (int i = 0; i < 4; ++i) {
reg[2][i] = dl * grid1[i] * select(1, -1, signs[1] & kmask_iq2xs[i+0]);
reg[3][i] = dl * grid2[i] * select(1, -1, signs[1] & kmask_iq2xs[i+4]);
}
}
template <typename type4x4>
void dequantize_iq2_s(device const block_iq2_s * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const float d = xb->d;
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
device const uint8_t * signs = qs + QK_K/8;
const uint8_t qh = xb->qh[ib32] >> 4*il;
const float dl = d * (0.5f + ((xb->scales[ib32] >> 4*il) & 0xf)) * 0.25f;
constant uint8_t * grid1 = (constant uint8_t *)(iq2s_grid + (qs[0] | ((qh << 8) & 0x300)));
constant uint8_t * grid2 = (constant uint8_t *)(iq2s_grid + (qs[1] | ((qh << 6) & 0x300)));
for (int i = 0; i < 8; ++i) {
reg[i/4+0][i%4] = dl * grid1[i] * select(1, -1, signs[0] & kmask_iq2xs[i]);
reg[i/4+2][i%4] = dl * grid2[i] * select(1, -1, signs[1] & kmask_iq2xs[i]);
}
}
template <typename type4x4>
void dequantize_iq1_s(device const block_iq1_s * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const int ib32 = il/2;
il = il%2;
const float d = xb->d;
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
device const uint16_t * qh = xb->qh;
const float dl = d * (2*((qh[ib32] >> 12) & 7) + 1);
const float ml = dl * (qh[ib32] & 0x8000 ? -1 - IQ1S_DELTA : -1 + IQ1S_DELTA);
const uint16_t h = qh[ib32] >> 6*il;
constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((h << 8) & 0x700)));
constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((h << 5) & 0x700)));
for (int i = 0; i < 4; ++i) {
reg[0][i] = dl * (grid1[i] & 0xf) + ml;
reg[1][i] = dl * (grid1[i] >> 4) + ml;
reg[2][i] = dl * (grid2[i] & 0xf) + ml;
reg[3][i] = dl * (grid2[i] >> 4) + ml;
}
}
template <typename type4x4>
void dequantize_iq1_m(device const block_iq1_m * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const int ib32 = il/2;
il = il%2;
device const uint16_t * sc = (device const uint16_t *)xb->scales;
iq1m_scale_t scale;
scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
const float d = scale.f16;
device const uint8_t * qs = xb->qs + 4*ib32 + 2*il;
device const uint8_t * qh = xb->qh + 2*ib32 + il;
const float dl = d * (2*((sc[ib32/2] >> (6*(ib32%2)+3*il)) & 7) + 1);
const float ml1 = dl * (qh[0] & 0x08 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
const float ml2 = dl * (qh[0] & 0x80 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((qh[0] << 8) & 0x700)));
constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((qh[0] << 4) & 0x700)));
for (int i = 0; i < 4; ++i) {
reg[0][i] = dl * (grid1[i] & 0xf) + ml1;
reg[1][i] = dl * (grid1[i] >> 4) + ml1;
reg[2][i] = dl * (grid2[i] & 0xf) + ml2;
reg[3][i] = dl * (grid2[i] >> 4) + ml2;
}
}
template <typename type4x4>
void dequantize_iq4_nl(device const block_iq4_nl * xb, short il, thread type4x4 & reg) {
device const uint16_t * q4 = (device const uint16_t *)xb->qs;
const float d = xb->d;
uint32_t aux32;
thread const uint8_t * q8 = (thread const uint8_t *)&aux32;
for (int i = 0; i < 4; ++i) {
aux32 = ((q4[2*i] | (q4[2*i+1] << 16)) >> 4*il) & 0x0f0f0f0f;
reg[i][0] = d * kvalues_iq4nl_f[q8[0]];
reg[i][1] = d * kvalues_iq4nl_f[q8[1]];
reg[i][2] = d * kvalues_iq4nl_f[q8[2]];
reg[i][3] = d * kvalues_iq4nl_f[q8[3]];
}
}
template <typename type4x4>
void dequantize_iq4_xs(device const block_iq4_xs * xb, short il, thread type4x4 & reg) {
// il is 0...15 for QK_K = 256 => index of block of 32 is il/2
const int ib32 = il/2;
il = il%2;
// il = 0 or 1. il = 0 processes the first 16 quants in a block of 32, il = 1 the second 16
device const uint32_t * q4 = (device const uint32_t *)xb->qs + 4*ib32;
const int ls = ((xb->scales_l[ib32/2] >> 4*(ib32%2)) & 0xf) | (((xb->scales_h >> 2*ib32) & 3) << 4);
const float d = (float)xb->d * (ls - 32);
uint32_t aux32;
thread const uint8_t * q8 = (thread const uint8_t *)&aux32;
for (int i = 0; i < 4; ++i) {
aux32 = (q4[i] >> 4*il) & 0x0f0f0f0f;
reg[i][0] = d * kvalues_iq4nl_f[q8[0]];
reg[i][1] = d * kvalues_iq4nl_f[q8[1]];
reg[i][2] = d * kvalues_iq4nl_f[q8[2]];
reg[i][3] = d * kvalues_iq4nl_f[q8[3]];
}
}
enum ggml_sort_order {
GGML_SORT_ORDER_ASC,
GGML_SORT_ORDER_DESC,
};
// general-purpose kernel for addition, subtraction, multiplication and division of two tensors
// pros: works for non-contiguous tensors, supports broadcast across all dims
// cons: not very efficient
kernel void kernel_add(
constant ggml_metal_kargs_bin & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig.z;
const int i02 = tgpig.y;
const int i01 = tgpig.x;
const int i13 = i03%args.ne13;
const int i12 = i02%args.ne12;
const int i11 = i01%args.ne11;
device const char * src0_ptr = src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + args.offs;
device const char * src1_ptr = src1 + i13*args.nb13 + i12*args.nb12 + i11*args.nb11;
device char * dst_ptr = dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1 + args.offs;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int i10 = i0%args.ne10;
*((device float *)(dst_ptr + i0*args.nb0)) = *((device float *)(src0_ptr + i0*args.nb00)) + *((device float *)(src1_ptr + i10*args.nb10));
}
}
kernel void kernel_sub(
constant ggml_metal_kargs_bin & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig.z;
const int i02 = tgpig.y;
const int i01 = tgpig.x;
const int i13 = i03%args.ne13;
const int i12 = i02%args.ne12;
const int i11 = i01%args.ne11;
device const char * src0_ptr = src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + args.offs;
device const char * src1_ptr = src1 + i13*args.nb13 + i12*args.nb12 + i11*args.nb11;
device char * dst_ptr = dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1 + args.offs;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int i10 = i0%args.ne10;
*((device float *)(dst_ptr + i0*args.nb0)) = *((device float *)(src0_ptr + i0*args.nb00)) - *((device float *)(src1_ptr + i10*args.nb10));
}
}
kernel void kernel_mul(
constant ggml_metal_kargs_bin & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig.z;
const int i02 = tgpig.y;
const int i01 = tgpig.x;
const int i13 = i03%args.ne13;
const int i12 = i02%args.ne12;
const int i11 = i01%args.ne11;
device const char * src0_ptr = src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01;
device const char * src1_ptr = src1 + i13*args.nb13 + i12*args.nb12 + i11*args.nb11;
device char * dst_ptr = dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int i10 = i0%args.ne10;
*((device float *)(dst_ptr + i0*args.nb0)) = *((device float *)(src0_ptr + i0*args.nb00)) * *((device float *)(src1_ptr + i10*args.nb10));
}
}
kernel void kernel_div(
constant ggml_metal_kargs_bin & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig.z;
const int i02 = tgpig.y;
const int i01 = tgpig.x;
const int i13 = i03%args.ne13;
const int i12 = i02%args.ne12;
const int i11 = i01%args.ne11;
device const char * src0_ptr = src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01;
device const char * src1_ptr = src1 + i13*args.nb13 + i12*args.nb12 + i11*args.nb11;
device char * dst_ptr = dst + i03*args.nb3 + i02*args.nb2 + i01*args.nb1;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int i10 = i0%args.ne10;
*((device float *)(dst_ptr + i0*args.nb0)) = *((device float *)(src0_ptr + i0*args.nb00)) / *((device float *)(src1_ptr + i10*args.nb10));
}
}
template<typename T>
kernel void kernel_repeat(
constant ggml_metal_kargs_repeat & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = tgpig.x;
const int i03 = i3%args.ne03;
const int i02 = i2%args.ne02;
const int i01 = i1%args.ne01;
device const char * src0_ptr = src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01;
device char * dst_ptr = dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
const int i00 = i0%args.ne00;
*((device T *)(dst_ptr + i0*args.nb0)) = *((device T *)(src0_ptr + i00*args.nb00));
}
}
typedef decltype(kernel_repeat<float>) kernel_repeat_t;
template [[host_name("kernel_repeat_f32")]] kernel kernel_repeat_t kernel_repeat<float>;
template [[host_name("kernel_repeat_f16")]] kernel kernel_repeat_t kernel_repeat<half>;
template [[host_name("kernel_repeat_i32")]] kernel kernel_repeat_t kernel_repeat<int>;
template [[host_name("kernel_repeat_i16")]] kernel kernel_repeat_t kernel_repeat<short>;
// assumption: src1 is a row
// broadcast src1 into src0
kernel void kernel_add_row(
constant ggml_metal_kargs_bin & args,
device const float4 * src0,
device const float4 * src1,
device float4 * dst,
uint tpig[[thread_position_in_grid]]) {
const uint nb = args.ne00/4;
dst[tpig] = src0[tpig] + src1[tpig % nb];
}
kernel void kernel_sub_row(
constant ggml_metal_kargs_bin & args,
device const float4 * src0,
device const float4 * src1,
device float4 * dst,
uint tpig[[thread_position_in_grid]]) {
const uint nb = args.ne00/4;
dst[tpig] = src0[tpig] - src1[tpig % nb];
}
kernel void kernel_mul_row(
constant ggml_metal_kargs_bin & args,
device const float4 * src0,
device const float4 * src1,
device float4 * dst,
uint tpig[[thread_position_in_grid]]) {
const uint nb = args.ne00/4;
dst[tpig] = src0[tpig] * src1[tpig % nb];
}
kernel void kernel_div_row(
constant ggml_metal_kargs_bin & args,
device const float4 * src0,
device const float4 * src1,
device float4 * dst,
uint tpig[[thread_position_in_grid]]) {
const uint nb = args.ne00/4;
dst[tpig] = src0[tpig] / src1[tpig % nb];
}
kernel void kernel_scale(
device const float * src0,
device float * dst,
constant float & scale,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = src0[tpig] * scale;
}
kernel void kernel_scale_4(
device const float4 * src0,
device float4 * dst,
constant float & scale,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = src0[tpig] * scale;
}
kernel void kernel_clamp(
device const float * src0,
device float * dst,
constant float & min,
constant float & max,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = src0[tpig] < min ? min : (src0[tpig] > max ? max : src0[tpig]);
}
kernel void kernel_relu(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = max(0.0f, src0[tpig]);
}
kernel void kernel_sigmoid(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = 1.0f / (1.0f + exp(-src0[tpig]));
}
kernel void kernel_tanh(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
device const float & x = src0[tpig];
dst[tpig] = precise::tanh(x);
}
constant float GELU_COEF_A = 0.044715f;
constant float GELU_QUICK_COEF = -1.702f;
constant float SQRT_2_OVER_PI = 0.79788456080286535587989211986876f;
kernel void kernel_gelu(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
device const float & x = src0[tpig];
dst[tpig] = 0.5f*x*(1.0f + precise::tanh(SQRT_2_OVER_PI*x*(1.0f + GELU_COEF_A*x*x)));
}
kernel void kernel_gelu_4(
device const float4 * src0,
device float4 * dst,
uint tpig[[thread_position_in_grid]]) {
device const float4 & x = src0[tpig];
// BEWARE !!!
// Simply using "tanh" instead of "precise::tanh" will sometimes results in NaNs!
// This was observed with Falcon 7B and 40B models
//
dst[tpig] = 0.5f*x*(1.0f + precise::tanh(SQRT_2_OVER_PI*x*(1.0f + GELU_COEF_A*x*x)));
}
kernel void kernel_gelu_quick(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
device const float & x = src0[tpig];
dst[tpig] = x*(1.0f/(1.0f+exp(GELU_QUICK_COEF*x)));
}
kernel void kernel_gelu_quick_4(
device const float4 * src0,
device float4 * dst,
uint tpig[[thread_position_in_grid]]) {
device const float4 & x = src0[tpig];
dst[tpig] = x*(1.0f/(1.0f+exp(GELU_QUICK_COEF*x)));
}
kernel void kernel_silu(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
device const float & x = src0[tpig];
dst[tpig] = x / (1.0f + exp(-x));
}
kernel void kernel_silu_4(
device const float4 * src0,
device float4 * dst,
uint tpig[[thread_position_in_grid]]) {
device const float4 & x = src0[tpig];
dst[tpig] = x / (1.0f + exp(-x));
}
kernel void kernel_sqr(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = src0[tpig] * src0[tpig];
}
kernel void kernel_sqrt(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = sqrt(src0[tpig]);
}
kernel void kernel_sin(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = sin(src0[tpig]);
}
kernel void kernel_cos(
device const float * src0,
device float * dst,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = cos(src0[tpig]);
}
kernel void kernel_sum_rows(
device const float * src0,
device float * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int64_t & ne02,
constant int64_t & ne03,
constant uint64_t & nb00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant uint64_t & nb03,
constant int64_t & ne10,
constant int64_t & ne11,
constant int64_t & ne12,
constant int64_t & ne13,
constant uint64_t & nb10,
constant uint64_t & nb11,
constant uint64_t & nb12,
constant uint64_t & nb13,
constant int64_t & ne0,
constant int64_t & ne1,
constant int64_t & ne2,
constant int64_t & ne3,
constant uint64_t & nb0,
constant uint64_t & nb1,
constant uint64_t & nb2,
constant uint64_t & nb3,
uint3 tpig[[thread_position_in_grid]]) {
int64_t i3 = tpig.z;
int64_t i2 = tpig.y;
int64_t i1 = tpig.x;
if (i3 >= ne03 || i2 >= ne02 || i1 >= ne01) {
return;
}
device const float * src_row = (device const float *) ((device const char *) src0 + i1*nb01 + i2*nb02 + i3*nb03);
device float * dst_row = (device float *) ((device char *) dst + i1*nb1 + i2*nb2 + i3*nb3);
float row_sum = 0;
for (int64_t i0 = 0; i0 < ne00; i0++) {
row_sum += src_row[i0];
}
dst_row[0] = row_sum;
}
template<typename T>
kernel void kernel_soft_max(
device const char * src0,
device const char * src1,
device char * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int64_t & ne02,
constant float & scale,
constant float & max_bias,
constant float & m0,
constant float & m1,
constant uint32_t & n_head_log2,
threadgroup float * buf [[threadgroup(0)]],
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint sgitg[[simdgroup_index_in_threadgroup]],
uint tiisg[[thread_index_in_simdgroup]],
uint ntg[[threads_per_threadgroup]]) {
const int64_t i03 = (tgpig) / (ne02*ne01);
const int64_t i02 = (tgpig - i03*ne02*ne01) / ne01;
const int64_t i01 = (tgpig - i03*ne02*ne01 - i02*ne01);
device const float * psrc0 = (device const float *) src0 + (i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00);
device const T * pmask = src1 != src0 ? (device const T *) src1 + i01*ne00 : nullptr;
device float * pdst = (device float *) dst + (i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00);
float slope = 1.0f;
// ALiBi
if (max_bias > 0.0f) {
const int64_t h = i02;
const float base = h < n_head_log2 ? m0 : m1;
const int exp = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
slope = pow(base, exp);
}
// parallel max
float lmax = -INFINITY;
for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
lmax = MAX(lmax, psrc0[i00]*scale + (pmask ? slope*pmask[i00] : 0.0f));
}
// find the max value in the block
float max_val = simd_max(lmax);
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = -INFINITY;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = max_val;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
max_val = buf[tiisg];
max_val = simd_max(max_val);
}
// parallel sum
float lsum = 0.0f;
for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
const float exp_psrc0 = exp((psrc0[i00]*scale + (pmask ? slope*pmask[i00] : 0.0f)) - max_val);
lsum += exp_psrc0;
pdst[i00] = exp_psrc0;
}
// This barrier fixes a failing test
// ref: https://github.com/ggerganov/ggml/pull/621#discussion_r1425156335
threadgroup_barrier(mem_flags::mem_none);
float sum = simd_sum(lsum);
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = sum;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sum = buf[tiisg];
sum = simd_sum(sum);
}
const float inv_sum = 1.0f/sum;
for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
pdst[i00] *= inv_sum;
}
}
template<typename T>
kernel void kernel_soft_max_4(
device const char * src0,
device const char * src1,
device char * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int64_t & ne02,
constant float & scale,
constant float & max_bias,
constant float & m0,
constant float & m1,
constant uint32_t & n_head_log2,
threadgroup float * buf [[threadgroup(0)]],
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint sgitg[[simdgroup_index_in_threadgroup]],
uint tiisg[[thread_index_in_simdgroup]],
uint ntg[[threads_per_threadgroup]]) {
const int64_t i03 = (tgpig) / (ne02*ne01);
const int64_t i02 = (tgpig - i03*ne02*ne01) / ne01;
const int64_t i01 = (tgpig - i03*ne02*ne01 - i02*ne01);
device const float4 * psrc4 = (device const float4 *) src0 + (i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00)/4;
device const T * pmask = src1 != src0 ? (device const T *) src1 + i01*ne00/4 : nullptr;
device float4 * pdst4 = (device float4 *) dst + (i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00)/4;
float slope = 1.0f;
if (max_bias > 0.0f) {
const int64_t h = i02;
const float base = h < n_head_log2 ? m0 : m1;
const int exp = h < n_head_log2 ? h + 1 : 2*(h - n_head_log2) + 1;
slope = pow(base, exp);
}
// parallel max
float4 lmax4 = -INFINITY;
for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) {
lmax4 = fmax(lmax4, psrc4[i00]*scale + (float4)((pmask ? slope*pmask[i00] : 0.0f)));
}
const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3]));
float max_val = simd_max(lmax);
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = -INFINITY;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = max_val;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
max_val = buf[tiisg];
max_val = simd_max(max_val);
}
// parallel sum
float4 lsum4 = 0.0f;
for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) {
const float4 exp_psrc4 = exp((psrc4[i00]*scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))) - max_val);
lsum4 += exp_psrc4;
pdst4[i00] = exp_psrc4;
}
const float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3];
// This barrier fixes a failing test
// ref: https://github.com/ggerganov/ggml/pull/621#discussion_r1425156335
threadgroup_barrier(mem_flags::mem_none);
float sum = simd_sum(lsum);
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = sum;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sum = buf[tiisg];
sum = simd_sum(sum);
}
const float inv_sum = 1.0f/sum;
for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) {
pdst4[i00] *= inv_sum;
}
}
typedef decltype(kernel_soft_max<float>) kernel_soft_max_t;
typedef decltype(kernel_soft_max_4<float4>) kernel_soft_max_4_t;
template [[host_name("kernel_soft_max_f16")]] kernel kernel_soft_max_t kernel_soft_max<half>;
template [[host_name("kernel_soft_max_f32")]] kernel kernel_soft_max_t kernel_soft_max<float>;
template [[host_name("kernel_soft_max_f16_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<half4>;
template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<float4>;
kernel void kernel_diag_mask_inf(
device const float * src0,
device float * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int & n_past,
uint3 tpig[[thread_position_in_grid]]) {
const int64_t i02 = tpig[2];
const int64_t i01 = tpig[1];
const int64_t i00 = tpig[0];
if (i00 > n_past + i01) {
dst[i02*ne01*ne00 + i01*ne00 + i00] = -INFINITY;
} else {
dst[i02*ne01*ne00 + i01*ne00 + i00] = src0[i02*ne01*ne00 + i01*ne00 + i00];
}
}
kernel void kernel_diag_mask_inf_8(
device const float4 * src0,
device float4 * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int & n_past,
uint3 tpig[[thread_position_in_grid]]) {
const int64_t i = 2*tpig[0];
dst[i+0] = src0[i+0];
dst[i+1] = src0[i+1];
int64_t i4 = 4*i;
const int64_t i02 = i4/(ne00*ne01); i4 -= i02*ne00*ne01;
const int64_t i01 = i4/(ne00); i4 -= i01*ne00;
const int64_t i00 = i4;
for (int k = 3; k >= 0; --k) {
if (i00 + 4 + k <= n_past + i01) {
break;
}
dst[i+1][k] = -INFINITY;
if (i00 + k > n_past + i01) {
dst[i][k] = -INFINITY;
}
}
}
// ref: ggml.c:ggml_compute_forward_ssm_conv_f32
// TODO: optimize
kernel void kernel_ssm_conv_f32(
device const void * src0,
device const void * src1,
device float * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int64_t & ne02,
constant uint64_t & nb00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant int64_t & ne10,
constant int64_t & ne11,
constant uint64_t & nb10,
constant uint64_t & nb11,
constant int64_t & ne0,
constant int64_t & ne1,
constant int64_t & ne2,
constant uint64_t & nb0,
constant uint64_t & nb1,
constant uint64_t & nb2,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t ir = tgpig.x;
const int64_t i2 = tgpig.y;
const int64_t i3 = tgpig.z;
const int64_t nc = ne10;
//const int64_t ncs = ne00;
//const int64_t nr = ne01;
//const int64_t n_t = ne1;
//const int64_t n_s = ne2;
device const float * s = (device const float *) ((device const char *) src0 + ir*nb01 + i2*nb00 + i3*nb02);
device const float * c = (device const float *) ((device const char *) src1 + ir*nb11);
device float * x = (device float *) ((device char *) dst + ir*nb0 + i2*nb1 + i3*nb2);
float sumf = 0.0f;
for (int64_t i0 = 0; i0 < nc; ++i0) {
sumf += s[i0] * c[i0];
}
x[0] = sumf;
}
// ref: ggml.c:ggml_compute_forward_ssm_scan_f32
// TODO: optimize
kernel void kernel_ssm_scan_f32(
device const void * src0,
device const void * src1,
device const void * src2,
device const void * src3,
device const void * src4,
device const void * src5,
device float * dst,
constant int64_t & d_state,
constant int64_t & d_inner,
constant int64_t & n_seq_tokens,
constant int64_t & n_seqs,
constant uint64_t & nb00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant uint64_t & nb10,
constant uint64_t & nb11,
constant uint64_t & nb12,
constant uint64_t & nb13,
constant uint64_t & nb20,
constant uint64_t & nb21,
constant uint64_t & nb22,
constant uint64_t & nb30,
constant uint64_t & nb31,
constant uint64_t & nb40,
constant uint64_t & nb41,
constant uint64_t & nb42,
constant uint64_t & nb50,
constant uint64_t & nb51,
constant uint64_t & nb52,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t ir = tgpig.x;
const int64_t i3 = tgpig.y;
const int64_t nc = d_state;
//const int64_t nr = d_inner;
const int64_t n_t = n_seq_tokens;
//const int64_t n_s = n_seqs;
for (int64_t i2 = 0; i2 < n_t; ++i2) {
device const float * s0 = (device const float *) ((device const char *) src0 + ir*nb01 + i3*nb02);
device const float * x = (device const float *) ((device const char *) src1 + ir*nb10 + i2*nb11 + i3*nb12);
device const float * dt = (device const float *) ((device const char *) src2 + ir*nb20 + i2*nb21 + i3*nb22);
device const float * A = (device const float *) ((device const char *) src3 + ir*nb31);
device const float * B = (device const float *) ((device const char *) src4 + i2*nb41 + i3*nb42);
device const float * C = (device const float *) ((device const char *) src5 + i2*nb51 + i3*nb52);
device float * y = (device float *) ((device char *) dst + ir*nb10 + i2*nb11 + i3*nb12); // TODO: do not use src1 strides
device float * s = (device float *) ((device char *) dst + ir*nb01 + i3*nb02 + nb13);
if (i2 > 0) {
s0 = s;
}
// i1 == 0
float dt_soft_plus = dt[0] <= 20.0f ? log(1.0f + exp(dt[0])) : dt[0];
float x_dt = x[0] * dt_soft_plus;
float sumf = 0.0f;
for (int64_t i0 = 0; i0 < nc; ++i0) {
int64_t i = i0;
float state = (s0[i] * exp(dt_soft_plus * A[i])) + (B[i0] * x_dt);
sumf += state * C[i0];
s[i] = state;
}
y[0] = sumf;
}
}
kernel void kernel_norm(
constant ggml_metal_kargs_norm & args,
device const char * src0,
device char * dst,
threadgroup float * shmem_f32 [[threadgroup(0)]],
uint tgpig[[threadgroup_position_in_grid]],
ushort tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort ntg[[threads_per_threadgroup]]) {
if (sgitg == 0) {
shmem_f32[tiisg] = 0.0f;
}
device const float4 * x = (device const float4 *) (src0 + tgpig*args.nb01);
float4 sumf4(0.0f);
float sumf = 0.0f;
for (int i00 = tpitg; i00 < args.ne00_4; i00 += ntg) {
sumf4 += x[i00];
}
sumf = sumf4[0] + sumf4[1] + sumf4[2] + sumf4[3];
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_f32[tiisg];
sumf = simd_sum(sumf);
const float mean = sumf/args.ne00;
device float4 * y = (device float4 *) dst + tgpig*args.ne00_4;
sumf = 0.0f;
for (int i00 = tpitg; i00 < args.ne00_4; i00 += ntg) {
y[i00] = x[i00] - mean;
sumf += dot(y[i00], y[i00]);
}
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_f32[tiisg];
sumf = simd_sum(sumf);
const float variance = sumf/args.ne00;
const float scale = 1.0f/sqrt(variance + args.eps);
for (int i00 = tpitg; i00 < args.ne00_4; i00 += ntg) {
y[i00] = y[i00] * scale;
}
}
kernel void kernel_rms_norm(
constant ggml_metal_kargs_rms_norm & args,
device const char * src0,
device char * dst,
threadgroup float * shmem_f32 [[threadgroup(0)]],
uint tgpig[[threadgroup_position_in_grid]],
ushort tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort ntg[[threads_per_threadgroup]]) {
if (sgitg == 0) {
shmem_f32[tiisg] = 0.0f;
}
device const float4 * x = (device const float4 *) (src0 + tgpig*args.nb01);
float sumf = 0.0f;
// parallel sum
for (int i00 = tpitg; i00 < args.ne00_4; i00 += ntg) {
sumf += dot(x[i00], x[i00]);
}
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_f32[tiisg];
sumf = simd_sum(sumf);
const float mean = sumf/args.ne00;
const float scale = 1.0f/sqrt(mean + args.eps);
device float4 * y = (device float4 *) dst + tgpig*args.ne00_4;
for (int i00 = tpitg; i00 < args.ne00_4; i00 += ntg) {
y[i00] = x[i00] * scale;
}
}
kernel void kernel_group_norm(
device const float * src0,
device float * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int64_t & ne02,
constant uint64_t & nb00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant int32_t & n_groups,
constant float & eps,
threadgroup float * buf [[threadgroup(0)]],
uint tgpig[[threadgroup_position_in_grid]],
uint tpitg[[thread_position_in_threadgroup]],
uint sgitg[[simdgroup_index_in_threadgroup]],
uint tiisg[[thread_index_in_simdgroup]],
uint ntg[[threads_per_threadgroup]]) {
const int64_t ne = ne00*ne01*ne02;
const int64_t gs = ne00*ne01*((ne02 + n_groups - 1) / n_groups);
int start = tgpig * gs;
int end = start + gs;
start += tpitg;
if (end >= ne) {
end = ne;
}
float tmp = 0.0f; // partial sum for thread in warp
for (int j = start; j < end; j += ntg) {
tmp += src0[j];
}
threadgroup_barrier(mem_flags::mem_threadgroup);
tmp = simd_sum(tmp);
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = tmp;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
tmp = buf[tiisg];
tmp = simd_sum(tmp);
}
const float mean = tmp / gs;
tmp = 0.0f;
for (int j = start; j < end; j += ntg) {
float xi = src0[j] - mean;
dst[j] = xi;
tmp += xi * xi;
}
tmp = simd_sum(tmp);
if (ntg > N_SIMDWIDTH) {
if (sgitg == 0) {
buf[tiisg] = 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
buf[sgitg] = tmp;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
tmp = buf[tiisg];
tmp = simd_sum(tmp);
}
const float variance = tmp / gs;
const float scale = 1.0f/sqrt(variance + eps);
for (int j = start; j < end; j += ntg) {
dst[j] *= scale;
}
}
// function for calculate inner product between half a q4_0 block and 16 floats (yl), sumy is SUM(yl[i])
// il indicates where the q4 quants begin (0 or QK4_0/4)
// we assume that the yl's have been multiplied with the appropriate scale factor
// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096)
inline float block_q_n_dot_y(device const block_q4_0 * qb_curr, float sumy, thread float * yl, int il) {
float d = qb_curr->d;
float acc[4] = { 0.0f, 0.0f, 0.0f, 0.0f };
device const uint16_t * qs = ((device const uint16_t *) qb_curr + 1 + il/2);
for (int i = 0; i < 8; i += 2) {
acc[0] += yl[i + 0] * (qs[i / 2] & 0x000F);
acc[1] += yl[i + 1] * (qs[i / 2] & 0x0F00);
acc[2] += yl[i + 8] * (qs[i / 2] & 0x00F0);
acc[3] += yl[i + 9] * (qs[i / 2] & 0xF000);
}
return d * (sumy * -8.f + acc[0] + acc[1] + acc[2] + acc[3]);
}
// function for calculate inner product between half a q4_1 block and 16 floats (yl), sumy is SUM(yl[i])
// il indicates where the q4 quants begin (0 or QK4_0/4)
// we assume that the yl's have been multiplied with the appropriate scale factor
// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096)
inline float block_q_n_dot_y(device const block_q4_1 * qb_curr, float sumy, thread float * yl, int il) {
float d = qb_curr->d;
float m = qb_curr->m;
float acc[4] = { 0.0f, 0.0f, 0.0f, 0.0f };
device const uint16_t * qs = ((device const uint16_t *) qb_curr + 2 + il/2);
for (int i = 0; i < 8; i+=2) {
acc[0] += yl[i + 0] * (qs[i / 2] & 0x000F);
acc[1] += yl[i + 1] * (qs[i / 2] & 0x0F00);
acc[2] += yl[i + 8] * (qs[i / 2] & 0x00F0);
acc[3] += yl[i + 9] * (qs[i / 2] & 0xF000);
}
return d * (acc[0] + acc[1] + acc[2] + acc[3]) + sumy * m;
}
// function for calculate inner product between half a q5_0 block and 16 floats (yl), sumy is SUM(yl[i])
// il indicates where the q5 quants begin (0 or QK5_0/4)
// we assume that the yl's have been multiplied with the appropriate scale factor
// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096)
inline float block_q_n_dot_y(device const block_q5_0 * qb_curr, float sumy, thread float * yl, int il) {
float d = qb_curr->d;
float acc[4] = { 0.0f, 0.0f, 0.0f, 0.0f };
device const uint16_t * qs = ((device const uint16_t *)qb_curr + 3 + il/2);
const uint32_t qh = *((device const uint32_t *)qb_curr->qh);
for (int i = 0; i < 8; i+=2) {
acc[0] += yl[i + 0] * ((qs[i / 2] & 0x000F) | ((qh >> (i+0+il ) << 4 ) & 0x00010));
acc[1] += yl[i + 1] * ((qs[i / 2] & 0x0F00) | ((qh >> (i+1+il ) << 12) & 0x01000));
acc[2] += yl[i + 8] * ((qs[i / 2] & 0x00F0) | ((qh >> (i+0+il+QK5_0/2) << 8 ) & 0x00100));
acc[3] += yl[i + 9] * ((qs[i / 2] & 0xF000) | ((qh >> (i+1+il+QK5_0/2) << 16) & 0x10000));
}
return d * (sumy * -16.f + acc[0] + acc[1] + acc[2] + acc[3]);
}
// function for calculate inner product between half a q5_1 block and 16 floats (yl), sumy is SUM(yl[i])
// il indicates where the q5 quants begin (0 or QK5_1/4)
// we assume that the yl's have been multiplied with the appropriate scale factor
// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096)
inline float block_q_n_dot_y(device const block_q5_1 * qb_curr, float sumy, thread float * yl, int il) {
float d = qb_curr->d;
float m = qb_curr->m;
float acc[4] = { 0.0f, 0.0f, 0.0f, 0.0f };
device const uint16_t * qs = ((device const uint16_t *)qb_curr + 4 + il/2);
const uint32_t qh = *((device const uint32_t *)qb_curr->qh);
for (int i = 0; i < 8; i+=2) {
acc[0] += yl[i + 0] * ((qs[i / 2] & 0x000F) | ((qh >> (i+0+il ) << 4 ) & 0x00010));
acc[1] += yl[i + 1] * ((qs[i / 2] & 0x0F00) | ((qh >> (i+1+il ) << 12) & 0x01000));
acc[2] += yl[i + 8] * ((qs[i / 2] & 0x00F0) | ((qh >> (i+0+il+QK5_0/2) << 8 ) & 0x00100));
acc[3] += yl[i + 9] * ((qs[i / 2] & 0xF000) | ((qh >> (i+1+il+QK5_0/2) << 16) & 0x10000));
}
return d * (acc[0] + acc[1] + acc[2] + acc[3]) + sumy * m;
}
// putting them in the kernel cause a significant performance penalty
#define N_DST 4 // each SIMD group works on 4 rows
#define N_SIMDGROUP 2 // number of SIMD groups in a thread group
//Note: This is a template, but strictly speaking it only applies to
// quantizations where the block size is 32. It also does not
// guard against the number of rows not being divisible by
// N_DST, so this is another explicit assumption of the implementation.
template<typename block_q_type, int nr, int nsg, int nw, typename args_t>
void mul_vec_q_n_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK4_0;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * nsg + sgitg) * nr;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
//const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
//device const block_q_type * x = (device const block_q_type *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
// pointers to src0 rows
device const block_q_type * ax[nr];
for (int row = 0; row < nr; ++row) {
const uint64_t offset0 = (first_row + row)*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
ax[row] = (device const block_q_type *) ((device char *) src0 + offset0);
}
float yl[16]; // src1 vector cache
float sumf[nr] = {0.f};
const short ix = (tiisg/2);
const short il = (tiisg%2)*8;
device const float * yb = y + ix*QK4_0 + il;
// each thread in a SIMD group deals with half a block.
for (int ib = ix; ib < nb; ib += nw/2) {
float sumy[2] = { 0.f, 0.f };
#pragma unroll
for (int i = 0; i < 8; i += 2) {
sumy[0] += yb[i + 0] + yb[i + 1];
yl[i + 0] = yb[i + 0];
yl[i + 1] = yb[i + 1]/256.f;
sumy[1] += yb[i + 16] + yb[i + 17];
yl[i + 8] = yb[i + 16]/16.f;
yl[i + 9] = yb[i + 17]/4096.f;
}
#pragma unroll
for (int row = 0; row < nr; row++) {
sumf[row] += block_q_n_dot_y(ax[row] + ib, sumy[0] + sumy[1], yl, il);
}
yb += QK4_0 * 16;
}
device float * dst_f32 = (device float *) dst + im*args.ne0*args.ne1 + r1*args.ne0;
for (int row = 0; row < nr; ++row) {
const float tot = simd_sum(sumf[row]);
if (tiisg == 0 && first_row + row < args.ne01) {
dst_f32[first_row + row] = tot;
}
}
}
kernel void kernel_mul_mv_q4_0_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
mul_vec_q_n_f32_impl<block_q4_0, N_DST, N_SIMDGROUP, N_SIMDWIDTH, constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
kernel void kernel_mul_mv_q4_1_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
mul_vec_q_n_f32_impl<block_q4_1, N_DST, N_SIMDGROUP, N_SIMDWIDTH, constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
kernel void kernel_mul_mv_q5_0_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
mul_vec_q_n_f32_impl<block_q5_0, N_DST, N_SIMDGROUP, N_SIMDWIDTH, constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
kernel void kernel_mul_mv_q5_1_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
mul_vec_q_n_f32_impl<block_q5_1, N_DST, N_SIMDGROUP, N_SIMDWIDTH, constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
#define NB_Q8_0 8
template<typename args_t>
void kernel_mul_mv_q8_0_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nr = N_DST;
const int nsg = N_SIMDGROUP;
const int nw = N_SIMDWIDTH;
const int nb = args.ne00/QK8_0;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0*nsg + sgitg)*nr;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
//const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
//device const block_q8_0 * x = (device const block_q8_0 *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
// pointers to src0 rows
device const block_q8_0 * ax[nr];
for (int row = 0; row < nr; ++row) {
const uint64_t offset0 = (first_row + row)*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
ax[row] = (device const block_q8_0 *) ((device char *) src0 + offset0);
}
float yl[NB_Q8_0];
float sumf[nr] = { 0.f };
const short ix = tiisg/4;
const short il = tiisg%4;
device const float * yb = y + ix*QK8_0 + il*NB_Q8_0;
// each thread in a SIMD group deals with NB_Q8_0 quants at a time
for (int ib = ix; ib < nb; ib += nw/4) {
for (short i = 0; i < NB_Q8_0; ++i) {
yl[i] = yb[i];
}
for (int row = 0; row < nr; row++) {
device const int8_t * qs = ax[row][ib].qs + il*NB_Q8_0;
float sumq = 0.f;
for (short iq = 0; iq < NB_Q8_0; ++iq) {
sumq += qs[iq] * yl[iq];
}
sumf[row] += sumq*ax[row][ib].d;
}
yb += nw*NB_Q8_0;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < nr; ++row) {
const float tot = simd_sum(sumf[row]);
if (tiisg == 0 && first_row + row < args.ne01) {
dst_f32[first_row + row] = tot;
}
}
}
[[host_name("kernel_mul_mv_q8_0_f32")]]
kernel void kernel_mul_mv_q8_0_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_q8_0_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
#define N_MV_T_T 4
template<typename T0, typename T04, typename T1, typename T14, typename args_t>
void kernel_mul_mv_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig,
ushort tiisg) {
const int r0 = tgpig.x;
const int rb = tgpig.y*N_MV_T_T;
const int im = tgpig.z;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = r0*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
device const T0 * x = (device const T0 *) (src0 + offset0);
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1;
if (args.ne00 < 128) {
for (int row = 0; row < N_MV_T_T; ++row) {
int r1 = rb + row;
if (r1 >= args.ne11) {
break;
}
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const T1 * y = (device const T1 *) (src1 + offset1);
float sumf = 0;
for (int i = tiisg; i < args.ne00; i += 32) {
sumf += (T0) x[i] * (T1) y[i];
}
float all_sum = simd_sum(sumf);
if (tiisg == 0) {
dst_f32[(uint64_t)r1*args.ne0 + r0] = all_sum;
}
}
} else {
device const T04 * x4 = (device const T04 *) x;
for (int row = 0; row < N_MV_T_T; ++row) {
int r1 = rb + row;
if (r1 >= args.ne11) {
break;
}
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const T1 * y = (device const T1 *) (src1 + offset1);
device const T14 * y4 = (device const T14 *) y;
float sumf = 0;
for (int i = tiisg; i < args.ne00/4; i += 32) {
sumf += dot((float4) x4[i], (float4) y4[i]);
}
float all_sum = simd_sum(sumf);
if (tiisg == 0) {
for (int i = 4*(args.ne00/4); i < args.ne00; ++i) all_sum += (float) (x[i] * y[i]);
dst_f32[(uint64_t)r1*args.ne0 + r0] = all_sum;
}
}
}
}
template<typename T0, typename T04, typename T1, typename T14>
kernel void kernel_mul_mv(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]]) {
kernel_mul_mv_impl<T0, T04, T1, T14, constant ggml_metal_kargs_mul_mv &>(
args,
src0,
src1,
dst,
tgpig,
tiisg);
}
typedef decltype(kernel_mul_mv<half, half4, half, half4>) mul_mv_t;
template [[host_name("kernel_mul_mv_f32_f32")]] kernel mul_mv_t kernel_mul_mv<float, float4, float, float4>;
template [[host_name("kernel_mul_mv_f16_f32")]] kernel mul_mv_t kernel_mul_mv<half, half4, float, float4>;
template [[host_name("kernel_mul_mv_f16_f16")]] kernel mul_mv_t kernel_mul_mv<half, half4, half, half4>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_mul_mv_bf16_f32")]] kernel mul_mv_t kernel_mul_mv<bfloat, bfloat4, float, float4>;
template [[host_name("kernel_mul_mv_bf16_bf16")]] kernel mul_mv_t kernel_mul_mv<bfloat, bfloat4, bfloat, bfloat4>;
#endif
template<typename T, typename T4>
kernel void kernel_mul_mv_1row(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]]) {
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = r0*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const T * x = (device const T *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
float sumf = 0;
if (args.ne00 < 128) {
for (int i = tiisg; i < args.ne00; i += 32) {
sumf += (float) x[i] * (float) y[i];
}
float all_sum = simd_sum(sumf);
if (tiisg == 0) {
dst_f32[r0] = all_sum;
}
} else {
device const T4 * x4 = (device const T4 *) x;
device const float4 * y4 = (device const float4 *) y;
for (int i = tiisg; i < args.ne00/4; i += 32) {
sumf += dot((float4) x4[i], y4[i]);
}
float all_sum = simd_sum(sumf);
if (tiisg == 0) {
for (int i = 4*(args.ne00/4); i < args.ne00; ++i) all_sum += (float) (x[i] * y[i]);
dst_f32[r0] = all_sum;
}
}
}
typedef decltype(kernel_mul_mv_1row<half, half4>) mul_mv_1row_t;
template [[host_name("kernel_mul_mv_f16_f32_1row")]] kernel mul_mv_1row_t kernel_mul_mv_1row<half, half4>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_mul_mv_bf16_f32_1row")]] kernel mul_mv_1row_t kernel_mul_mv_1row<bfloat, bfloat4>;
#endif
// Assumes row size (ne00) is a multiple of 4
template<typename T, typename T4>
kernel void kernel_mul_mv_l4(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]]) {
const int nrows = args.ne11;
const int r0 = tgpig.x;
const int im = tgpig.z;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = r0*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
device const T4 * x4 = (device const T4 *) (src0 + offset0);
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1;
for (int r1 = 0; r1 < nrows; ++r1) {
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const float4 * y4 = (device const float4 *) (src1 + offset1);
float sumf = 0;
for (int i = tiisg; i < args.ne00/4; i += 32) {
sumf += dot((float4) x4[i], y4[i]);
}
float all_sum = simd_sum(sumf);
if (tiisg == 0) {
dst_f32[(uint64_t)r1*args.ne0 + r0] = all_sum;
}
}
}
typedef decltype(kernel_mul_mv_l4<half, half4>) mul_mv_l4_t;
template [[host_name("kernel_mul_mv_f16_f32_l4")]] kernel mul_mv_l4_t kernel_mul_mv_l4<half, half4>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_mul_mv_bf16_f32_l4")]] kernel mul_mv_l4_t kernel_mul_mv_l4<bfloat, bfloat4>;
#endif
static float rope_yarn_ramp(const float low, const float high, const int i0) {
const float y = (i0 / 2 - low) / max(0.001f, high - low);
return 1.0f - min(1.0f, max(0.0f, y));
}
// YaRN algorithm based on LlamaYaRNScaledRotaryEmbedding.py from https://github.com/jquesnelle/yarn
// MIT licensed. Copyright (c) 2023 Jeffrey Quesnelle and Bowen Peng.
static void rope_yarn(
float theta_extrap, float freq_scale, float corr_dims[2], int i0, float ext_factor, float mscale,
thread float * cos_theta, thread float * sin_theta) {
// Get n-d rotational scaling corrected for extrapolation
float theta_interp = freq_scale * theta_extrap;
float theta = theta_interp;
if (ext_factor != 0.0f) {
float ramp_mix = rope_yarn_ramp(corr_dims[0], corr_dims[1], i0) * ext_factor;
theta = theta_interp * (1 - ramp_mix) + theta_extrap * ramp_mix;
// Get n-d magnitude scaling corrected for interpolation
mscale *= 1.0f + 0.1f * log(1.0f / freq_scale);
}
*cos_theta = cos(theta) * mscale;
*sin_theta = sin(theta) * mscale;
}
// Apparently solving `n_rot = 2pi * x * base^((2 * max_pos_emb) / n_dims)` for x, we get
// `corr_fac(n_rot) = n_dims * log(max_pos_emb / (n_rot * 2pi)) / (2 * log(base))`
static float rope_yarn_corr_factor(int n_dims, int n_ctx_orig, float n_rot, float base) {
return n_dims * log(n_ctx_orig / (n_rot * 2 * M_PI_F)) / (2 * log(base));
}
static void rope_yarn_corr_dims(
int n_dims, int n_ctx_orig, float freq_base, float beta_fast, float beta_slow, float dims[2]
) {
// start and end correction dims
dims[0] = max(0.0f, floor(rope_yarn_corr_factor(n_dims, n_ctx_orig, beta_fast, freq_base)));
dims[1] = min(n_dims - 1.0f, ceil(rope_yarn_corr_factor(n_dims, n_ctx_orig, beta_slow, freq_base)));
}
template<typename T>
kernel void kernel_rope_norm(
constant ggml_metal_kargs_rope & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
ushort tiitg[[thread_index_in_threadgroup]],
ushort3 tptg [[threads_per_threadgroup]],
uint3 tgpig[[threadgroup_position_in_grid]]) {
const int i3 = tgpig[2];
const int i2 = tgpig[1];
const int i1 = tgpig[0];
float corr_dims[2];
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
device const int32_t * pos = (device const int32_t *) src1;
const float theta_base = (float) pos[i2];
const float inv_ndims = -1.f/args.n_dims;
float cos_theta;
float sin_theta;
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
if (i0 < args.n_dims) {
const int ic = i0/2;
const float theta = theta_base * pow(args.freq_base, inv_ndims*i0);
const float freq_factor = src2 != src0 ? ((device const float *) src2)[ic] : 1.0f;
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
const float x0 = src[0];
const float x1 = src[1];
dst_data[0] = x0*cos_theta - x1*sin_theta;
dst_data[1] = x0*sin_theta + x1*cos_theta;
} else {
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
dst_data[0] = src[0];
dst_data[1] = src[1];
}
}
}
template<typename T>
kernel void kernel_rope_neox(
constant ggml_metal_kargs_rope & args,
device const char * src0,
device const char * src1,
device const char * src2,
device char * dst,
ushort tiitg[[thread_index_in_threadgroup]],
ushort3 tptg [[threads_per_threadgroup]],
uint3 tgpig[[threadgroup_position_in_grid]]) {
const int i3 = tgpig[2];
const int i2 = tgpig[1];
const int i1 = tgpig[0];
float corr_dims[2];
rope_yarn_corr_dims(args.n_dims, args.n_ctx_orig, args.freq_base, args.beta_fast, args.beta_slow, corr_dims);
device const int32_t * pos = (device const int32_t *) src1;
const float theta_base = (float) pos[i2];
const float inv_ndims = -1.f/args.n_dims;
float cos_theta;
float sin_theta;
for (int i0 = 2*tiitg; i0 < args.ne0; i0 += 2*tptg.x) {
if (i0 < args.n_dims) {
const int ic = i0/2;
const float theta = theta_base * pow(args.freq_base, inv_ndims*i0);
const float freq_factor = src2 != src0 ? ((device const float *) src2)[ic] : 1.0f;
rope_yarn(theta/freq_factor, args.freq_scale, corr_dims, i0, args.ext_factor, args.attn_factor, &cos_theta, &sin_theta);
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + ic*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + ic*args.nb0);
const float x0 = src[0];
const float x1 = src[args.n_dims/2];
dst_data[0] = x0*cos_theta - x1*sin_theta;
dst_data[args.n_dims/2] = x0*sin_theta + x1*cos_theta;
} else {
device const T * const src = (device T *)(src0 + i3*args.nb03 + i2*args.nb02 + i1*args.nb01 + i0*args.nb00);
device T * dst_data = (device T *)( dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
dst_data[0] = src[0];
dst_data[1] = src[1];
}
}
}
typedef decltype(kernel_rope_norm<float>) kernel_rope_norm_t;
typedef decltype(kernel_rope_neox<float>) kernel_rope_neox_t;
template [[host_name("kernel_rope_norm_f32")]] kernel kernel_rope_norm_t kernel_rope_norm<float>;
template [[host_name("kernel_rope_norm_f16")]] kernel kernel_rope_norm_t kernel_rope_norm<half>;
template [[host_name("kernel_rope_neox_f32")]] kernel kernel_rope_neox_t kernel_rope_neox<float>;
template [[host_name("kernel_rope_neox_f16")]] kernel kernel_rope_neox_t kernel_rope_neox<half>;
typedef void (im2col_t)(
device const float * x,
device char * dst,
constant int32_t & ofs0,
constant int32_t & ofs1,
constant int32_t & IW,
constant int32_t & IH,
constant int32_t & CHW,
constant int32_t & s0,
constant int32_t & s1,
constant int32_t & p0,
constant int32_t & p1,
constant int32_t & d0,
constant int32_t & d1,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template <typename T>
kernel void kernel_im2col(
device const float * x,
device char * dst,
constant int32_t & ofs0,
constant int32_t & ofs1,
constant int32_t & IW,
constant int32_t & IH,
constant int32_t & CHW,
constant int32_t & s0,
constant int32_t & s1,
constant int32_t & p0,
constant int32_t & p1,
constant int32_t & d0,
constant int32_t & d1,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int32_t iiw = tgpig[2] * s0 + tpitg[2] * d0 - p0;
const int32_t iih = tgpig[1] * s1 + tpitg[1] * d1 - p1;
const int32_t offset_dst =
(tpitg[0] * tgpg[1] * tgpg[2] + tgpig[1] * tgpg[2] + tgpig[2]) * CHW +
(tgpig[0] * (ntg[1] * ntg[2]) + tpitg[1] * ntg[2] + tpitg[2]);
device T * pdst = (device T *) (dst);
if (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW) {
pdst[offset_dst] = 0.0f;
} else {
const int32_t offset_src = tpitg[0] * ofs0 + tgpig[0] * ofs1;
pdst[offset_dst] = x[offset_src + iih * IW + iiw];
}
}
template [[host_name("kernel_im2col_f32")]] kernel im2col_t kernel_im2col<float>;
template [[host_name("kernel_im2col_f16")]] kernel im2col_t kernel_im2col<half>;
typedef void (im2col_ext_t)(
device const float * x,
device char * dst,
constant int32_t & ofs0,
constant int32_t & ofs1,
constant int32_t & IW,
constant int32_t & IH,
constant int32_t & CHW,
constant int32_t & s0,
constant int32_t & s1,
constant int32_t & p0,
constant int32_t & p1,
constant int32_t & d0,
constant int32_t & d1,
constant int32_t & N,
constant int32_t & KH,
constant int32_t & KW,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]);
template <typename T>
kernel void kernel_im2col_ext(
device const float * x,
device char * dst,
constant int32_t & ofs0,
constant int32_t & ofs1,
constant int32_t & IW,
constant int32_t & IH,
constant int32_t & CHW,
constant int32_t & s0,
constant int32_t & s1,
constant int32_t & p0,
constant int32_t & p1,
constant int32_t & d0,
constant int32_t & d1,
constant int32_t & N,
constant int32_t & KH,
constant int32_t & KW,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tgpg[[threadgroups_per_grid]], // tgpg[0] = D x IC x KH x KW, CHW = IC x KH x KW
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) { // [M, 1, 1]
const int32_t KHW = KH * KW; // KHW == ntg[1] * ntg[2], KW == ntg[2]
const int32_t d = tgpig[0] / CHW;
const int32_t chw = tgpig[0] % CHW;
const int32_t tgpig_0 = chw / KHW; // 0 ~ (IC - 1)
const int32_t HW = tgpig[0] % KHW;
const int32_t tpitg_0 = (d * ntg[0]) + tpitg[0];
if (tpitg_0 >= N) {
return;
}
const int32_t tpitg_1 = HW / KW;
const int32_t tpitg_2 = HW % KW;
const int32_t iiw = tgpig[2] * s0 + tpitg_2 * d0 - p0;
const int32_t iih = tgpig[1] * s1 + tpitg_1 * d1 - p1;
const int32_t offset_dst =
(tpitg_0 * tgpg[1] * tgpg[2] + tgpig[1] * tgpg[2] + tgpig[2]) * CHW +
(tgpig_0 * KHW + tpitg_1 * KW + tpitg_2);
device T * pdst = (device T *) (dst);
if (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW) {
pdst[offset_dst] = 0.0f;
} else {
const int32_t offset_src = tpitg_0 * ofs0 + tgpig_0 * ofs1;
pdst[offset_dst] = x[offset_src + iih * IW + iiw];
}
}
template [[host_name("kernel_im2col_ext_f32")]] kernel im2col_ext_t kernel_im2col_ext<float>;
template [[host_name("kernel_im2col_ext_f16")]] kernel im2col_ext_t kernel_im2col_ext<half>;
kernel void kernel_upscale_f32(
device const char * src0,
device char * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int64_t & ne02,
constant int64_t & ne03,
constant uint64_t & nb00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant uint64_t & nb03,
constant int64_t & ne0,
constant int64_t & ne1,
constant int64_t & ne2,
constant int64_t & ne3,
constant uint64_t & nb0,
constant uint64_t & nb1,
constant uint64_t & nb2,
constant uint64_t & nb3,
constant float & sf0,
constant float & sf1,
constant float & sf2,
constant float & sf3,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t i3 = tgpig.z;
const int64_t i2 = tgpig.y;
const int64_t i1 = tgpig.x;
const int64_t i03 = i3/sf3;
const int64_t i02 = i2/sf2;
const int64_t i01 = i1/sf1;
for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) {
const int64_t i00 = i0/sf0;
device const float * src0_ptr = (device const float *) (src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00);
device float * dst_ptr = (device float *) (dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
dst_ptr[0] = src0_ptr[0];
}
}
kernel void kernel_pad_f32(
device const char * src0,
device char * dst,
constant int64_t & ne00,
constant int64_t & ne01,
constant int64_t & ne02,
constant int64_t & ne03,
constant uint64_t & nb00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant uint64_t & nb03,
constant int64_t & ne0,
constant int64_t & ne1,
constant int64_t & ne2,
constant int64_t & ne3,
constant uint64_t & nb0,
constant uint64_t & nb1,
constant uint64_t & nb2,
constant uint64_t & nb3,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t i3 = tgpig.z;
const int64_t i2 = tgpig.y;
const int64_t i1 = tgpig.x;
const int64_t i03 = i3;
const int64_t i02 = i2;
const int64_t i01 = i1;
device const float * src0_ptr = (device const float *) (src0 + i03*nb03 + i02*nb02 + i01*nb01);
device float * dst_ptr = (device float *) (dst + i3*nb3 + i2*nb2 + i1*nb1);
if (i1 < ne01 && i2 < ne02 && i3 < ne03) {
for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) {
if (i0 < ne00) {
dst_ptr[i0] = src0_ptr[i0];
} else {
dst_ptr[i0] = 0.0f;
}
}
return;
}
for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) {
dst_ptr[i0] = 0.0f;
}
}
kernel void kernel_arange_f32(
device char * dst,
constant int64_t & ne0,
constant float & start,
constant float & step,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
device float * dst_ptr = (device float *) dst;
for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) {
dst_ptr[i0] = start + step * i0;
}
}
kernel void kernel_timestep_embedding_f32(
device const char * src0,
device char * dst,
constant uint64_t & nb1,
constant int & dim,
constant int & max_period,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
int i = tgpig.x;
device float * embed_data = (device float *)(dst + i*nb1);
int half_ = dim / 2;
for (int j = tpitg.x; j < half_; j += ntg.x) {
float timestep = ((device float *)src0)[i];
float freq = (float)exp(-log((float)max_period) * j / half_);
float arg = timestep * freq;
embed_data[j ] = cos(arg);
embed_data[j + half_] = sin(arg);
}
if (dim % 2 != 0 && tpitg.x == 0) {
embed_data[dim] = 0.f;
}
}
// bitonic sort implementation following the CUDA kernels as reference
typedef void (argsort_t)(
device const float * x,
device int32_t * dst,
constant int64_t & ncols,
constant int64_t & ncols_pad,
threadgroup int32_t * shared_values [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]]);
template<ggml_sort_order order>
kernel void kernel_argsort_f32_i32(
device const float * x,
device int32_t * dst,
constant int64_t & ncols,
constant int64_t & ncols_pad,
threadgroup int32_t * shared_values [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]]) {
// bitonic sort
int col = tpitg[0];
int row = tgpig[1];
if (col >= ncols_pad) return;
device const float * x_row = x + row * ncols;
threadgroup int32_t * dst_row = shared_values;
// initialize indices
dst_row[col] = col;
threadgroup_barrier(mem_flags::mem_threadgroup);
for (int k = 2; k <= ncols_pad; k *= 2) {
for (int j = k / 2; j > 0; j /= 2) {
int ixj = col ^ j;
if (ixj > col) {
if ((col & k) == 0) {
if (dst_row[col] >= ncols ||
(dst_row[ixj] < ncols && (order == GGML_SORT_ORDER_ASC ?
x_row[dst_row[col]] > x_row[dst_row[ixj]] :
x_row[dst_row[col]] < x_row[dst_row[ixj]]))
) {
SWAP(dst_row[col], dst_row[ixj]);
}
} else {
if (dst_row[ixj] >= ncols ||
(dst_row[col] < ncols && (order == GGML_SORT_ORDER_ASC ?
x_row[dst_row[col]] < x_row[dst_row[ixj]] :
x_row[dst_row[col]] > x_row[dst_row[ixj]]))
) {
SWAP(dst_row[col], dst_row[ixj]);
}
}
}
threadgroup_barrier(mem_flags::mem_threadgroup);
}
}
// copy the result to dst without the padding
if (col < ncols) {
dst[row * ncols + col] = dst_row[col];
}
}
template [[host_name("kernel_argsort_f32_i32_asc")]] kernel argsort_t kernel_argsort_f32_i32<GGML_SORT_ORDER_ASC>;
template [[host_name("kernel_argsort_f32_i32_desc")]] kernel argsort_t kernel_argsort_f32_i32<GGML_SORT_ORDER_DESC>;
kernel void kernel_leaky_relu_f32(
device const float * src0,
device float * dst,
constant float & slope,
uint tpig[[thread_position_in_grid]]) {
dst[tpig] = src0[tpig] > 0.0f ? src0[tpig] : src0[tpig] * slope;
}
// ref: https://arxiv.org/pdf/2307.08691.pdf
template<
typename q_t, // query types in shared memory
typename q4_t,
typename q8x8_t,
typename k_t, // key types in shared memory
typename k4x4_t,
typename k8x8_t,
typename v_t, // value types in shared memory
typename v4x4_t,
typename v8x8_t,
typename qk_t, // Q*K types
typename qk8x8_t,
typename s_t, // soft-max types
typename s8x8_t,
typename o_t, // attention accumulation types
typename o4_t,
typename o8x8_t,
typename kd4x4_t, // key type in device memory
short nl_k,
void (*deq_k)(device const kd4x4_t *, short, thread k4x4_t &),
typename vd4x4_t, // key type in device memory
short nl_v,
void (*deq_v)(device const vd4x4_t *, short, thread v4x4_t &),
short D, // head size
short Q = 8, // queries per threadgroup
short KV = 8, // key/value processed per each simdgroup
short C = 32> // cache items per threadgroup
kernel void kernel_flash_attn_ext(
constant ggml_metal_kargs_flash_attn_ext & args,
device const char * q,
device const char * k,
device const char * v,
device const char * mask,
device char * dst,
threadgroup half * shmem_f16 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 ntg[[threads_per_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
const short nsg = ntg.y; // number of simdgroups
const int iq3 = tgpig[2];
const int iq2 = tgpig[1];
const int iq1 = tgpig[0]*Q;
const short D4 = D/4;
const short D8 = D/8;
const short D16 = D/16;
const short NW = N_SIMDWIDTH;
const short SH = (2*C + Q); // shared memory per simdgroup (s_t == float)
const short TS = nsg*SH; // shared memory size per query in (s_t == float)
const short T = D + 2*TS; // shared memory size per query in (half)
threadgroup q_t * sq = (threadgroup q_t *) (shmem_f16 + 0*D); // holds the query data
threadgroup q4_t * sq4 = (threadgroup q4_t *) (shmem_f16 + 0*D); // same as above but in q4_t
threadgroup o_t * so = (threadgroup o_t *) (shmem_f16 + 0*D); // reuse query data for accumulation
threadgroup o4_t * so4 = (threadgroup o4_t *) (shmem_f16 + 0*D); // same as above but in o4_t
threadgroup s_t * ss = (threadgroup s_t *) (shmem_f16 + 2*sgitg*SH + Q*D); // scratch buffer for attention, mask and diagonal matrix
threadgroup k_t * sk = (threadgroup k_t *) (shmem_f16 + sgitg*(4*16*KV) + Q*T); // scratch buffer to load K in shared memory
threadgroup k4x4_t * sk4x4 = (threadgroup k4x4_t *) (shmem_f16 + sgitg*(4*16*KV) + Q*T); // same as above but in k4x4_t
threadgroup v_t * sv = (threadgroup v_t *) (shmem_f16 + sgitg*(4*16*KV) + Q*T); // scratch buffer to load V in shared memory
threadgroup v4x4_t * sv4x4 = (threadgroup v4x4_t *) (shmem_f16 + sgitg*(4*16*KV) + Q*T); // same as above but in v4x4_t
// store the result for all queries in local memory in 8x8 matrices (the O matrix from the paper)
o8x8_t lo[D8];
// load heads from Q to shared memory
for (short j = sgitg; j < Q; j += nsg) {
device const float4 * q4 = (device const float4 *) ((device const char *) q + ((iq1 + j)*args.nb01 + iq2*args.nb02 + iq3*args.nb03));
for (short i = tiisg; i < D4; i += NW) {
if (iq1 + j < args.ne01) {
sq4[j*D4 + i] = (q4_t) q4[i];
} else {
sq4[j*D4 + i] = (q4_t) 0.0f;
}
}
}
// zero out lo
for (short i = 0; i < D8; ++i) {
lo[i] = make_filled_simdgroup_matrix<o_t, 8>((o_t) 0.0f);
}
// zero out shared memory SH
for (short j = 0; j < Q; ++j) {
for (short i = tiisg; i < SH; i += NW) {
ss[j*TS + i] = 0.0f;
}
}
threadgroup_barrier(mem_flags::mem_threadgroup);
{
half S[Q] = { [0 ... Q-1] = 0.0f };
half M[Q] = { [0 ... Q-1] = -__FLT16_MAX__/2 };
// thread indices inside the simdgroup
// TODO: see if we can utilize quad-group functions for better performance
// https://developer.apple.com/metal/Metal-Shading-Language-Specification.pdf (6.9.3)
const short tx = tiisg%4;
const short ty = tiisg/4;
// broadcast kv
//const short rk2 = args.ne02/args.ne12;
//const short rk3 = args.ne03/args.ne13;
const short ikv2 = iq2/(args.ne02/args.ne_12_2);
const short ikv3 = iq3/(args.ne03/args.ne_12_3);
// load the queries from shared memory into local memory
q8x8_t mq[D8];
for (short i = 0; i < D8; ++i) {
simdgroup_load(mq[i], sq + i*8, D);
}
const bool has_mask = mask != q;
half slope = 1.0f;
// ALiBi
if (args.max_bias > 0.0f) {
const short h = iq2;
const half base = h < args.n_head_log2 ? args.m0 : args.m1;
const short exph = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;
slope = pow(base, exph);
}
// loop over the KV cache
// each simdgroup handles blocks of Q rows and C columns
for (int ic0 = 0; ic0 < args.ne11; ic0 += C*nsg) {
const int ic = ic0 + C*sgitg;
if (ic >= args.ne11) {
break;
}
if (has_mask) {
// used to detect blocks full of -INF
half smax = -INFINITY;
// load the mask in shared memory
#pragma unroll(Q)
for (short j = 0; j < Q; ++j) {
device const half * pm = (device const half *) ((device const char *) mask + (iq1 + j)*args.nb31);
const half m = pm[ic + tiisg];
ss[j*TS + C + tiisg] = m;
smax = max(smax, m);
}
smax = simd_max(smax);
if (smax == -INFINITY) {
continue;
}
}
// Q*K^T
{
for (short cc = 0; cc < C/8; ++cc) {
qk8x8_t mqk = make_filled_simdgroup_matrix<qk_t, 8>((qk_t) 0.0f);
// this is compile-time check, so it does not have runtime overhead
if (is_same<kd4x4_t, k4x4_t>::value) {
// we can read directly from global memory
device const k_t * pk = (device const k_t *) ((device const char *) k + ((ic + 8*cc)*args.nb_12_1 + ikv2*args.nb_12_2 + ikv3*args.nb_12_3));
#pragma unroll(D8)
for (short i = 0; i < D8; ++i) {
k8x8_t mk;
simdgroup_load(mk, pk + i*8, args.nb_12_1/sizeof(k_t), 0, true); // transpose // TODO: use ne10
simdgroup_multiply_accumulate(mqk, mq[i], mk, mqk);
}
} else {
for (short ii = 0; ii < D16; ii += 4) {
device const kd4x4_t * pk4x4 = (device const kd4x4_t *) ((device const char *) k + ((ic + 8*cc + ty)*args.nb_12_1 + ikv2*args.nb_12_2 + ikv3*args.nb_12_3));
if (D16%4 == 0) {
// the head is evenly divisible by 4*16 = 64, so no need for bound checks
{
k4x4_t tmp;
deq_k(pk4x4 + (ii + tx)/nl_k, (ii + tx)%nl_k, tmp);
sk4x4[4*ty + tx] = tmp;
}
simdgroup_barrier(mem_flags::mem_threadgroup);
#pragma unroll(4)
for (short k = 0; k < 4; ++k) {
k8x8_t mk;
simdgroup_load(mk, sk + 16*k + 0*8, 4*16, 0, true); // transpose
simdgroup_multiply_accumulate(mqk, mq[2*(ii + k) + 0], mk, mqk);
simdgroup_load(mk, sk + 16*k + 1*8, 4*16, 0, true); // transpose
simdgroup_multiply_accumulate(mqk, mq[2*(ii + k) + 1], mk, mqk);
}
} else {
if (ii + tx < D16) {
k4x4_t tmp;
deq_k(pk4x4 + (ii + tx)/nl_k, (ii + tx)%nl_k, tmp);
sk4x4[4*ty + tx] = tmp;
}
simdgroup_barrier(mem_flags::mem_threadgroup);
for (short k = 0; k < 4 && ii + k < D16; ++k) {
k8x8_t mk;
simdgroup_load(mk, sk + 16*k + 0*8, 4*16, 0, true); // transpose
simdgroup_multiply_accumulate(mqk, mq[2*(ii + k) + 0], mk, mqk);
simdgroup_load(mk, sk + 16*k + 1*8, 4*16, 0, true); // transpose
simdgroup_multiply_accumulate(mqk, mq[2*(ii + k) + 1], mk, mqk);
}
}
}
}
// cast qk_t -> s_t
//s8x8_t mqks(1.0f);
//simdgroup_multiply(mqks, mqk, mqks);
//simdgroup_store(mqks, ss + 8*cc, TS, 0, false);
simdgroup_store(mqk, ss + 8*cc, TS, 0, false);
}
}
// online softmax
{
for (ushort j = 0; j < Q; ++j) {
const half m = M[j];
// scale and apply the logitcap / mask
half s = ss[j*TS + tiisg]*args.scale;
if (args.logit_softcap != 0.0f) {
s = args.logit_softcap*precise::tanh(s);
}
// mqk = mqk + mask*slope
s += slope*ss[j*TS + C + tiisg];
M[j] = simd_max(max(M[j], s));
const half ms = exp(m - M[j]);
const half vs = exp(s - M[j]);
S[j] = S[j]*ms + simd_sum(vs);
// the P matrix from the paper (Q rows, C columns)
ss[j*TS + tiisg] = vs;
// create a QxQ diagonal matrix for rescaling the output
if (tiisg == j) {
ss[j*TS + 2*C + j] = ms;
}
}
}
// O = diag(ms)*O
{
s8x8_t mm;
simdgroup_load(mm, ss + 2*C, TS, 0, false);
#pragma unroll(D8)
for (short i = 0; i < D8; ++i) {
simdgroup_multiply(lo[i], mm, lo[i]);
}
}
// O = O + (Q*K^T)*V
{
for (short cc = 0; cc < C/8; ++cc) {
s8x8_t ms;
simdgroup_load(ms, ss + 8*cc, TS, 0, false);
if (is_same<vd4x4_t, v4x4_t>::value) {
// we can read directly from global memory
device const v_t * pv = (device const v_t *) ((device const char *) v + ((ic + 8*cc)*args.nb_12_1 + ikv2*args.nb_12_2 + ikv3*args.nb_12_3));
#pragma unroll(D8)
for (short i = 0; i < D8; ++i) {
v8x8_t mv;
simdgroup_load(mv, pv + i*8, args.nb_12_1/sizeof(v_t), 0, false); // TODO: use ne20
simdgroup_multiply_accumulate(lo[i], ms, mv, lo[i]);
}
} else {
for (short ii = 0; ii < D16; ii += 4) {
device const vd4x4_t * pv4x4 = (device const vd4x4_t *) ((device const char *) v + ((ic + 8*cc + ty)*args.nb_12_1 + ikv2*args.nb_12_2 + ikv3*args.nb_12_3));
if (D16%4 == 0) {
// no need for bound checks
{
v4x4_t tmp;
deq_v(pv4x4 + (ii + tx)/nl_v, (ii + tx)%nl_v, tmp);
sv4x4[4*ty + tx] = tmp;
}
simdgroup_barrier(mem_flags::mem_threadgroup);
#pragma unroll(4)
for (short k = 0; k < 4; ++k) {
v8x8_t mv;
simdgroup_load(mv, sv + 16*k + 0*8, 4*16, 0, false);
simdgroup_multiply_accumulate(lo[2*(ii + k) + 0], ms, mv, lo[2*(ii + k) + 0]);
simdgroup_load(mv, sv + 16*k + 1*8, 4*16, 0, false);
simdgroup_multiply_accumulate(lo[2*(ii + k) + 1], ms, mv, lo[2*(ii + k) + 1]);
}
} else {
if (ii + tx < D16) {
v4x4_t tmp;
deq_v(pv4x4 + (ii + tx)/nl_v, (ii + tx)%nl_v, tmp);
sv4x4[4*ty + tx] = tmp;
}
simdgroup_barrier(mem_flags::mem_threadgroup);
for (short k = 0; k < 4 && ii + k < D16; ++k) {
v8x8_t mv;
simdgroup_load(mv, sv + 16*k + 0*8, 4*16, 0, false);
simdgroup_multiply_accumulate(lo[2*(ii + k) + 0], ms, mv, lo[2*(ii + k) + 0]);
simdgroup_load(mv, sv + 16*k + 1*8, 4*16, 0, false);
simdgroup_multiply_accumulate(lo[2*(ii + k) + 1], ms, mv, lo[2*(ii + k) + 1]);
}
}
}
}
}
}
}
// these are needed for reducing the results from the simdgroups (reuse the ss buffer)
for (short j = 0; j < Q; ++j) {
if (tiisg == 0) {
ss[j*TS + 0] = S[j];
ss[j*TS + 1] = M[j];
}
}
}
// reduce the warps sequentially
for (ushort sg = 1; sg < nsg; ++sg) {
half S = { 0.0f };
half M = { -__FLT16_MAX__/2 };
threadgroup_barrier(mem_flags::mem_threadgroup);
// each simdgroup stores its output to shared memory, reusing sq
if (sgitg == sg) {
for (short i = 0; i < D8; ++i) {
simdgroup_store(lo[i], so + i*8, D, 0, false);
}
}
threadgroup_barrier(mem_flags::mem_threadgroup);
// the first simdgroup accumulates the results from the other simdgroups
if (sgitg == 0) {
for (short j = 0; j < Q; ++j) {
const half S0 = ss[j*TS + 0];
const half S1 = ss[j*TS + sg*SH + 0];
const half M0 = ss[j*TS + 1];
const half M1 = ss[j*TS + sg*SH + 1];
M = max(M0, M1);
const half ms0 = exp(M0 - M);
const half ms1 = exp(M1 - M);
S = S0*ms0 + S1*ms1;
if (tiisg == 0) {
ss[j*TS + 0] = S;
ss[j*TS + 1] = M;
ss[j*TS + 2*C + j ] = ms0;
ss[j*TS + 2*C + j + sg*SH] = ms1;
}
}
// O_0 = diag(ms0)*O_0 + diag(ms1)*O_1
{
s8x8_t ms0;
s8x8_t ms1;
simdgroup_load(ms0, ss + 2*C, TS, 0, false);
simdgroup_load(ms1, ss + 2*C + sg*SH, TS, 0, false);
#pragma unroll(D8)
for (short i = 0; i < D8; ++i) {
o8x8_t t;
simdgroup_load (t, so + i*8, D, 0, false);
simdgroup_multiply(t, ms1, t);
simdgroup_multiply_accumulate(lo[i], ms0, lo[i], t);
}
}
}
}
// store result to shared memory (reuse sq)
if (sgitg == 0) {
for (short i = 0; i < D8; ++i) {
simdgroup_store(lo[i], so + i*8, D, 0, false);
}
}
device float4 * dst4 = (device float4 *) dst;
// final rescale with 1/S and store to global memory
if (sgitg == 0) {
for (short j = 0; j < Q && iq1 + j < args.ne01; ++j) {
const float S = ss[j*TS + 0];
for (short i = tiisg; i < D4; i += NW) {
dst4[((uint64_t)iq3*args.ne2*args.ne1 + iq2 + (uint64_t)(iq1 + j)*args.ne1)*D4 + i] = (float4) so4[j*D4 + i]/S;
}
}
}
}
// TODO: this is quite ugly. in the future these types will be hardcoded in the kernel, but for now keep them as
// template to be able to explore different combinations
//
#define FA_TYPES \
half, half4, simdgroup_half8x8, \
half, half4x4, simdgroup_half8x8, \
half, half4x4, simdgroup_half8x8, \
float, simdgroup_float8x8, \
float, simdgroup_float8x8, \
half, half4, simdgroup_half8x8
typedef decltype(kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 64>) flash_attn_ext_t;
template [[host_name("kernel_flash_attn_ext_f16_h64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 64>;
template [[host_name("kernel_flash_attn_ext_f16_h80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 80>;
template [[host_name("kernel_flash_attn_ext_f16_h96" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 96>;
template [[host_name("kernel_flash_attn_ext_f16_h112")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 112>;
template [[host_name("kernel_flash_attn_ext_f16_h128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 128>;
template [[host_name("kernel_flash_attn_ext_f16_h256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 256>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_flash_attn_ext_bf16_h64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 64>;
template [[host_name("kernel_flash_attn_ext_bf16_h80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 80>;
template [[host_name("kernel_flash_attn_ext_bf16_h96" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 96>;
template [[host_name("kernel_flash_attn_ext_bf16_h112")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 112>;
template [[host_name("kernel_flash_attn_ext_bf16_h128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 128>;
template [[host_name("kernel_flash_attn_ext_bf16_h256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 256>;
#endif
template [[host_name("kernel_flash_attn_ext_q4_0_h64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 64>;
template [[host_name("kernel_flash_attn_ext_q4_0_h80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 80>;
template [[host_name("kernel_flash_attn_ext_q4_0_h96" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 96>;
template [[host_name("kernel_flash_attn_ext_q4_0_h112")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 112>;
template [[host_name("kernel_flash_attn_ext_q4_0_h128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 128>;
template [[host_name("kernel_flash_attn_ext_q4_0_h256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 256>;
template [[host_name("kernel_flash_attn_ext_q4_1_h64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 64>;
template [[host_name("kernel_flash_attn_ext_q4_1_h80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 80>;
template [[host_name("kernel_flash_attn_ext_q4_1_h96" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 96>;
template [[host_name("kernel_flash_attn_ext_q4_1_h112")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 112>;
template [[host_name("kernel_flash_attn_ext_q4_1_h128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 128>;
template [[host_name("kernel_flash_attn_ext_q4_1_h256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 256>;
template [[host_name("kernel_flash_attn_ext_q5_0_h64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 64>;
template [[host_name("kernel_flash_attn_ext_q5_0_h80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 80>;
template [[host_name("kernel_flash_attn_ext_q5_0_h96" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 96>;
template [[host_name("kernel_flash_attn_ext_q5_0_h112")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 112>;
template [[host_name("kernel_flash_attn_ext_q5_0_h128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 128>;
template [[host_name("kernel_flash_attn_ext_q5_0_h256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 256>;
template [[host_name("kernel_flash_attn_ext_q5_1_h64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 64>;
template [[host_name("kernel_flash_attn_ext_q5_1_h80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 80>;
template [[host_name("kernel_flash_attn_ext_q5_1_h96" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 96>;
template [[host_name("kernel_flash_attn_ext_q5_1_h112")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 112>;
template [[host_name("kernel_flash_attn_ext_q5_1_h128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 128>;
template [[host_name("kernel_flash_attn_ext_q5_1_h256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 256>;
template [[host_name("kernel_flash_attn_ext_q8_0_h64" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 64>;
template [[host_name("kernel_flash_attn_ext_q8_0_h80" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 80>;
template [[host_name("kernel_flash_attn_ext_q8_0_h96" )]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 96>;
template [[host_name("kernel_flash_attn_ext_q8_0_h112")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 112>;
template [[host_name("kernel_flash_attn_ext_q8_0_h128")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 128>;
template [[host_name("kernel_flash_attn_ext_q8_0_h256")]] kernel flash_attn_ext_t kernel_flash_attn_ext<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 256>;
#undef FA_TYPES
template<
typename q4_t, // query types in shared memory
typename q4x4_t,
typename k4x4_t, // key types in shared memory
typename v4x4_t, // value types in shared memory
typename qk_t, // Q*K types
typename s_t, // soft-max types
typename s4_t,
typename s4x4_t,
typename o4x4_t, // attention accumulation types
typename kd4x4_t, // key type in device memory
short nl_k,
void (*deq_k)(device const kd4x4_t *, short, thread k4x4_t &),
typename vd4x4_t, // key type in device memory
short nl_v,
void (*deq_v)(device const vd4x4_t *, short, thread v4x4_t &),
short D, // head size
short Q = 1, // queries per threadgroup
short C = 32> // cache items per threadgroup
kernel void kernel_flash_attn_ext_vec(
constant ggml_metal_kargs_flash_attn_ext & args,
device const char * q,
device const char * k,
device const char * v,
device const char * mask,
device char * dst,
threadgroup half * shmem_f16 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 ntg[[threads_per_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
const short nsg = ntg.y; // number of simdgroups
const int iq3 = tgpig[2];
const int iq2 = tgpig[1];
const int iq1 = tgpig[0];
const short D4 = D/4;
const short D16 = D/16;
const short NW = N_SIMDWIDTH;
const short NL = NW/4; // note: this can be adjusted to support D%64 == 0 and D%32 == 0
const short SH = 2*C; // shared memory per simdgroup
const short T = D + nsg*SH; // shared memory size per query in (half)
//threadgroup q_t * sq = (threadgroup q_t *) (shmem_f16 + 0*D); // holds the query data
threadgroup q4_t * sq4 = (threadgroup q4_t *) (shmem_f16 + 0*D); // same as above but in q4_t
threadgroup q4x4_t * sq4x4 = (threadgroup q4x4_t *) (shmem_f16 + 0*D); // same as above but in q4x4_t
threadgroup s_t * ss = (threadgroup s_t *) (shmem_f16 + sgitg*SH + Q*D); // scratch buffer for attention
threadgroup s4_t * ss4 = (threadgroup s4_t *) (shmem_f16 + sgitg*SH + Q*D); // same as above but in s4_t
threadgroup half * sm = (threadgroup half *) (shmem_f16 + sgitg*SH + C + Q*D); // scratch buffer for mask
threadgroup o4x4_t * sr4x4 = (threadgroup o4x4_t *) (shmem_f16 + sgitg*D + Q*T); // scratch buffer for the results
// store the result for all queries in local memory in 8x8 matrices (the O matrix from the paper)
o4x4_t lo[D16/NL];
// load heads from Q to shared memory
device const float4 * q4 = (device const float4 *) ((device const char *) q + (iq1*args.nb01 + iq2*args.nb02 + iq3*args.nb03));
for (short i = tiisg; i < D4; i += NW) {
if (iq1 < args.ne01) {
sq4[i] = (q4_t) q4[i];
} else {
sq4[i] = (q4_t) 0.0f;
}
}
// zero out lo
for (short i = 0; i < D16/NL; ++i) {
lo[i] = (o4x4_t) 0.0f;
}
// zero out shared memory SH
for (short i = tiisg; i < SH/4; i += NW) {
ss4[i] = (s4_t) 0.0f;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
{
half S = 0.0f;
half M = -__FLT16_MAX__/2;
// thread indices inside the simdgroup
const short tx = tiisg%NL;
const short ty = tiisg/NL;
// broadcast kv
//const short rk2 = args.ne02/args.ne12;
//const short rk3 = args.ne03/args.ne13;
const short ikv2 = iq2/(args.ne02/args.ne_12_2);
const short ikv3 = iq3/(args.ne03/args.ne_12_3);
// load the queries from shared memory into local memory
q4x4_t mq[D16/NL];
#pragma unroll(D16/NL)
for (short ii = 0; ii < D16; ii += NL) {
mq[ii/NL] = sq4x4[ii + tx];
}
const bool has_mask = mask != q;
// pointer to the mask
device const half * pm = (device const half *) (mask + iq1*args.nb31);
half slope = 1.0f;
// ALiBi
if (args.max_bias > 0.0f) {
const short h = iq2;
const half base = h < args.n_head_log2 ? args.m0 : args.m1;
const short exph = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;
slope = pow(base, exph);
}
// loop over the KV cache
// each simdgroup handles blocks of Q rows and C columns
for (int ic0 = 0; ic0 < args.ne11; ic0 += C*nsg) {
const int ic = ic0 + C*sgitg;
if (ic >= args.ne11) {
break;
}
if (has_mask) {
sm[tiisg] = pm[ic + tiisg];
}
// Q*K^T
{
// each simdgroup processes 1 query and 4 (NW/NL) keys
for (short cc = 0; cc < C/4; ++cc) {
qk_t mqka[4] = { 0.0, 0.0, 0.0, 0.0 };
device const kd4x4_t * pk = (device const kd4x4_t *) ((device const char *) k + ((ic + 4*cc + ty)*args.nb_12_1 + ikv2*args.nb_12_2 + ikv3*args.nb_12_3));
#pragma unroll(D16/NL)
for (short ii = 0; ii < D16; ii += NL) {
const short i = ii + tx;
k4x4_t mk;
deq_k(pk + i/nl_k, i%nl_k, mk);
// note: this is less precise than the version below
//mqka[0] += dot(mq[ii/NL][0], mk[0]);
//mqka[1] += dot(mq[ii/NL][1], mk[1]);
//mqka[2] += dot(mq[ii/NL][2], mk[2]);
//mqka[3] += dot(mq[ii/NL][3], mk[3]);
mqka[0] += dot((float4) mq[ii/NL][0], (float4) mk[0]);
mqka[1] += dot((float4) mq[ii/NL][1], (float4) mk[1]);
mqka[2] += dot((float4) mq[ii/NL][2], (float4) mk[2]);
mqka[3] += dot((float4) mq[ii/NL][3], (float4) mk[3]);
}
qk_t mqk = mqka[0] + mqka[1] + mqka[2] + mqka[3];
// simdgroup reduce
// [ 0 .. 7] -> [ 0]
// [ 8 .. 15] -> [ 8]
// [16 .. 23] -> [16]
// [24 .. 31] -> [24]
//mqk += simd_shuffle_down(mqk, 16);
//mqk += simd_shuffle_down(mqk, 8);
mqk += simd_shuffle_down(mqk, 4);
mqk += simd_shuffle_down(mqk, 2);
mqk += simd_shuffle_down(mqk, 1);
// mqk = mqk*scale + mask*slope
if (tx == 0) {
mqk *= args.scale;
if (args.logit_softcap != 0.0f) {
mqk = args.logit_softcap*precise::tanh(mqk);
}
mqk += sm[4*cc + ty]*slope;
ss[4*cc + ty] = mqk;
}
}
}
simdgroup_barrier(mem_flags::mem_threadgroup);
// online softmax
{
const half m = M;
const half s = ss[tiisg];
M = simd_max(max(M, s));
const half ms = exp(m - M);
const half vs = exp(s - M);
S = S*ms + simd_sum(vs);
// the P matrix from the paper (Q rows, C columns)
ss[tiisg] = vs;
// O = diag(ms)*O
#pragma unroll(D16/NL)
for (short ii = 0; ii < D16; ii += NL) {
lo[ii/NL] *= ms;
}
}
simdgroup_barrier(mem_flags::mem_threadgroup);
// O = O + (Q*K^T)*V
{
for (short cc = 0; cc < C/4; ++cc) {
device const vd4x4_t * pv4 = (device const vd4x4_t *) ((device const char *) v + ((ic + 4*cc + ty)*args.nb_12_1 + ikv2*args.nb_12_2 + ikv3*args.nb_12_3));
const s4x4_t ms(ss[4*cc + ty]);
#pragma unroll(D16/NL)
for (short ii = 0; ii < D16; ii += NL) {
const short i = ii + tx;
v4x4_t mv;
deq_v(pv4 + i/nl_v, i%nl_v, mv);
lo[ii/NL] += mv*ms;
}
}
}
}
// these are needed for reducing the results from the simdgroups (reuse the ss buffer)
if (tiisg == 0) {
ss[0] = (s_t) S;
ss[1] = (s_t) M;
}
}
// simdgroup reduce
// [ 0, 8, 16, 24] -> [ 0]
// [ 1, 9, 17, 25] -> [ 1]
// [ 2, 10, 18, 26] -> [ 2]
// [ 3, 11, 19, 27] -> [ 3]
// [ 4, 12, 20, 28] -> [ 4]
// [ 5, 13, 21, 29] -> [ 5]
// [ 6, 14, 22, 30] -> [ 6]
// [ 7, 15, 23, 31] -> [ 7]
for (short ii = 0; ii < D16; ii += NL) {
lo[ii/NL][0] += simd_shuffle_down(lo[ii/NL][0], 16);
lo[ii/NL][0] += simd_shuffle_down(lo[ii/NL][0], 8);
//lo[ii/NL][0] += simd_shuffle_down(lo[ii/NL][0], 4);
//lo[ii/NL][0] += simd_shuffle_down(lo[ii/NL][0], 2);
//lo[ii/NL][0] += simd_shuffle_down(lo[ii/NL][0], 1);
lo[ii/NL][1] += simd_shuffle_down(lo[ii/NL][1], 16);
lo[ii/NL][1] += simd_shuffle_down(lo[ii/NL][1], 8);
//lo[ii/NL][1] += simd_shuffle_down(lo[ii/NL][1], 4);
//lo[ii/NL][1] += simd_shuffle_down(lo[ii/NL][1], 2);
//lo[ii/NL][1] += simd_shuffle_down(lo[ii/NL][1], 1);
lo[ii/NL][2] += simd_shuffle_down(lo[ii/NL][2], 16);
lo[ii/NL][2] += simd_shuffle_down(lo[ii/NL][2], 8);
//lo[ii/NL][2] += simd_shuffle_down(lo[ii/NL][2], 4);
//lo[ii/NL][2] += simd_shuffle_down(lo[ii/NL][2], 2);
//lo[ii/NL][2] += simd_shuffle_down(lo[ii/NL][2], 1);
lo[ii/NL][3] += simd_shuffle_down(lo[ii/NL][3], 16);
lo[ii/NL][3] += simd_shuffle_down(lo[ii/NL][3], 8);
//lo[ii/NL][3] += simd_shuffle_down(lo[ii/NL][3], 4);
//lo[ii/NL][3] += simd_shuffle_down(lo[ii/NL][3], 2);
//lo[ii/NL][3] += simd_shuffle_down(lo[ii/NL][3], 1);
}
threadgroup_barrier(mem_flags::mem_threadgroup);
// store results to shared memory
for (short i = tiisg; i < D16; i += NL) {
sr4x4[i] = lo[i/NL];
}
threadgroup_barrier(mem_flags::mem_threadgroup);
// parallel reduce
for (short r = nsg/2; r > 0; r >>= 1) {
if (sgitg < r) {
const half S0 = ss[ 0];
const half S1 = ss[r*SH + 0];
const half M0 = ss[ 1];
const half M1 = ss[r*SH + 1];
const half M = max(M0, M1);
const half ms0 = exp(M0 - M);
const half ms1 = exp(M1 - M);
const half S = S0*ms0 + S1*ms1;
if (tiisg == 0) {
ss[0] = S;
ss[1] = M;
}
// O_0 = diag(ms0)*O_0 + diag(ms1)*O_1
for (short i = tiisg; i < D16; i += NW) {
sr4x4[i] = sr4x4[i]*ms0 + sr4x4[i + r*D16]*ms1;
}
}
threadgroup_barrier(mem_flags::mem_threadgroup);
}
device float4x4 * dst44 = (device float4x4 *) dst;
// final rescale with 1/S and store to global memory
if (sgitg == 0) {
const float S = ss[0];
for (short i = tiisg; i < D16; i += NW) {
dst44[((uint64_t)iq3*args.ne2*args.ne1 + iq2 + (uint64_t)iq1*args.ne1)*D16 + i] = (float4x4) sr4x4[i]/S;
}
}
}
// note: I think the s_t can be half instead of float, because the Q*K scaling is done before storing to shared mem
// in the other (non-vec) kernel, we need s_t to also be float because we scale during the soft_max
//
#define FA_TYPES \
half4, half4x4, \
half4x4, \
half4x4, \
float, \
half, half4, half4x4, \
half4x4
typedef decltype(kernel_flash_attn_ext_vec<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 128>) flash_attn_ext_vec_t;
template [[host_name("kernel_flash_attn_ext_vec_f16_h128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 128>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_h128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 128>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_h128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 128>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_h128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 128>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_h128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 128>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_h128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 128>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_h128")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 128>;
template [[host_name("kernel_flash_attn_ext_vec_f16_h256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, half4x4, 1, dequantize_f16, half4x4, 1, dequantize_f16, 256>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_flash_attn_ext_vec_bf16_h256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, bfloat4x4, 1, dequantize_bf16, bfloat4x4, 1, dequantize_bf16, 256>;
#endif
template [[host_name("kernel_flash_attn_ext_vec_q4_0_h256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_0, 2, dequantize_q4_0, block_q4_0, 2, dequantize_q4_0, 256>;
template [[host_name("kernel_flash_attn_ext_vec_q4_1_h256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q4_1, 2, dequantize_q4_1, block_q4_1, 2, dequantize_q4_1, 256>;
template [[host_name("kernel_flash_attn_ext_vec_q5_0_h256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_0, 2, dequantize_q5_0, block_q5_0, 2, dequantize_q5_0, 256>;
template [[host_name("kernel_flash_attn_ext_vec_q5_1_h256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q5_1, 2, dequantize_q5_1, block_q5_1, 2, dequantize_q5_1, 256>;
template [[host_name("kernel_flash_attn_ext_vec_q8_0_h256")]] kernel flash_attn_ext_vec_t kernel_flash_attn_ext_vec<FA_TYPES, block_q8_0, 2, dequantize_q8_0, block_q8_0, 2, dequantize_q8_0, 256>;
#undef FA_TYPES
template<typename T0, typename T1>
kernel void kernel_cpy(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig[2];
const int i02 = tgpig[1];
const int i01 = tgpig[0];
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int64_t i3 = n/(args.ne2*args.ne1*args.ne0);
const int64_t i2 = (n - i3*args.ne2*args.ne1*args.ne0)/(args.ne1*args.ne0);
const int64_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0)/args.ne0;
const int64_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0);
device T1 * dst_data = (device T1 *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int64_t i00 = tpitg.x; i00 < args.ne00; i00 += ntg.x) {
device const T0 * src = (device T0 *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
dst_data[i00] = (T1) src[0];
}
}
typedef decltype(kernel_cpy<float, float>) kernel_cpy_t;
template [[host_name("kernel_cpy_f32_f32")]] kernel kernel_cpy_t kernel_cpy<float, float>;
template [[host_name("kernel_cpy_f32_f16")]] kernel kernel_cpy_t kernel_cpy<float, half>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_cpy_f32_bf16")]] kernel kernel_cpy_t kernel_cpy<float, bfloat>;
#endif
template [[host_name("kernel_cpy_f16_f32")]] kernel kernel_cpy_t kernel_cpy<half, float>;
template [[host_name("kernel_cpy_f16_f16")]] kernel kernel_cpy_t kernel_cpy<half, half>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_cpy_bf16_f32")]] kernel kernel_cpy_t kernel_cpy<bfloat, float>;
template [[host_name("kernel_cpy_bf16_bf16")]] kernel kernel_cpy_t kernel_cpy<bfloat, bfloat>;
#endif
kernel void kernel_cpy_f32_q8_0(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig[2];
const int i02 = tgpig[1];
const int i01 = tgpig[0];
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int64_t i3 = n / (args.ne2*args.ne1*args.ne0);
const int64_t i2 = (n - i3*args.ne2*args.ne1*args.ne0) / (args.ne1*args.ne0);
const int64_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0) / args.ne0;
const int64_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0)/QK8_0;
device block_q8_0 * dst_data = (device block_q8_0 *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int64_t i00 = tpitg.x*QK8_0; i00 < args.ne00; i00 += ntg.x*QK8_0) {
device const float * src = (device float *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
float amax = 0.0f; // absolute max
for (int j = 0; j < QK8_0; j++) {
const float v = src[j];
amax = MAX(amax, fabs(v));
}
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
dst_data[i00/QK8_0].d = d;
for (int j = 0; j < QK8_0; ++j) {
const float x0 = src[j]*id;
dst_data[i00/QK8_0].qs[j] = round(x0);
}
}
}
kernel void kernel_cpy_f32_q4_0(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig[2];
const int i02 = tgpig[1];
const int i01 = tgpig[0];
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int64_t i3 = n / (args.ne2*args.ne1*args.ne0);
const int64_t i2 = (n - i3*args.ne2*args.ne1*args.ne0) / (args.ne1*args.ne0);
const int64_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0) / args.ne0;
const int64_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0)/QK4_0;
device block_q4_0 * dst_data = (device block_q4_0 *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int64_t i00 = tpitg.x*QK4_0; i00 < args.ne00; i00 += ntg.x*QK4_0) {
device const float * src = (device float *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
float amax = 0.0f; // absolute max
float max = 0.0f;
for (int j = 0; j < QK4_0; j++) {
const float v = src[j];
if (amax < fabs(v)) {
amax = fabs(v);
max = v;
}
}
const float d = max / -8;
const float id = d ? 1.0f/d : 0.0f;
dst_data[i00/QK4_0].d = d;
for (int j = 0; j < QK4_0/2; ++j) {
const float x0 = src[0 + j]*id;
const float x1 = src[QK4_0/2 + j]*id;
const uint8_t xi0 = MIN(15, (int8_t)(x0 + 8.5f));
const uint8_t xi1 = MIN(15, (int8_t)(x1 + 8.5f));
dst_data[i00/QK4_0].qs[j] = xi0;
dst_data[i00/QK4_0].qs[j] |= xi1 << 4;
}
}
}
kernel void kernel_cpy_f32_q4_1(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig[2];
const int i02 = tgpig[1];
const int i01 = tgpig[0];
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int64_t i3 = n / (args.ne2*args.ne1*args.ne0);
const int64_t i2 = (n - i3*args.ne2*args.ne1*args.ne0) / (args.ne1*args.ne0);
const int64_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0) / args.ne0;
const int64_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0)/QK4_1;
device block_q4_1 * dst_data = (device block_q4_1 *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int64_t i00 = tpitg.x*QK4_1; i00 < args.ne00; i00 += ntg.x*QK4_1) {
device const float * src = (device float *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
float min = FLT_MAX;
float max = -FLT_MAX;
for (int j = 0; j < QK4_1; j++) {
const float v = src[j];
if (min > v) min = v;
if (max < v) max = v;
}
const float d = (max - min) / ((1 << 4) - 1);
const float id = d ? 1.0f/d : 0.0f;
dst_data[i00/QK4_1].d = d;
dst_data[i00/QK4_1].m = min;
for (int j = 0; j < QK4_1/2; ++j) {
const float x0 = (src[0 + j] - min)*id;
const float x1 = (src[QK4_1/2 + j] - min)*id;
const uint8_t xi0 = MIN(15, (int8_t)(x0 + 0.5f));
const uint8_t xi1 = MIN(15, (int8_t)(x1 + 0.5f));
dst_data[i00/QK4_1].qs[j] = xi0;
dst_data[i00/QK4_1].qs[j] |= xi1 << 4;
}
}
}
kernel void kernel_cpy_f32_q5_0(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig[2];
const int i02 = tgpig[1];
const int i01 = tgpig[0];
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int64_t i3 = n / (args.ne2*args.ne1*args.ne0);
const int64_t i2 = (n - i3*args.ne2*args.ne1*args.ne0) / (args.ne1*args.ne0);
const int64_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0) / args.ne0;
const int64_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0)/QK5_0;
device block_q5_0 * dst_data = (device block_q5_0 *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int64_t i00 = tpitg.x*QK5_0; i00 < args.ne00; i00 += ntg.x*QK5_0) {
device const float * src = (device float *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
float amax = 0.0f; // absolute max
float max = 0.0f;
for (int j = 0; j < QK5_0; j++) {
const float v = src[j];
if (amax < fabs(v)) {
amax = fabs(v);
max = v;
}
}
const float d = max / -16;
const float id = d ? 1.0f/d : 0.0f;
dst_data[i00/QK5_0].d = d;
uint32_t qh = 0;
for (int j = 0; j < QK5_0/2; ++j) {
const float x0 = src[0 + j]*id;
const float x1 = src[QK5_0/2 + j]*id;
const uint8_t xi0 = MIN(31, (int8_t)(x0 + 16.5f));
const uint8_t xi1 = MIN(31, (int8_t)(x1 + 16.5f));
dst_data[i00/QK5_0].qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_0/2);
}
thread const uint8_t * qh8 = (thread const uint8_t *)&qh;
for (int j = 0; j < 4; ++j) {
dst_data[i00/QK5_0].qh[j] = qh8[j];
}
}
}
kernel void kernel_cpy_f32_q5_1(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig[2];
const int i02 = tgpig[1];
const int i01 = tgpig[0];
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int64_t i3 = n / (args.ne2*args.ne1*args.ne0);
const int64_t i2 = (n - i3*args.ne2*args.ne1*args.ne0) / (args.ne1*args.ne0);
const int64_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0) / args.ne0;
const int64_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0)/QK5_1;
device block_q5_1 * dst_data = (device block_q5_1 *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int64_t i00 = tpitg.x*QK5_1; i00 < args.ne00; i00 += ntg.x*QK5_1) {
device const float * src = (device float *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
float max = src[0];
float min = src[0];
for (int j = 1; j < QK5_1; j++) {
const float v = src[j];
min = v < min ? v : min;
max = v > max ? v : max;
}
const float d = (max - min) / 31;
const float id = d ? 1.0f/d : 0.0f;
dst_data[i00/QK5_1].d = d;
dst_data[i00/QK5_1].m = min;
uint32_t qh = 0;
for (int j = 0; j < QK5_1/2; ++j) {
const float x0 = (src[0 + j] - min)*id;
const float x1 = (src[QK5_1/2 + j] - min)*id;
const uint8_t xi0 = (uint8_t)(x0 + 0.5f);
const uint8_t xi1 = (uint8_t)(x1 + 0.5f);
dst_data[i00/QK5_1].qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_1/2);
}
thread const uint8_t * qh8 = (thread const uint8_t *)&qh;
for (int j = 0; j < 4; ++j) {
dst_data[i00/QK5_1].qh[j] = qh8[j];
}
}
}
static inline int best_index_int8(int n, constant float * val, float x) {
if (x <= val[0]) return 0;
if (x >= val[n-1]) return n-1;
int ml = 0, mu = n-1;
while (mu-ml > 1) {
int mav = (ml+mu)/2;
if (x < val[mav]) mu = mav; else ml = mav;
}
return x - val[mu-1] < val[mu] - x ? mu-1 : mu;
}
kernel void kernel_cpy_f32_iq4_nl(
constant ggml_metal_kargs_cpy & args,
device const char * src0,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i03 = tgpig[2];
const int i02 = tgpig[1];
const int i01 = tgpig[0];
const int64_t n = i03*args.ne02*args.ne01*args.ne00 + i02*args.ne01*args.ne00 + i01*args.ne00;
const int64_t i3 = n / (args.ne2*args.ne1*args.ne0);
const int64_t i2 = (n - i3*args.ne2*args.ne1*args.ne0) / (args.ne1*args.ne0);
const int64_t i1 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0) / args.ne0;
const int64_t i0 = (n - i3*args.ne2*args.ne1*args.ne0 - i2*args.ne1*args.ne0 - i1*args.ne0)/QK4_NL;
device block_iq4_nl * dst_data = (device block_iq4_nl *) (dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
for (int64_t i00 = tpitg.x*QK4_NL; i00 < args.ne00; i00 += ntg.x*QK4_NL) {
device const float * src = (device float *)(src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01 + i00*args.nb00);
float amax = 0.0f; // absolute max
float max = 0.0f;
for (int j = 0; j < QK4_0; j++) {
const float v = src[j];
if (amax < fabs(v)) {
amax = fabs(v);
max = v;
}
}
const float d = max / kvalues_iq4nl_f[0];
const float id = d ? 1.0f/d : 0.0f;
float sumqx = 0, sumq2 = 0;
for (int j = 0; j < QK4_NL/2; ++j) {
const float x0 = src[0 + j]*id;
const float x1 = src[QK4_NL/2 + j]*id;
const uint8_t xi0 = best_index_int8(16, kvalues_iq4nl_f, x0);
const uint8_t xi1 = best_index_int8(16, kvalues_iq4nl_f, x1);
dst_data[i00/QK4_NL].qs[j] = xi0 | (xi1 << 4);
const float v0 = kvalues_iq4nl_f[xi0];
const float v1 = kvalues_iq4nl_f[xi1];
const float w0 = src[0 + j]*src[0 + j];
const float w1 = src[QK4_NL/2 + j]*src[QK4_NL/2 + j];
sumqx += w0*v0*src[j] + w1*v1*src[QK4_NL/2 + j];
sumq2 += w0*v0*v0 + w1*v1*v1;
}
dst_data[i00/QK4_NL].d = sumq2 > 0 ? sumqx/sumq2 : d;
}
}
kernel void kernel_concat(
constant ggml_metal_kargs_concat & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = tgpig.x;
int o[4] = {0, 0, 0, 0};
o[args.dim] = args.dim == 0 ? args.ne00 : (args.dim == 1 ? args.ne01 : (args.dim == 2 ? args.ne02 : args.ne03));
device const float * x;
for (int i0 = tpitg.x; i0 < args.ne0; i0 += ntg.x) {
if (i0 < args.ne00 && i1 < args.ne01 && i2 < args.ne02 && i3 < args.ne03) {
x = (device const float *)(src0 + (i3 )*args.nb03 + (i2 )*args.nb02 + (i1 )*args.nb01 + (i0 )*args.nb00);
} else {
x = (device const float *)(src1 + (i3 - o[3])*args.nb13 + (i2 - o[2])*args.nb12 + (i1 - o[1])*args.nb11 + (i0 - o[0])*args.nb10);
}
device float * y = (device float *)(dst + i3*args.nb3 + i2*args.nb2 + i1*args.nb1 + i0*args.nb0);
*y = *x;
}
}
template<typename args_t>
void kernel_mul_mv_q2_K_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_q2_K * x = (device const block_q2_K *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[32];
float sumf[N_DST]={0.f}, all_sum;
const int ix = tiisg/8; // 0...3
const int it = tiisg%8; // 0...7
const int iq = it/4; // 0 or 1
const int ir = it%4; // 0...3
const int is = (8*ir)/16;// 0 or 1
device const float * y4 = y + ix * QK_K + 128 * iq + 8 * ir;
for (int ib = ix; ib < nb; ib += 4) {
float4 sumy = {0.f, 0.f, 0.f, 0.f};
for (int i = 0; i < 8; ++i) {
yl[i+ 0] = y4[i+ 0]; sumy[0] += yl[i+ 0];
yl[i+ 8] = y4[i+32]; sumy[1] += yl[i+ 8];
yl[i+16] = y4[i+64]; sumy[2] += yl[i+16];
yl[i+24] = y4[i+96]; sumy[3] += yl[i+24];
}
device const uint8_t * sc = (device const uint8_t *)x[ib].scales + 8*iq + is;
device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 16 * iq + 4 * ir;
device const half * dh = &x[ib].d;
for (int row = 0; row < N_DST; row++) {
float4 acc1 = {0.f, 0.f, 0.f, 0.f};
float4 acc2 = {0.f, 0.f, 0.f, 0.f};
for (int i = 0; i < 8; i += 2) {
acc1[0] += yl[i+ 0] * (qs[i/2] & 0x0003);
acc2[0] += yl[i+ 1] * (qs[i/2] & 0x0300);
acc1[1] += yl[i+ 8] * (qs[i/2] & 0x000c);
acc2[1] += yl[i+ 9] * (qs[i/2] & 0x0c00);
acc1[2] += yl[i+16] * (qs[i/2] & 0x0030);
acc2[2] += yl[i+17] * (qs[i/2] & 0x3000);
acc1[3] += yl[i+24] * (qs[i/2] & 0x00c0);
acc2[3] += yl[i+25] * (qs[i/2] & 0xc000);
}
float dall = dh[0];
float dmin = dh[1] * 1.f/16.f;
sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc2[0]) * (sc[0] & 0xF) * 1.f/ 1.f +
(acc1[1] + 1.f/256.f * acc2[1]) * (sc[2] & 0xF) * 1.f/ 4.f +
(acc1[2] + 1.f/256.f * acc2[2]) * (sc[4] & 0xF) * 1.f/16.f +
(acc1[3] + 1.f/256.f * acc2[3]) * (sc[6] & 0xF) * 1.f/64.f) -
dmin * (sumy[0] * (sc[0] & 0xF0) + sumy[1] * (sc[2] & 0xF0) + sumy[2] * (sc[4] & 0xF0) + sumy[3] * (sc[6] & 0xF0));
qs += args.nb01/2;
sc += args.nb01;
dh += args.nb01/2;
}
y4 += 4 * QK_K;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum;
}
}
}
[[host_name("kernel_mul_mv_q2_K_f32")]]
kernel void kernel_mul_mv_q2_K_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_q2_K_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
template<typename args_t>
void kernel_mul_mv_q3_K_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * 2;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_q3_K * x = (device const block_q3_K *) (src0 + offset0);
device const float * yy = (device const float *) (src1 + offset1);
float yl[32];
//const uint16_t kmask1 = 0x3030;
//const uint16_t kmask2 = 0x0f0f;
const int tid = tiisg/4;
const int ix = tiisg%4;
const int ip = tid/4; // 0 or 1
const int il = 2*((tid%4)/2); // 0 or 2
const int ir = tid%2;
const int n = 8;
const int l0 = n*ir;
// One would think that the Metal compiler would figure out that ip and il can only have
// 4 possible states, and optimize accordingly. Well, no. It needs help, and we do it
// with these two tales.
//
// Possible masks for the high bit
const ushort4 mm[4] = {{0x0001, 0x0100, 0x0002, 0x0200}, // ip = 0, il = 0
{0x0004, 0x0400, 0x0008, 0x0800}, // ip = 0, il = 2
{0x0010, 0x1000, 0x0020, 0x2000}, // ip = 1, il = 0
{0x0040, 0x4000, 0x0080, 0x8000}}; // ip = 1, il = 2
// Possible masks for the low 2 bits
const int4 qm[2] = {{0x0003, 0x0300, 0x000c, 0x0c00}, {0x0030, 0x3000, 0x00c0, 0xc000}};
const ushort4 hm = mm[2*ip + il/2];
const short shift = 2*il;
const float v1 = il == 0 ? 4.f : 64.f;
const float v2 = 4.f * v1;
const uint16_t s_shift1 = 4*ip;
const uint16_t s_shift2 = s_shift1 + il;
const int q_offset = 32*ip + l0;
const int y_offset = 128*ip + 32*il + l0;
device const float * y1 = yy + ix*QK_K + y_offset;
uint32_t scales32, aux32;
thread uint16_t * scales16 = (thread uint16_t *)&scales32;
thread const int8_t * scales = (thread const int8_t *)&scales32;
float sumf1[2] = {0.f};
float sumf2[2] = {0.f};
for (int i = ix; i < nb; i += 4) {
for (int l = 0; l < 8; ++l) {
yl[l+ 0] = y1[l+ 0];
yl[l+ 8] = y1[l+16];
yl[l+16] = y1[l+32];
yl[l+24] = y1[l+48];
}
device const uint16_t * q = (device const uint16_t *)(x[i].qs + q_offset);
device const uint16_t * h = (device const uint16_t *)(x[i].hmask + l0);
device const uint16_t * a = (device const uint16_t *)(x[i].scales);
device const half * dh = &x[i].d;
for (int row = 0; row < 2; ++row) {
const float d_all = (float)dh[0];
scales16[0] = a[4];
scales16[1] = a[5];
aux32 = ((scales32 >> s_shift2) << 4) & 0x30303030;
scales16[0] = a[il+0];
scales16[1] = a[il+1];
scales32 = ((scales32 >> s_shift1) & 0x0f0f0f0f) | aux32;
float s1 = 0, s2 = 0, s3 = 0, s4 = 0, s5 = 0, s6 = 0;
for (int l = 0; l < n; l += 2) {
const int32_t qs = q[l/2];
s1 += yl[l+0] * (qs & qm[il/2][0]);
s2 += yl[l+1] * (qs & qm[il/2][1]);
s3 += ((h[l/2] & hm[0]) ? 0.f : yl[l+0]) + ((h[l/2] & hm[1]) ? 0.f : yl[l+1]);
s4 += yl[l+16] * (qs & qm[il/2][2]);
s5 += yl[l+17] * (qs & qm[il/2][3]);
s6 += ((h[l/2] & hm[2]) ? 0.f : yl[l+16]) + ((h[l/2] & hm[3]) ? 0.f : yl[l+17]);
}
float d1 = d_all * (s1 + 1.f/256.f * s2 - s3*v1);
float d2 = d_all * (s4 + 1.f/256.f * s5 - s6*v2);
sumf1[row] += d1 * (scales[0] - 32);
sumf2[row] += d2 * (scales[2] - 32);
s1 = s2 = s3 = s4 = s5 = s6 = 0;
for (int l = 0; l < n; l += 2) {
const int32_t qs = q[l/2+8];
s1 += yl[l+8] * (qs & qm[il/2][0]);
s2 += yl[l+9] * (qs & qm[il/2][1]);
s3 += ((h[l/2+8] & hm[0]) ? 0.f : yl[l+8]) + ((h[l/2+8] & hm[1]) ? 0.f : yl[l+9]);
s4 += yl[l+24] * (qs & qm[il/2][2]);
s5 += yl[l+25] * (qs & qm[il/2][3]);
s6 += ((h[l/2+8] & hm[2]) ? 0.f : yl[l+24]) + ((h[l/2+8] & hm[3]) ? 0.f : yl[l+25]);
}
d1 = d_all * (s1 + 1.f/256.f * s2 - s3*v1);
d2 = d_all * (s4 + 1.f/256.f * s5 - s6*v2);
sumf1[row] += d1 * (scales[1] - 32);
sumf2[row] += d2 * (scales[3] - 32);
q += args.nb01/2;
h += args.nb01/2;
a += args.nb01/2;
dh += args.nb01/2;
}
y1 += 4 * QK_K;
}
for (int row = 0; row < 2; ++row) {
const float sumf = (sumf1[row] + 0.25f * sumf2[row]) / (1 << shift);
sumf1[row] = simd_sum(sumf);
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
if (tiisg == 0) {
for (int row = 0; row < 2; ++row) {
dst_f32[first_row + row] = sumf1[row];
}
}
}
[[host_name("kernel_mul_mv_q3_K_f32")]]
kernel void kernel_mul_mv_q3_K_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_q3_K_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
template<typename args_t>
void kernel_mul_mv_q4_K_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
const int ix = tiisg/8; // 0...3
const int it = tiisg%8; // 0...7
const int iq = it/4; // 0 or 1
const int ir = it%4; // 0...3
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
//const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const int first_row = r0 * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_q4_K * x = (device const block_q4_K *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[16];
float yh[16];
float sumf[N_DST]={0.f}, all_sum;
device const float * y4 = y + ix * QK_K + 64 * iq + 8 * ir;
uint16_t sc16[4];
thread const uint8_t * sc8 = (thread const uint8_t *)sc16;
for (int ib = ix; ib < nb; ib += 4) {
float4 sumy = {0.f, 0.f, 0.f, 0.f};
for (int i = 0; i < 8; ++i) {
yl[i+0] = y4[i+ 0]; sumy[0] += yl[i+0];
yl[i+8] = y4[i+ 32]; sumy[1] += yl[i+8];
yh[i+0] = y4[i+128]; sumy[2] += yh[i+0];
yh[i+8] = y4[i+160]; sumy[3] += yh[i+8];
}
device const uint16_t * sc = (device const uint16_t *)x[ib].scales + iq;
device const uint16_t * q1 = (device const uint16_t *)x[ib].qs + 16 * iq + 4 * ir;
device const half * dh = &x[ib].d;
for (int row = 0; row < N_DST; row++) {
sc16[0] = sc[0] & kmask1;
sc16[1] = sc[2] & kmask1;
sc16[2] = ((sc[4] >> 0) & kmask2) | ((sc[0] & kmask3) >> 2);
sc16[3] = ((sc[4] >> 4) & kmask2) | ((sc[2] & kmask3) >> 2);
device const uint16_t * q2 = q1 + 32;
float4 acc1 = {0.f, 0.f, 0.f, 0.f};
float4 acc2 = {0.f, 0.f, 0.f, 0.f};
for (int i = 0; i < 8; i += 2) {
acc1[0] += yl[i+0] * (q1[i/2] & 0x000F);
acc1[1] += yl[i+1] * (q1[i/2] & 0x0F00);
acc1[2] += yl[i+8] * (q1[i/2] & 0x00F0);
acc1[3] += yl[i+9] * (q1[i/2] & 0xF000);
acc2[0] += yh[i+0] * (q2[i/2] & 0x000F);
acc2[1] += yh[i+1] * (q2[i/2] & 0x0F00);
acc2[2] += yh[i+8] * (q2[i/2] & 0x00F0);
acc2[3] += yh[i+9] * (q2[i/2] & 0xF000);
}
float dall = dh[0];
float dmin = dh[1];
sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc1[1]) * sc8[0] +
(acc1[2] + 1.f/256.f * acc1[3]) * sc8[1] * 1.f/16.f +
(acc2[0] + 1.f/256.f * acc2[1]) * sc8[4] +
(acc2[2] + 1.f/256.f * acc2[3]) * sc8[5] * 1.f/16.f) -
dmin * (sumy[0] * sc8[2] + sumy[1] * sc8[3] + sumy[2] * sc8[6] + sumy[3] * sc8[7]);
q1 += args.nb01/2;
sc += args.nb01/2;
dh += args.nb01/2;
}
y4 += 4 * QK_K;
}
device float * dst_f32 = (device float *) dst + (int64_t)im*args.ne0*args.ne1 + (int64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum;
}
}
}
[[host_name("kernel_mul_mv_q4_K_f32")]]
kernel void kernel_mul_mv_q4_K_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_q4_K_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
template<typename args_t>
void kernel_mul_mv_q5_K_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * 2;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_q5_K * x = (device const block_q5_K *) (src0 + offset0);
device const float * yy = (device const float *) (src1 + offset1);
float sumf[2]={0.f};
float yl[16], yh[16];
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
const int tid = tiisg/4;
const int ix = tiisg%4;
const int iq = tid/4;
const int ir = tid%4;
const int n = 8;
const int l0 = n*ir;
const int q_offset = 32*iq + l0;
const int y_offset = 64*iq + l0;
const uint8_t hm1 = 1u << (2*iq);
const uint8_t hm2 = hm1 << 1;
const uint8_t hm3 = hm1 << 4;
const uint8_t hm4 = hm2 << 4;
uint16_t sc16[4];
thread const uint8_t * sc8 = (thread const uint8_t *)sc16;
device const float * y1 = yy + ix*QK_K + y_offset;
for (int i = ix; i < nb; i += 4) {
device const uint8_t * q1 = x[i].qs + q_offset;
device const uint8_t * qh = x[i].qh + l0;
device const half * dh = &x[i].d;
device const uint16_t * a = (device const uint16_t *)x[i].scales + iq;
device const float * y2 = y1 + 128;
float4 sumy = {0.f, 0.f, 0.f, 0.f};
for (int l = 0; l < 8; ++l) {
yl[l+0] = y1[l+ 0]; sumy[0] += yl[l+0];
yl[l+8] = y1[l+32]; sumy[1] += yl[l+8];
yh[l+0] = y2[l+ 0]; sumy[2] += yh[l+0];
yh[l+8] = y2[l+32]; sumy[3] += yh[l+8];
}
for (int row = 0; row < 2; ++row) {
device const uint8_t * q2 = q1 + 64;
sc16[0] = a[0] & kmask1;
sc16[1] = a[2] & kmask1;
sc16[2] = ((a[4] >> 0) & kmask2) | ((a[0] & kmask3) >> 2);
sc16[3] = ((a[4] >> 4) & kmask2) | ((a[2] & kmask3) >> 2);
float4 acc1 = {0.f};
float4 acc2 = {0.f};
for (int l = 0; l < n; ++l) {
uint8_t h = qh[l];
acc1[0] += yl[l+0] * (q1[l] & 0x0F);
acc1[1] += yl[l+8] * (q1[l] & 0xF0);
acc1[2] += yh[l+0] * (q2[l] & 0x0F);
acc1[3] += yh[l+8] * (q2[l] & 0xF0);
acc2[0] += h & hm1 ? yl[l+0] : 0.f;
acc2[1] += h & hm2 ? yl[l+8] : 0.f;
acc2[2] += h & hm3 ? yh[l+0] : 0.f;
acc2[3] += h & hm4 ? yh[l+8] : 0.f;
}
const float dall = dh[0];
const float dmin = dh[1];
sumf[row] += dall * (sc8[0] * (acc1[0] + 16.f*acc2[0]) +
sc8[1] * (acc1[1]/16.f + 16.f*acc2[1]) +
sc8[4] * (acc1[2] + 16.f*acc2[2]) +
sc8[5] * (acc1[3]/16.f + 16.f*acc2[3])) -
dmin * (sumy[0] * sc8[2] + sumy[1] * sc8[3] + sumy[2] * sc8[6] + sumy[3] * sc8[7]);
q1 += args.nb01;
qh += args.nb01;
dh += args.nb01/2;
a += args.nb01/2;
}
y1 += 4 * QK_K;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < 2; ++row) {
const float tot = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = tot;
}
}
}
[[host_name("kernel_mul_mv_q5_K_f32")]]
kernel void kernel_mul_mv_q5_K_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_q5_K_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
template <typename args_t>
void kernel_mul_mv_q6_K_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const uint8_t kmask1 = 0x03;
const uint8_t kmask2 = 0x0C;
const uint8_t kmask3 = 0x30;
const uint8_t kmask4 = 0xC0;
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int row = 2*r0 + sgitg;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_q6_K * x = (device const block_q6_K *) (src0 + offset0);
device const float * yy = (device const float *) (src1 + offset1);
float sumf = 0;
const int tid = tiisg/2;
const int ix = tiisg%2;
const int ip = tid/8; // 0 or 1
const int il = tid%8;
const int n = 4;
const int l0 = n*il;
const int is = 8*ip + l0/16;
const int y_offset = 128*ip + l0;
const int q_offset_l = 64*ip + l0;
const int q_offset_h = 32*ip + l0;
for (int i = ix; i < nb; i += 2) {
device const uint8_t * q1 = x[i].ql + q_offset_l;
device const uint8_t * q2 = q1 + 32;
device const uint8_t * qh = x[i].qh + q_offset_h;
device const int8_t * sc = x[i].scales + is;
device const float * y = yy + i * QK_K + y_offset;
const float dall = x[i].d;
float4 sums = {0.f, 0.f, 0.f, 0.f};
for (int l = 0; l < n; ++l) {
sums[0] += y[l+ 0] * ((int8_t)((q1[l] & 0xF) | ((qh[l] & kmask1) << 4)) - 32);
sums[1] += y[l+32] * ((int8_t)((q2[l] & 0xF) | ((qh[l] & kmask2) << 2)) - 32);
sums[2] += y[l+64] * ((int8_t)((q1[l] >> 4) | ((qh[l] & kmask3) << 0)) - 32);
sums[3] += y[l+96] * ((int8_t)((q2[l] >> 4) | ((qh[l] & kmask4) >> 2)) - 32);
}
sumf += dall * (sums[0] * sc[0] + sums[1] * sc[2] + sums[2] * sc[4] + sums[3] * sc[6]);
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
const float tot = simd_sum(sumf);
if (tiisg == 0) {
dst_f32[row] = tot;
}
}
[[host_name("kernel_mul_mv_q6_K_f32")]]
kernel void kernel_mul_mv_q6_K_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_q6_K_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
// ======================= "True" 2-bit
template<typename args_t>
void kernel_mul_mv_iq2_xxs_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq2_xxs * x = (device const block_iq2_xxs *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[32];
float sumf[N_DST]={0.f}, all_sum;
const int nb32 = nb * (QK_K / 32);
threadgroup uint64_t * svalues = (threadgroup uint64_t *)(shmem);
threadgroup uint8_t * ssigns = (threadgroup uint8_t *)(svalues + 256);
{
int nval = 4;
int pos = (32*sgitg + tiisg)*nval;
for (int i = 0; i < nval; ++i) svalues[pos + i] = iq2xxs_grid[pos + i];
nval = 2;
pos = (32*sgitg + tiisg)*nval;
for (int i = 0; i < nval; ++i) ssigns[pos+i] = ksigns_iq2xs[pos+i];
threadgroup_barrier(mem_flags::mem_threadgroup);
}
const int ix = tiisg;
device const float * y4 = y + 32 * ix;
for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
for (int i = 0; i < 32; ++i) {
yl[i] = y4[i];
}
const int ibl = ib32 / (QK_K / 32);
const int ib = ib32 % (QK_K / 32);
device const block_iq2_xxs * xr = x + ibl;
device const uint16_t * q2 = xr->qs + 4 * ib;
device const half * dh = &xr->d;
for (int row = 0; row < N_DST; row++) {
const float db = dh[0];
device const uint8_t * aux8 = (device const uint8_t *)q2;
const uint32_t aux32 = q2[2] | (q2[3] << 16);
const float d = db * (0.5f + (aux32 >> 28));
float sum = 0;
for (int l = 0; l < 4; ++l) {
const threadgroup uint8_t * grid = (const threadgroup uint8_t *)(svalues + aux8[l]);
const uint8_t signs = ssigns[(aux32 >> 7*l) & 127];
for (int j = 0; j < 8; ++j) {
sum += yl[8*l + j] * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
}
}
sumf[row] += d * sum;
dh += args.nb01/2;
q2 += args.nb01/2;
}
y4 += 32 * 32;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum * 0.25f;
}
}
}
[[host_name("kernel_mul_mv_iq2_xxs_f32")]]
kernel void kernel_mul_mv_iq2_xxs_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq2_xxs_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
}
template<typename args_t>
void kernel_mul_mv_iq2_xs_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq2_xs * x = (device const block_iq2_xs *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[32];
float sumf[N_DST]={0.f}, all_sum;
const int nb32 = nb * (QK_K / 32);
threadgroup uint64_t * svalues = (threadgroup uint64_t *)(shmem);
threadgroup uint8_t * ssigns = (threadgroup uint8_t *)(svalues + 512);
{
int nval = 8;
int pos = (32*sgitg + tiisg)*nval;
for (int i = 0; i < nval; ++i) svalues[pos + i] = iq2xs_grid[pos + i];
nval = 2;
pos = (32*sgitg + tiisg)*nval;
for (int i = 0; i < nval; ++i) ssigns[pos+i] = ksigns_iq2xs[pos+i];
threadgroup_barrier(mem_flags::mem_threadgroup);
}
const int ix = tiisg;
device const float * y4 = y + 32 * ix;
for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
for (int i = 0; i < 32; ++i) {
yl[i] = y4[i];
}
const int ibl = ib32 / (QK_K / 32);
const int ib = ib32 % (QK_K / 32);
device const block_iq2_xs * xr = x + ibl;
device const uint16_t * q2 = xr->qs + 4 * ib;
device const uint8_t * sc = xr->scales + ib;
device const half * dh = &xr->d;
for (int row = 0; row < N_DST; row++) {
const float db = dh[0];
const uint8_t ls1 = sc[0] & 0xf;
const uint8_t ls2 = sc[0] >> 4;
const float d1 = db * (0.5f + ls1);
const float d2 = db * (0.5f + ls2);
float sum1 = 0, sum2 = 0;
for (int l = 0; l < 2; ++l) {
const threadgroup uint8_t * grid = (const threadgroup uint8_t *)(svalues + (q2[l] & 511));
const uint8_t signs = ssigns[(q2[l] >> 9)];
for (int j = 0; j < 8; ++j) {
sum1 += yl[8*l + j] * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
}
}
for (int l = 2; l < 4; ++l) {
const threadgroup uint8_t * grid = (const threadgroup uint8_t *)(svalues + (q2[l] & 511));
const uint8_t signs = ssigns[(q2[l] >> 9)];
for (int j = 0; j < 8; ++j) {
sum2 += yl[8*l + j] * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f);
}
}
sumf[row] += d1 * sum1 + d2 * sum2;
dh += args.nb01/2;
q2 += args.nb01/2;
sc += args.nb01;
}
y4 += 32 * 32;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum * 0.25f;
}
}
}
[[host_name("kernel_mul_mv_iq2_xs_f32")]]
kernel void kernel_mul_mv_iq2_xs_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq2_xs_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
}
template <typename args_t>
void kernel_mul_mv_iq3_xxs_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq3_xxs * x = (device const block_iq3_xxs *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[32];
float sumf[N_DST]={0.f}, all_sum;
const int nb32 = nb * (QK_K / 32);
threadgroup uint32_t * svalues = (threadgroup uint32_t *)(shmem);
threadgroup uint8_t * ssigns = (threadgroup uint8_t *)(svalues + 256);
{
int nval = 4;
int pos = (32*sgitg + tiisg)*nval;
for (int i = 0; i < nval; ++i) svalues[pos + i] = iq3xxs_grid[pos + i];
nval = 2;
pos = (32*sgitg + tiisg)*nval;
for (int i = 0; i < nval; ++i) ssigns[pos+i] = ksigns_iq2xs[pos+i];
threadgroup_barrier(mem_flags::mem_threadgroup);
}
const int ix = tiisg;
device const float * y4 = y + 32 * ix;
for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
for (int i = 0; i < 32; ++i) {
yl[i] = y4[i];
}
const int ibl = ib32 / (QK_K / 32);
const int ib = ib32 % (QK_K / 32);
device const block_iq3_xxs * xr = x + ibl;
device const uint8_t * q3 = xr->qs + 8 * ib;
device const uint16_t * gas = (device const uint16_t *)(xr->qs + QK_K/4) + 2 * ib;
device const half * dh = &xr->d;
for (int row = 0; row < N_DST; row++) {
const float db = dh[0];
const uint32_t aux32 = gas[0] | (gas[1] << 16);
const float d = db * (0.5f + (aux32 >> 28));
float2 sum = {0};
for (int l = 0; l < 4; ++l) {
const threadgroup uint8_t * grid1 = (const threadgroup uint8_t *)(svalues + q3[2*l+0]);
const threadgroup uint8_t * grid2 = (const threadgroup uint8_t *)(svalues + q3[2*l+1]);
const uint8_t signs = ssigns[(aux32 >> 7*l) & 127];
for (int j = 0; j < 4; ++j) {
sum[0] += yl[8*l + j + 0] * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f);
sum[1] += yl[8*l + j + 4] * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f);
}
}
sumf[row] += d * (sum[0] + sum[1]);
dh += args.nb01/2;
q3 += args.nb01;
gas += args.nb01/2;
}
y4 += 32 * 32;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum * 0.5f;
}
}
}
[[host_name("kernel_mul_mv_iq3_xxs_f32")]]
kernel void kernel_mul_mv_iq3_xxs_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq3_xxs_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
}
template<typename args_t>
void kernel_mul_mv_iq3_s_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq3_s * x = (device const block_iq3_s *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[32];
float sumf[N_DST]={0.f}, all_sum;
const int nb32 = nb * (QK_K / 32);
threadgroup uint32_t * svalues = (threadgroup uint32_t *) shmem;
{
int nval = 8;
int pos = (32*sgitg + tiisg)*nval;
for (int i = 0; i < nval; ++i) svalues[pos + i] = iq3s_grid[pos + i];
threadgroup_barrier(mem_flags::mem_threadgroup);
}
const int ix = tiisg;
device const float * y4 = y + 32 * ix;
for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
for (int i = 0; i < 32; ++i) {
yl[i] = y4[i];
}
const int ibl = ib32 / (QK_K / 32);
const int ib = ib32 % (QK_K / 32);
device const block_iq3_s * xr = x + ibl;
device const uint8_t * qs = xr->qs + 8 * ib;
device const uint8_t * qh = xr->qh + ib;
device const uint8_t * sc = xr->scales + (ib/2);
device const uint8_t * signs = xr->signs + 4 * ib;
device const half * dh = &xr->d;
for (int row = 0; row < N_DST; row++) {
const float db = dh[0];
const float d = db * (1 + 2*((sc[0] >> 4*(ib%2)) & 0xf));
float2 sum = {0};
for (int l = 0; l < 4; ++l) {
const threadgroup uint32_t * table1 = qh[0] & kmask_iq2xs[2*l+0] ? svalues + 256 : svalues;
const threadgroup uint32_t * table2 = qh[0] & kmask_iq2xs[2*l+1] ? svalues + 256 : svalues;
const threadgroup uint8_t * grid1 = (const threadgroup uint8_t *)(table1 + qs[2*l+0]);
const threadgroup uint8_t * grid2 = (const threadgroup uint8_t *)(table2 + qs[2*l+1]);
for (int j = 0; j < 4; ++j) {
sum[0] += yl[8*l + j + 0] * grid1[j] * select(1, -1, signs[l] & kmask_iq2xs[j+0]);
sum[1] += yl[8*l + j + 4] * grid2[j] * select(1, -1, signs[l] & kmask_iq2xs[j+4]);
}
}
sumf[row] += d * (sum[0] + sum[1]);
dh += args.nb01/2;
qs += args.nb01;
qh += args.nb01;
sc += args.nb01;
signs += args.nb01;
}
y4 += 32 * 32;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum;
}
}
}
[[host_name("kernel_mul_mv_iq3_s_f32")]]
kernel void kernel_mul_mv_iq3_s_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq3_s_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
}
template <typename args_t>
void kernel_mul_mv_iq2_s_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq2_s * x = (device const block_iq2_s *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[32];
float sumf[N_DST]={0.f}, all_sum;
const int nb32 = nb * (QK_K / 32);
//threadgroup uint64_t * svalues = (threadgroup uint64_t *) shmem;
//{
// int nval = 32;
// int pos = (32*sgitg + tiisg)*nval;
// for (int i = 0; i < nval; ++i) svalues[pos + i] = iq2s_grid[pos + i];
// threadgroup_barrier(mem_flags::mem_threadgroup);
//}
const int ix = tiisg;
device const float * y4 = y + 32 * ix;
for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
for (int i = 0; i < 32; ++i) {
yl[i] = y4[i];
}
const int ibl = ib32 / (QK_K / 32);
const int ib = ib32 % (QK_K / 32);
device const block_iq2_s * xr = x + ibl;
device const uint8_t * qs = xr->qs + 4 * ib;
device const uint8_t * qh = xr->qh + ib;
device const uint8_t * sc = xr->scales + ib;
device const uint8_t * signs = qs + QK_K/8;
device const half * dh = &xr->d;
for (int row = 0; row < N_DST; row++) {
const float db = dh[0];
const float d1 = db * (0.5f + (sc[0] & 0xf));
const float d2 = db * (0.5f + (sc[0] >> 4));
float2 sum = {0};
for (int l = 0; l < 2; ++l) {
//const threadgroup uint8_t * grid1 = (const threadgroup uint8_t *)(svalues + (qs[l+0] | ((qh[0] << (8-2*l)) & 0x300)));
//const threadgroup uint8_t * grid2 = (const threadgroup uint8_t *)(svalues + (qs[l+2] | ((qh[0] << (4-2*l)) & 0x300)));
constant uint8_t * grid1 = (constant uint8_t *)(iq2s_grid + (qs[l+0] | ((qh[0] << (8-2*l)) & 0x300)));
constant uint8_t * grid2 = (constant uint8_t *)(iq2s_grid + (qs[l+2] | ((qh[0] << (4-2*l)) & 0x300)));
for (int j = 0; j < 8; ++j) {
sum[0] += yl[8*l + j + 0] * grid1[j] * select(1, -1, signs[l+0] & kmask_iq2xs[j]);
sum[1] += yl[8*l + j + 16] * grid2[j] * select(1, -1, signs[l+2] & kmask_iq2xs[j]);
}
}
sumf[row] += d1 * sum[0] + d2 * sum[1];
dh += args.nb01/2;
qs += args.nb01;
qh += args.nb01;
sc += args.nb01;
signs += args.nb01;
}
y4 += 32 * 32;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum * 0.25f;
}
}
}
[[host_name("kernel_mul_mv_iq2_s_f32")]]
kernel void kernel_mul_mv_iq2_s_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq2_s_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
}
template<typename args_t>
void kernel_mul_mv_iq1_s_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq1_s * x = (device const block_iq1_s *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[32];
float sumf[N_DST]={0.f}, all_sum;
const int nb32 = nb * (QK_K / 32);
const int ix = tiisg;
device const float * y4 = y + 32 * ix;
for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
float sumy = 0;
for (int i = 0; i < 32; ++i) {
yl[i] = y4[i];
sumy += yl[i];
}
const int ibl = ib32 / (QK_K / 32);
const int ib = ib32 % (QK_K / 32);
device const block_iq1_s * xr = x + ibl;
device const uint8_t * qs = xr->qs + 4 * ib;
device const uint16_t * qh = xr->qh + ib;
device const half * dh = &xr->d;
for (int row = 0; row < N_DST; row++) {
constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((qh[0] << 8) & 0x700)));
constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((qh[0] << 5) & 0x700)));
constant uint8_t * grid3 = (constant uint8_t *)(iq1s_grid_gpu + (qs[2] | ((qh[0] << 2) & 0x700)));
constant uint8_t * grid4 = (constant uint8_t *)(iq1s_grid_gpu + (qs[3] | ((qh[0] >> 1) & 0x700)));
float sum = 0;
for (int j = 0; j < 4; ++j) {
sum += yl[j+ 0] * (grid1[j] & 0xf) + yl[j+ 4] * (grid1[j] >> 4)
+ yl[j+ 8] * (grid2[j] & 0xf) + yl[j+12] * (grid2[j] >> 4)
+ yl[j+16] * (grid3[j] & 0xf) + yl[j+20] * (grid3[j] >> 4)
+ yl[j+24] * (grid4[j] & 0xf) + yl[j+28] * (grid4[j] >> 4);
}
sumf[row] += (float)dh[0] * (sum + sumy * (qh[0] & 0x8000 ? -1 - IQ1S_DELTA : -1 + IQ1S_DELTA)) * (2*((qh[0] >> 12) & 7) + 1);
dh += args.nb01/2;
qs += args.nb01;
qh += args.nb01/2;
}
y4 += 32 * 32;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum;
}
}
}
template <typename args_t>
void kernel_mul_mv_iq1_m_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq1_m * x = (device const block_iq1_m *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
float yl[32];
float sumf[N_DST]={0.f}, all_sum;
const int nb32 = nb * (QK_K / 32);
const int ix = tiisg;
device const float * y4 = y + 32 * ix;
iq1m_scale_t scale;
for (int ib32 = ix; ib32 < nb32; ib32 += 32) {
float4 sumy = {0.f};
for (int i = 0; i < 8; ++i) {
yl[i+ 0] = y4[i+ 0]; sumy[0] += yl[i+ 0];
yl[i+ 8] = y4[i+ 8]; sumy[1] += yl[i+ 8];
yl[i+16] = y4[i+16]; sumy[2] += yl[i+16];
yl[i+24] = y4[i+24]; sumy[3] += yl[i+24];
}
const int ibl = ib32 / (QK_K / 32);
const int ib = ib32 % (QK_K / 32);
device const block_iq1_m * xr = x + ibl;
device const uint8_t * qs = xr->qs + 4 * ib;
device const uint8_t * qh = xr->qh + 2 * ib;
device const uint16_t * sc = (device const uint16_t *)xr->scales;
for (int row = 0; row < N_DST; row++) {
scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000);
constant uint8_t * grid1 = (constant uint8_t *)(iq1s_grid_gpu + (qs[0] | ((qh[0] << 8) & 0x700)));
constant uint8_t * grid2 = (constant uint8_t *)(iq1s_grid_gpu + (qs[1] | ((qh[0] << 4) & 0x700)));
constant uint8_t * grid3 = (constant uint8_t *)(iq1s_grid_gpu + (qs[2] | ((qh[1] << 8) & 0x700)));
constant uint8_t * grid4 = (constant uint8_t *)(iq1s_grid_gpu + (qs[3] | ((qh[1] << 4) & 0x700)));
float2 sum = {0.f};
for (int j = 0; j < 4; ++j) {
sum[0] += yl[j+ 0] * (grid1[j] & 0xf) + yl[j+ 4] * (grid1[j] >> 4)
+ yl[j+ 8] * (grid2[j] & 0xf) + yl[j+12] * (grid2[j] >> 4);
sum[1] += yl[j+16] * (grid3[j] & 0xf) + yl[j+20] * (grid3[j] >> 4)
+ yl[j+24] * (grid4[j] & 0xf) + yl[j+28] * (grid4[j] >> 4);
}
const float delta1 = sumy[0] * (qh[0] & 0x08 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA) + sumy[1] * (qh[0] & 0x80 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
const float delta2 = sumy[2] * (qh[1] & 0x08 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA) + sumy[3] * (qh[1] & 0x80 ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA);
sumf[row] += (float)scale.f16 * ((sum[0] + delta1) * (2*((sc[ib/2] >> (6*(ib%2)+0)) & 7) + 1) +
(sum[1] + delta2) * (2*((sc[ib/2] >> (6*(ib%2)+3)) & 7) + 1));
sc += args.nb01/2;
qs += args.nb01;
qh += args.nb01;
}
y4 += 32 * 32;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < N_DST; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum;
}
}
}
template<typename args_t>
void kernel_mul_mv_iq4_nl_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
threadgroup float * shmem_f32 = (threadgroup float *) shmem;
const int nb = args.ne00/QK4_NL;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * 2 + sgitg) * 2;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq4_nl * x = (device const block_iq4_nl *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
const int ix = tiisg/2; // 0...15
const int it = tiisg%2; // 0 or 1
shmem_f32[tiisg] = kvalues_iq4nl_f[tiisg%16];
threadgroup_barrier(mem_flags::mem_threadgroup);
float4 yl[4];
float sumf[2]={0.f}, all_sum;
device const float * yb = y + ix * QK4_NL + it * 8;
uint32_t aux32[2];
thread const uint8_t * q8 = (thread const uint8_t *)aux32;
float4 qf1, qf2;
for (int ib = ix; ib < nb; ib += 16) {
device const float4 * y4 = (device const float4 *)yb;
yl[0] = y4[0]; yl[1] = y4[4]; yl[2] = y4[1]; yl[3] = y4[5];
for (int row = 0; row < 2 && first_row + row < args.ne01; ++row) {
device const block_iq4_nl & xb = x[row*nb + ib];
device const uint16_t * q4 = (device const uint16_t *)(xb.qs + 8*it);
float4 acc1 = {0.f}, acc2 = {0.f};
aux32[0] = q4[0] | (q4[1] << 16);
aux32[1] = (aux32[0] >> 4) & 0x0f0f0f0f;
aux32[0] &= 0x0f0f0f0f;
qf1 = {shmem_f32[q8[0]], shmem_f32[q8[1]], shmem_f32[q8[2]], shmem_f32[q8[3]]};
qf2 = {shmem_f32[q8[4]], shmem_f32[q8[5]], shmem_f32[q8[6]], shmem_f32[q8[7]]};
acc1 += yl[0] * qf1;
acc2 += yl[1] * qf2;
aux32[0] = q4[2] | (q4[3] << 16);
aux32[1] = (aux32[0] >> 4) & 0x0f0f0f0f;
aux32[0] &= 0x0f0f0f0f;
qf1 = {shmem_f32[q8[0]], shmem_f32[q8[1]], shmem_f32[q8[2]], shmem_f32[q8[3]]};
qf2 = {shmem_f32[q8[4]], shmem_f32[q8[5]], shmem_f32[q8[6]], shmem_f32[q8[7]]};
acc1 += yl[2] * qf1;
acc2 += yl[3] * qf2;
acc1 += acc2;
sumf[row] += (float)xb.d * (acc1[0] + acc1[1] + acc1[2] + acc1[3]);
}
yb += 16 * QK4_NL;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < 2 && first_row + row < args.ne01; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum;
}
}
}
template<typename args_t>
void kernel_mul_mv_iq4_xs_f32_impl(
args_t args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg) {
threadgroup float * shmem_f32 = (threadgroup float *) shmem;
const int nb = args.ne00/QK_K;
const int r0 = tgpig.x;
const int r1 = tgpig.y;
const int im = tgpig.z;
const int first_row = (r0 * 2 + sgitg) * 2;
const uint i12 = im%args.ne12;
const uint i13 = im/args.ne12;
const uint64_t offset0 = first_row*args.nb01 + (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
const uint64_t offset1 = r1*args.nb11 + (i12 )*args.nb12 + (i13 )*args.nb13;
device const block_iq4_xs * x = (device const block_iq4_xs *) (src0 + offset0);
device const float * y = (device const float *) (src1 + offset1);
const int ix = tiisg/16; // 0 or 1
const int it = tiisg%16; // 0...15
const int ib = it/2;
const int il = it%2;
shmem_f32[tiisg] = kvalues_iq4nl_f[tiisg%16];
threadgroup_barrier(mem_flags::mem_threadgroup);
float4 yl[4];
float sumf[2]={0.f}, all_sum;
device const float * yb = y + ix * QK_K + ib * 32 + il * 8;
uint32_t aux32[2];
thread const uint8_t * q8 = (thread const uint8_t *)aux32;
float4 qf1, qf2;
for (int ibl = ix; ibl < nb; ibl += 2) {
device const float4 * y4 = (device const float4 *)yb;
yl[0] = y4[0]; yl[1] = y4[4]; yl[2] = y4[1]; yl[3] = y4[5];
for (int row = 0; row < 2; ++row) {
device const block_iq4_xs & xb = x[row*nb + ibl];
device const uint32_t * q4 = (device const uint32_t *)(xb.qs + 16*ib + 8*il);
float4 acc1 = {0.f}, acc2 = {0.f};
aux32[0] = (q4[0] ) & 0x0f0f0f0f;
aux32[1] = (q4[0] >> 4) & 0x0f0f0f0f;
qf1 = {shmem_f32[q8[0]], shmem_f32[q8[1]], shmem_f32[q8[2]], shmem_f32[q8[3]]};
qf2 = {shmem_f32[q8[4]], shmem_f32[q8[5]], shmem_f32[q8[6]], shmem_f32[q8[7]]};
acc1 += yl[0] * qf1;
acc2 += yl[1] * qf2;
aux32[0] = (q4[1] ) & 0x0f0f0f0f;
aux32[1] = (q4[1] >> 4) & 0x0f0f0f0f;
qf1 = {shmem_f32[q8[0]], shmem_f32[q8[1]], shmem_f32[q8[2]], shmem_f32[q8[3]]};
qf2 = {shmem_f32[q8[4]], shmem_f32[q8[5]], shmem_f32[q8[6]], shmem_f32[q8[7]]};
acc1 += yl[2] * qf1;
acc2 += yl[3] * qf2;
acc1 += acc2;
const int ls = (((xb.scales_l[ib/2] >> 4*(ib%2)) & 0xf) | (((xb.scales_h >> 2*ib) & 3) << 4)) - 32;
sumf[row] += (float)xb.d * ls * (acc1[0] + acc1[1] + acc1[2] + acc1[3]);
}
yb += 2 * QK_K;
}
device float * dst_f32 = (device float *) dst + (uint64_t)im*args.ne0*args.ne1 + (uint64_t)r1*args.ne0;
for (int row = 0; row < 2; ++row) {
all_sum = simd_sum(sumf[row]);
if (tiisg == 0) {
dst_f32[first_row + row] = all_sum;
}
}
}
[[host_name("kernel_mul_mv_iq1_s_f32")]]
kernel void kernel_mul_mv_iq1_s_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq1_s_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
[[host_name("kernel_mul_mv_iq1_m_f32")]]
kernel void kernel_mul_mv_iq1_m_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq1_m_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, nullptr, tgpig, tiisg, sgitg);
}
[[host_name("kernel_mul_mv_iq4_nl_f32")]]
kernel void kernel_mul_mv_iq4_nl_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq4_nl_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
}
[[host_name("kernel_mul_mv_iq4_xs_f32")]]
kernel void kernel_mul_mv_iq4_xs_f32(
constant ggml_metal_kargs_mul_mv & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
kernel_mul_mv_iq4_xs_f32_impl<constant ggml_metal_kargs_mul_mv &>(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
}
template<typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread float4x4 &)>
kernel void kernel_get_rows_q(
device const void * src0,
device const void * src1,
device float * dst,
constant int64_t & ne00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant int64_t & ne10,
constant uint64_t & nb10,
constant uint64_t & nb11,
constant uint64_t & nb1,
constant uint64_t & nb2,
uint3 tgpig[[threadgroup_position_in_grid]],
uint tiitg[[thread_index_in_threadgroup]],
uint3 tptg [[threads_per_threadgroup]]) {
const int64_t i10 = tgpig.x;
const int64_t i11 = tgpig.y;
const int64_t r = ((const device int32_t *) ((const device char *) src1 + i11*nb11 + i10*nb10))[0];
const int64_t i02 = i11;
for (int64_t ind = tiitg; ind < ne00/16; ind += tptg.x) {
float4x4 temp;
dequantize_func(((device const block_q *) ((const device char *) src0 + r*nb01 + i02*nb02)) + ind/nl, ind%nl, temp);
*(((device float4x4 *) ((device char *) dst + i11*nb2 + i10*nb1)) + ind) = temp;
}
}
template<typename T>
kernel void kernel_get_rows_f(
device const void * src0,
device const void * src1,
device float * dst,
constant int64_t & ne00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant int64_t & ne10,
constant uint64_t & nb10,
constant uint64_t & nb11,
constant uint64_t & nb1,
constant uint64_t & nb2,
uint3 tgpig[[threadgroup_position_in_grid]],
uint tiitg[[thread_index_in_threadgroup]],
uint3 tptg [[threads_per_threadgroup]]) {
const int64_t i10 = tgpig.x;
const int64_t i11 = tgpig.y;
const int64_t r = ((const device int32_t *) ((const device char *) src1 + i11*nb11 + i10*nb10))[0];
const int64_t i02 = i11;
for (int ind = tiitg; ind < ne00; ind += tptg.x) {
(( device float *) (( device char *) dst + i11*nb2 + i10*nb1))[ind] =
((const device T *) ((const device char *) src0 + i02*nb02 + r*nb01))[ind];
}
}
kernel void kernel_get_rows_i32(
device const void * src0,
device const void * src1,
device int32_t * dst,
constant int64_t & ne00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant int64_t & ne10,
constant uint64_t & nb10,
constant uint64_t & nb11,
constant uint64_t & nb1,
constant uint64_t & nb2,
uint3 tgpig[[threadgroup_position_in_grid]],
uint tiitg[[thread_index_in_threadgroup]],
uint3 tptg [[threads_per_threadgroup]]) {
const int64_t i10 = tgpig.x;
const int64_t i11 = tgpig.y;
const int64_t r = ((const device int32_t *) ((const device char *) src1 + i11*nb11 + i10*nb10))[0];
const int64_t i02 = i11;
for (int ind = tiitg; ind < ne00; ind += tptg.x) {
(( device int32_t *) (( device char *) dst + i11*nb2 + i10*nb1))[ind] =
((const device int32_t *) ((const device char *) src0 + i02*nb02 + r*nb01))[ind];
}
}
#define BLOCK_SIZE_M 64 // 8 simdgroup matrices from matrix A
#define BLOCK_SIZE_N 32 // 4 simdgroup matrices from matrix B
#define BLOCK_SIZE_K 32
#define THREAD_MAT_M 4 // each thread take 4 simdgroup matrices from matrix A
#define THREAD_MAT_N 2 // each thread take 2 simdgroup matrices from matrix B
#define THREAD_PER_BLOCK 128
#define THREAD_PER_ROW 2 // 2 thread for each row in matrix A to load numbers
#define THREAD_PER_COL 4 // 4 thread for each row in matrix B to load numbers
#define SG_MAT_SIZE 64 // simdgroup matrix is of shape 8x8
#define SG_MAT_ROW 8
// each block_q contains 16*nl weights
template<typename T, typename T4x4, typename simdgroup_T8x8, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread T4x4 &)>
kernel void kernel_mul_mm(
constant ggml_metal_kargs_mul_mm & args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
threadgroup T * sa = (threadgroup T *)(shmem);
threadgroup float * sb = (threadgroup float *)(shmem + 4096);
const int r0 = tgpig.y;
const int r1 = tgpig.x;
const int im = tgpig.z;
// if this block is of 64x32 shape or smaller
short n_rows = (args.ne0 - r0*BLOCK_SIZE_M < BLOCK_SIZE_M) ? (args.ne0 - r0*BLOCK_SIZE_M) : BLOCK_SIZE_M;
short n_cols = (args.ne1 - r1*BLOCK_SIZE_N < BLOCK_SIZE_N) ? (args.ne1 - r1*BLOCK_SIZE_N) : BLOCK_SIZE_N;
// a thread shouldn't load data outside of the matrix
short thread_row = ((short)tiitg/THREAD_PER_ROW) < n_rows ? ((short)tiitg/THREAD_PER_ROW) : n_rows - 1;
short thread_col = ((short)tiitg/THREAD_PER_COL) < n_cols ? ((short)tiitg/THREAD_PER_COL) : n_cols - 1;
simdgroup_T8x8 ma[4];
simdgroup_float8x8 mb[2];
simdgroup_float8x8 mc[8];
for (short i = 0; i < 8; i++){
mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
}
short il = (tiitg % THREAD_PER_ROW);
const int i12 = im%args.ne12;
const int i13 = im/args.ne12;
uint64_t offset0 = (i12/args.r2)*args.nb02 + (i13/args.r3)*args.nb03;
short offset1 = il/nl;
device const block_q * x = (device const block_q *)(src0 + (r0*BLOCK_SIZE_M + thread_row)*args.nb01 + offset0) + offset1;
device const float * y = (device const float *)(src1
+ args.nb13*i13
+ args.nb12*i12
+ args.nb11*(r1 * BLOCK_SIZE_N + thread_col)
+ args.nb10*(BLOCK_SIZE_K / THREAD_PER_COL * (tiitg % THREAD_PER_COL)));
for (int loop_k = 0; loop_k < args.ne00; loop_k += BLOCK_SIZE_K) {
// load data and store to threadgroup memory
T4x4 temp_a;
dequantize_func(x, il, temp_a);
threadgroup_barrier(mem_flags::mem_threadgroup);
#pragma unroll(16)
for (short i = 0; i < 16; i++) {
*(sa + SG_MAT_SIZE * ((tiitg/THREAD_PER_ROW/8) \
+ (tiitg%THREAD_PER_ROW)*16 + (i/8)*8) \
+ (tiitg/THREAD_PER_ROW)%8 + (i&7)*8) = temp_a[i/4][i%4];
}
*(threadgroup float2x4 *)(sb + (tiitg % THREAD_PER_COL)*8*32 + 8*(tiitg/THREAD_PER_COL)) = *((device float2x4 *) y);
il = (il + 2 < nl) ? il + 2 : il % 2;
x = (il < 2) ? x + (2+nl-1)/nl : x;
y += BLOCK_SIZE_K;
threadgroup_barrier(mem_flags::mem_threadgroup);
// load matrices from threadgroup memory and conduct outer products
threadgroup T * lsma = (sa + THREAD_MAT_M*SG_MAT_SIZE*(sgitg%2));
threadgroup float * lsmb = (sb + THREAD_MAT_N*SG_MAT_SIZE*(sgitg/2));
#pragma unroll(4)
for (short ik = 0; ik < BLOCK_SIZE_K / 8; ik++) {
#pragma unroll(4)
for (short i = 0; i < 4; i++) {
simdgroup_load(ma[i], lsma + SG_MAT_SIZE * i);
}
simdgroup_barrier(mem_flags::mem_none);
#pragma unroll(2)
for (short i = 0; i < 2; i++) {
simdgroup_load(mb[i], lsmb + SG_MAT_SIZE * i);
}
lsma += BLOCK_SIZE_M/SG_MAT_ROW * SG_MAT_SIZE;
lsmb += BLOCK_SIZE_N/SG_MAT_ROW * SG_MAT_SIZE;
#pragma unroll(8)
for (short i = 0; i < 8; i++){
simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
}
}
}
if ((r0 + 1) * BLOCK_SIZE_M <= args.ne0 && (r1 + 1) * BLOCK_SIZE_N <= args.ne1) {
device float * C = (device float *) dst +
(BLOCK_SIZE_M * r0 + 32 * (sgitg & 1)) + \
(BLOCK_SIZE_N * r1 + 16 * (sgitg >> 1)) * args.ne0 + im*args.ne1*args.ne0;
for (short i = 0; i < 8; i++) {
simdgroup_store(mc[i], C + 8 * (i%4) + 8 * args.ne0 * (i/4), args.ne0);
}
} else {
// block is smaller than 64x32, we should avoid writing data outside of the matrix
threadgroup_barrier(mem_flags::mem_threadgroup);
threadgroup float * temp_str = ((threadgroup float *) shmem) \
+ 32 * (sgitg&1) + (16 * (sgitg>>1))*BLOCK_SIZE_M;
for (short i = 0; i < 8; i++) {
simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*BLOCK_SIZE_M*(i/4), BLOCK_SIZE_M);
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (sgitg == 0) {
for (int j = tiitg; j < n_cols; j += BLOCK_SIZE_N) {
device float * D = (device float *) dst + (r0*BLOCK_SIZE_M) + (r1*BLOCK_SIZE_N + j)*args.ne0 + im*args.ne1*args.ne0;
device float4 * D4 = (device float4 *) D;
threadgroup float * C = temp_str + (j*BLOCK_SIZE_M);
threadgroup float4 * C4 = (threadgroup float4 *) C;
int i = 0;
for (; i < n_rows/4; i++) {
*(D4 + i) = *(C4 + i);
}
i *= 4;
for (; i < n_rows; i++) {
*(D + i) = *(C + i);
}
}
}
}
}
// same as kernel_mul_mm_impl, but src1 and dst are accessed via indices stored in rowids
// TODO: this kernel needs to be reimplemented from scratch for better performance
template<typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread half4x4 &)>
void kernel_mul_mm_id_impl(
int32_t ne00,
int32_t ne02,
uint64_t nb01,
uint64_t nb02,
int32_t ne11,
int32_t ne12,
uint64_t nb10,
uint64_t nb11,
uint64_t nb12,
int32_t ne0,
int32_t ne1,
int64_t ne0ne1,
device const char * src0,
device const char * src1,
threadgroup ushort2 * rowids,
device char * dst,
threadgroup char * shmem,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
threadgroup half * sa = (threadgroup half *)(shmem);
threadgroup float * sb = (threadgroup float *)(shmem + 4096);
const int r0 = tgpig.y;
const int r1 = tgpig.x;
if (r1*BLOCK_SIZE_N >= ne1) return;
// if this block is of 64x32 shape or smaller
short n_rows = (ne0 - r0 * BLOCK_SIZE_M < BLOCK_SIZE_M) ? (ne0 - r0 * BLOCK_SIZE_M) : BLOCK_SIZE_M;
short n_cols = (ne1 - r1 * BLOCK_SIZE_N < BLOCK_SIZE_N) ? (ne1 - r1 * BLOCK_SIZE_N) : BLOCK_SIZE_N;
// a thread shouldn't load data outside of the matrix
short thread_row = ((short)tiitg/THREAD_PER_ROW) < n_rows ? ((short)tiitg/THREAD_PER_ROW) : n_rows - 1;
short thread_col = ((short)tiitg/THREAD_PER_COL) < n_cols ? ((short)tiitg/THREAD_PER_COL) : n_cols - 1;
simdgroup_half8x8 ma[4];
simdgroup_float8x8 mb[2];
simdgroup_float8x8 mc[8];
for (int i = 0; i < 8; i++){
mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
}
short il = (tiitg % THREAD_PER_ROW);
ushort offset1 = il/nl;
threadgroup const auto & id = rowids[r1 * BLOCK_SIZE_N + thread_col];
device const block_q * x = (device const block_q *)(src0 + (r0 * BLOCK_SIZE_M + thread_row) * nb01) + offset1;
device const float * y = (device const float *)(src1
+ nb12 * id[1]
+ nb11 * (id[0] % ne11)
+ nb10 * (BLOCK_SIZE_K / THREAD_PER_COL * (tiitg % THREAD_PER_COL)));
for (int loop_k = 0; loop_k < ne00; loop_k += BLOCK_SIZE_K) {
// load data and store to threadgroup memory
half4x4 temp_a;
dequantize_func(x, il, temp_a);
threadgroup_barrier(mem_flags::mem_threadgroup);
for (int i = 0; i < 16; i++) {
*(sa + SG_MAT_SIZE * ((tiitg / THREAD_PER_ROW / 8) \
+ (tiitg % THREAD_PER_ROW) * 16 + (i / 8) * 8) \
+ (tiitg / THREAD_PER_ROW) % 8 + (i & 7) * 8) = temp_a[i/4][i%4];
}
*(threadgroup float2x4 *)(sb + (tiitg % THREAD_PER_COL) * 8 * 32 + 8 * (tiitg / THREAD_PER_COL)) = *((device float2x4 *)y);
il = (il + 2 < nl) ? il + 2 : il % 2;
x = (il < 2) ? x + (2+nl-1)/nl : x;
y += BLOCK_SIZE_K;
threadgroup_barrier(mem_flags::mem_threadgroup);
// load matrices from threadgroup memory and conduct outer products
threadgroup half * lsma = (sa + THREAD_MAT_M * SG_MAT_SIZE * (sgitg % 2));
threadgroup float * lsmb = (sb + THREAD_MAT_N * SG_MAT_SIZE * (sgitg / 2));
#pragma unroll(BLOCK_SIZE_K/8)
for (int ik = 0; ik < BLOCK_SIZE_K / 8; ik++) {
#pragma unroll(4)
for (int i = 0; i < 4; i++) {
simdgroup_load(ma[i], lsma + SG_MAT_SIZE * i);
}
simdgroup_barrier(mem_flags::mem_none);
#pragma unroll(2)
for (int i = 0; i < 2; i++) {
simdgroup_load(mb[i], lsmb + SG_MAT_SIZE * i);
}
lsma += BLOCK_SIZE_M / SG_MAT_ROW * SG_MAT_SIZE;
lsmb += BLOCK_SIZE_N / SG_MAT_ROW * SG_MAT_SIZE;
#pragma unroll(8)
for (int i = 0; i < 8; i++){
simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
}
}
}
{
threadgroup_barrier(mem_flags::mem_threadgroup);
threadgroup float * temp_str = ((threadgroup float *) shmem) \
+ 32 * (sgitg&1) + (16 * (sgitg>>1)) * BLOCK_SIZE_M;
for (int i = 0; i < 8; i++) {
simdgroup_store(mc[i], temp_str + 8 * (i%4) + 8 * BLOCK_SIZE_M * (i/4), BLOCK_SIZE_M);
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (sgitg == 0) {
for (int j = tiitg; j < n_cols; j += BLOCK_SIZE_N) {
threadgroup const auto & jid = rowids[r1 * BLOCK_SIZE_N + j];
int64_t joff = jid[0]*ne0 + jid[1]*ne0ne1;
device float * D = (device float *) dst + (r0*BLOCK_SIZE_M) + joff;
device float4 * D4 = (device float4 *) D;
threadgroup float * C = temp_str + (j*BLOCK_SIZE_M);
threadgroup float4 * C4 = (threadgroup float4 *) C;
int i = 0;
for (; i < n_rows/4; i++) {
*(D4 + i) = *(C4 + i);
}
i *= 4;
for (; i < n_rows; i++) {
*(D + i) = *(C + i);
}
}
}
}
}
template<typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread half4x4 &)>
kernel void kernel_mul_mm_id(
constant ggml_metal_kargs_mul_mm_id & args,
device const char * src0s,
device const char * src1,
device char * dst,
device const char * ids,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
const int32_t i02 = tgpig.z;
tgpig.z = 0;
device const char * src0 = src0s + i02*args.nb02;
// row indices
threadgroup ushort2 * rowids = (threadgroup ushort2 *)(shmem + 8192);
// TODO: parallelize this loop
int32_t _ne1 = 0;
for (ushort ii1 = 0; ii1 < args.nei1; ii1++) {
for (ushort ii0 = 0; ii0 < args.nei0; ii0++) {
int32_t id = ((device int32_t *) (ids + ii1*args.nbi1))[ii0];
if (id == i02) {
if (tiitg == 0) {
rowids[_ne1] = ushort2(ii0, ii1);
}
_ne1++;
}
}
}
threadgroup_barrier(mem_flags::mem_threadgroup);
kernel_mul_mm_id_impl<block_q, nl, dequantize_func>(
args.ne00,
args.ne02,
args.nb01,
args.nb02,
args.ne11,
args.ne12,
args.nb10,
args.nb11,
args.nb12,
args.ne0,
_ne1,
(int64_t)args.ne0*args.ne1,
src0,
src1,
rowids,
dst,
shmem,
tgpig,
tiitg,
sgitg);
}
#define QK_NL 16
//
// get rows
//
typedef decltype(kernel_get_rows_f<float>) get_rows_f_t;
template [[host_name("kernel_get_rows_f32")]] kernel get_rows_f_t kernel_get_rows_f<float>;
template [[host_name("kernel_get_rows_f16")]] kernel get_rows_f_t kernel_get_rows_f<half>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_get_rows_bf16")]] kernel get_rows_f_t kernel_get_rows_f<bfloat>;
#endif
typedef decltype(kernel_get_rows_q<block_q4_0, 2, dequantize_q4_0>) get_rows_q_t;
template [[host_name("kernel_get_rows_q4_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_0, 2, dequantize_q4_0>;
template [[host_name("kernel_get_rows_q4_1")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_1, 2, dequantize_q4_1>;
template [[host_name("kernel_get_rows_q5_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_0, 2, dequantize_q5_0>;
template [[host_name("kernel_get_rows_q5_1")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_1, 2, dequantize_q5_1>;
template [[host_name("kernel_get_rows_q8_0")]] kernel get_rows_q_t kernel_get_rows_q<block_q8_0, 2, dequantize_q8_0>;
template [[host_name("kernel_get_rows_q2_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q2_K, QK_NL, dequantize_q2_K>;
template [[host_name("kernel_get_rows_q3_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q3_K, QK_NL, dequantize_q3_K>;
template [[host_name("kernel_get_rows_q4_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q4_K, QK_NL, dequantize_q4_K>;
template [[host_name("kernel_get_rows_q5_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q5_K, QK_NL, dequantize_q5_K>;
template [[host_name("kernel_get_rows_q6_K")]] kernel get_rows_q_t kernel_get_rows_q<block_q6_K, QK_NL, dequantize_q6_K>;
template [[host_name("kernel_get_rows_iq2_xxs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_xxs, QK_NL, dequantize_iq2_xxs>;
template [[host_name("kernel_get_rows_iq2_xs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_xs, QK_NL, dequantize_iq2_xs>;
template [[host_name("kernel_get_rows_iq3_xxs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq3_xxs, QK_NL, dequantize_iq3_xxs>;
template [[host_name("kernel_get_rows_iq3_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq3_s, QK_NL, dequantize_iq3_s>;
template [[host_name("kernel_get_rows_iq2_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq2_s, QK_NL, dequantize_iq2_s>;
template [[host_name("kernel_get_rows_iq1_s")]] kernel get_rows_q_t kernel_get_rows_q<block_iq1_s, QK_NL, dequantize_iq1_s>;
template [[host_name("kernel_get_rows_iq1_m")]] kernel get_rows_q_t kernel_get_rows_q<block_iq1_m, QK_NL, dequantize_iq1_m>;
template [[host_name("kernel_get_rows_iq4_nl")]] kernel get_rows_q_t kernel_get_rows_q<block_iq4_nl, 2, dequantize_iq4_nl>;
template [[host_name("kernel_get_rows_iq4_xs")]] kernel get_rows_q_t kernel_get_rows_q<block_iq4_xs, QK_NL, dequantize_iq4_xs>;
//
// matrix-matrix multiplication
//
typedef decltype(kernel_mul_mm<half, half4x4, simdgroup_half8x8, float4x4, 1, dequantize_f32>) mat_mm_t;
template [[host_name("kernel_mul_mm_f32_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, float4x4, 1, dequantize_f32>;
template [[host_name("kernel_mul_mm_f16_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, half4x4, 1, dequantize_f16>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_mul_mm_bf16_f32")]] kernel mat_mm_t kernel_mul_mm<bfloat, bfloat4x4, simdgroup_bfloat8x8, bfloat4x4, 1, dequantize_bf16>;
#endif
template [[host_name("kernel_mul_mm_q4_0_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q4_0, 2, dequantize_q4_0>;
template [[host_name("kernel_mul_mm_q4_1_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q4_1, 2, dequantize_q4_1>;
template [[host_name("kernel_mul_mm_q5_0_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q5_0, 2, dequantize_q5_0>;
template [[host_name("kernel_mul_mm_q5_1_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q5_1, 2, dequantize_q5_1>;
template [[host_name("kernel_mul_mm_q8_0_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q8_0, 2, dequantize_q8_0>;
template [[host_name("kernel_mul_mm_q2_K_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K>;
template [[host_name("kernel_mul_mm_q3_K_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q3_K, QK_NL, dequantize_q3_K>;
template [[host_name("kernel_mul_mm_q4_K_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q4_K, QK_NL, dequantize_q4_K>;
template [[host_name("kernel_mul_mm_q5_K_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q5_K, QK_NL, dequantize_q5_K>;
template [[host_name("kernel_mul_mm_q6_K_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_q6_K, QK_NL, dequantize_q6_K>;
template [[host_name("kernel_mul_mm_iq2_xxs_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs>;
template [[host_name("kernel_mul_mm_iq2_xs_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq2_xs, QK_NL, dequantize_iq2_xs>;
template [[host_name("kernel_mul_mm_iq3_xxs_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq3_xxs, QK_NL, dequantize_iq3_xxs>;
template [[host_name("kernel_mul_mm_iq3_s_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq3_s, QK_NL, dequantize_iq3_s>;
template [[host_name("kernel_mul_mm_iq2_s_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq2_s, QK_NL, dequantize_iq2_s>;
template [[host_name("kernel_mul_mm_iq1_s_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq1_s, QK_NL, dequantize_iq1_s>;
template [[host_name("kernel_mul_mm_iq1_m_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq1_m, QK_NL, dequantize_iq1_m>;
template [[host_name("kernel_mul_mm_iq4_nl_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq4_nl, 2, dequantize_iq4_nl>;
template [[host_name("kernel_mul_mm_iq4_xs_f32")]] kernel mat_mm_t kernel_mul_mm<half, half4x4, simdgroup_half8x8, block_iq4_xs, QK_NL, dequantize_iq4_xs>;
//
// indirect matrix-matrix multiplication
//
typedef decltype(kernel_mul_mm_id<float4x4, 1, dequantize_f32>) mat_mm_id_t;
template [[host_name("kernel_mul_mm_id_f32_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<float4x4, 1, dequantize_f32>;
template [[host_name("kernel_mul_mm_id_f16_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<half4x4, 1, dequantize_f16>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_mul_mm_id_bf16_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<bfloat4x4, 1, dequantize_bf16>;
#endif
template [[host_name("kernel_mul_mm_id_q4_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q4_0, 2, dequantize_q4_0>;
template [[host_name("kernel_mul_mm_id_q4_1_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q4_1, 2, dequantize_q4_1>;
template [[host_name("kernel_mul_mm_id_q5_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q5_0, 2, dequantize_q5_0>;
template [[host_name("kernel_mul_mm_id_q5_1_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q5_1, 2, dequantize_q5_1>;
template [[host_name("kernel_mul_mm_id_q8_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q8_0, 2, dequantize_q8_0>;
template [[host_name("kernel_mul_mm_id_q2_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q2_K, QK_NL, dequantize_q2_K>;
template [[host_name("kernel_mul_mm_id_q3_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q3_K, QK_NL, dequantize_q3_K>;
template [[host_name("kernel_mul_mm_id_q4_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q4_K, QK_NL, dequantize_q4_K>;
template [[host_name("kernel_mul_mm_id_q5_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q5_K, QK_NL, dequantize_q5_K>;
template [[host_name("kernel_mul_mm_id_q6_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_q6_K, QK_NL, dequantize_q6_K>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq2_xxs, QK_NL, dequantize_iq2_xxs>;
template [[host_name("kernel_mul_mm_id_iq2_xs_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq2_xs, QK_NL, dequantize_iq2_xs>;
template [[host_name("kernel_mul_mm_id_iq3_xxs_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq3_xxs, QK_NL, dequantize_iq3_xxs>;
template [[host_name("kernel_mul_mm_id_iq3_s_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq3_s, QK_NL, dequantize_iq3_s>;
template [[host_name("kernel_mul_mm_id_iq2_s_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq2_s, QK_NL, dequantize_iq2_s>;
template [[host_name("kernel_mul_mm_id_iq1_s_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq1_s, QK_NL, dequantize_iq1_s>;
template [[host_name("kernel_mul_mm_id_iq1_m_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq1_m, QK_NL, dequantize_iq1_m>;
template [[host_name("kernel_mul_mm_id_iq4_nl_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq4_nl, 2, dequantize_iq4_nl>;
template [[host_name("kernel_mul_mm_id_iq4_xs_f32")]] kernel mat_mm_id_t kernel_mul_mm_id<block_iq4_xs, QK_NL, dequantize_iq4_xs>;
//
// matrix-vector multiplication
//
typedef void (kernel_mul_mv_impl_t)(
ggml_metal_kargs_mul_mv args,
device const char * src0,
device const char * src1,
device char * dst,
uint3 tgpig,
ushort tiisg);
typedef void (kernel_mul_mv2_impl_t)(
ggml_metal_kargs_mul_mv args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiisg,
ushort sgitg);
template<kernel_mul_mv_impl_t impl_fn>
void mmv_fn(
ggml_metal_kargs_mul_mv args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiitg,
ushort tiisg,
ushort sgitg) {
impl_fn(args, src0, src1, dst, tgpig, tiisg);
}
template<kernel_mul_mv2_impl_t impl_fn>
void mmv_fn(
ggml_metal_kargs_mul_mv args,
device const char * src0,
device const char * src1,
device char * dst,
threadgroup char * shmem,
uint3 tgpig,
ushort tiitg,
ushort tiisg,
ushort sgitg) {
impl_fn(args, src0, src1, dst, shmem, tgpig, tiisg, sgitg);
}
typedef decltype(mmv_fn<kernel_mul_mv_impl<half, half4, half, half4, ggml_metal_kargs_mul_mv>>) mul_mv_impl_fn_t;
template<mul_mv_impl_fn_t impl_fn>
kernel void kernel_mul_mv_id(
constant ggml_metal_kargs_mul_mv_id & args,
device const char * src0s,
device const char * src1,
device char * dst,
device const char * ids,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort tiitg[[thread_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]]) {
const int iid1 = tgpig.z/args.nei0;
const int idx = tgpig.z%args.nei0;
tgpig.z = 0;
const int32_t i02 = ((device const int32_t *) (ids + iid1*args.nbi1))[idx];
const int64_t i11 = idx % args.ne11;
const int64_t i12 = iid1;
const int64_t i1 = idx;
const int64_t i2 = i12;
device const char * src0_cur = src0s + i02*args.nb02;
device const char * src1_cur = src1 + i11*args.nb11 + i12*args.nb12;
device char * dst_cur = dst + (i1*args.ne0 + i2*args.ne1*args.ne0)*sizeof(float);
ggml_metal_kargs_mul_mv args0 = {
/*.ne00 =*/ args.ne00,
/*.ne01 =*/ args.ne01,
/*.ne02 =*/ 1, // args.ne02,
/*.nb00 =*/ args.nb00,
/*.nb01 =*/ args.nb01,
/*.nb02 =*/ args.nb02,
/*.nb03 =*/ args.nb02, // args.ne02 == 1
/*.ne10 =*/ args.ne10,
/*.ne11 =*/ 1, // args.ne11,
/*.ne12 =*/ 1, // args.ne12,
/*.nb10 =*/ args.nb10,
/*.nb11 =*/ args.nb11,
/*.nb12 =*/ args.nb12,
/*.nb13 =*/ args.nb12, // ne12 == 1
/*.ne0 =*/ args.ne0,
/*.ne1 =*/ 1, // args.ne1,
/*.r2 =*/ 1,
/*.r3 =*/ 1,
};
impl_fn(
args0,
/* src0 */ src0_cur,
/* src1 */ src1_cur,
/* dst */ dst_cur,
shmem,
tgpig,
tiitg,
tiisg,
sgitg);
}
typedef decltype(kernel_mul_mv_id<mmv_fn<kernel_mul_mv_impl<float, float4, float, float4>>>) kernel_mul_mv_id_t;
template [[host_name("kernel_mul_mv_id_f32_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_impl<float, float4, float, float4>>>;
template [[host_name("kernel_mul_mv_id_f16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_impl<half, half4, float, float4>>>;
#if defined(GGML_METAL_USE_BF16)
template [[host_name("kernel_mul_mv_id_bf16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_impl<bfloat, bfloat4, float, float4>>>;
#endif
template [[host_name("kernel_mul_mv_id_q8_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_q8_0_f32_impl>>;
template [[host_name("kernel_mul_mv_id_q4_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<mul_vec_q_n_f32_impl<block_q4_0, N_DST, N_SIMDGROUP, N_SIMDWIDTH>>>;
template [[host_name("kernel_mul_mv_id_q4_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<mul_vec_q_n_f32_impl<block_q4_1, N_DST, N_SIMDGROUP, N_SIMDWIDTH>>>;
template [[host_name("kernel_mul_mv_id_q5_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<mul_vec_q_n_f32_impl<block_q5_0, N_DST, N_SIMDGROUP, N_SIMDWIDTH>>>;
template [[host_name("kernel_mul_mv_id_q5_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<mul_vec_q_n_f32_impl<block_q5_1, N_DST, N_SIMDGROUP, N_SIMDWIDTH>>>;
template [[host_name("kernel_mul_mv_id_q2_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_q2_K_f32_impl>>;
template [[host_name("kernel_mul_mv_id_q3_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_q3_K_f32_impl>>;
template [[host_name("kernel_mul_mv_id_q4_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_q4_K_f32_impl>>;
template [[host_name("kernel_mul_mv_id_q5_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_q5_K_f32_impl>>;
template [[host_name("kernel_mul_mv_id_q6_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_q6_K_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq1_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq1_s_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq1_m_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq1_m_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq2_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq2_xxs_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq2_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq2_xs_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq3_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq3_xxs_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq3_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq3_s_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq2_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq2_s_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq4_nl_f32_impl>>;
template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id<mmv_fn<kernel_mul_mv_iq4_xs_f32_impl>>;
kernel void kernel_pool_2d_max_f32(
device const float * src0,
device float * dst,
constant int32_t & k0,
constant int32_t & k1,
constant int32_t & s0,
constant int32_t & s1,
constant int32_t & p0,
constant int32_t & p1,
constant int64_t & IH,
constant int64_t & IW,
constant int64_t & OH,
constant int64_t & OW,
constant int64_t & parallel_elements,
uint gid[[thread_position_in_grid]]) {
if (gid >= parallel_elements) {
return;
}
const int idx = gid;
const int I_HW = IH * IW;
const int O_HW = OH * OW;
const int nc = idx / O_HW;
const int cur_oh = idx % O_HW / OW;
const int cur_ow = idx % O_HW % OW;
device const float * i_ptr = src0 + nc * I_HW;
device float * o_ptr = dst + nc * O_HW;
const int start_h = cur_oh * s1 - p1;
const int bh = MAX(0, start_h);
const int eh = MIN(IH, start_h + k1);
const int start_w = cur_ow * s0 - p0;
const int bw = MAX(0, start_w);
const int ew = MIN(IW, start_w + k0);
float res = -INFINITY;
for (int i = bh; i < eh; i += 1) {
for (int j = bw; j < ew; j += 1) {
res = MAX(res, i_ptr[i * IW + j]);
}
}
o_ptr[cur_oh * OW + cur_ow] = res;
}
kernel void kernel_pool_2d_avg_f32(
device const float * src0,
device float * dst,
constant int32_t & k0,
constant int32_t & k1,
constant int32_t & s0,
constant int32_t & s1,
constant int32_t & p0,
constant int32_t & p1,
constant int64_t & IH,
constant int64_t & IW,
constant int64_t & OH,
constant int64_t & OW,
constant int64_t & parallel_elements,
uint gid[[thread_position_in_grid]]) {
if (gid >= parallel_elements) {
return;
}
const int idx = gid;
const int I_HW = IH * IW;
const int O_HW = OH * OW;
const int nc = idx / O_HW;
const int cur_oh = idx % O_HW / OW;
const int cur_ow = idx % O_HW % OW;
device const float * i_ptr = src0 + nc * I_HW;
device float * o_ptr = dst + nc * O_HW;
const int start_h = cur_oh * s1 - p1;
const int bh = MAX(0, start_h);
const int eh = MIN(IH, start_h + k1);
const int start_w = cur_ow * s0 - p0;
const int bw = MAX(0, start_w);
const int ew = MIN(IW, start_w + k0);
// const float scale = 1. / ((eh - bh) * (ew - bw));
const float scale = 1. / (k0 * k1);
float res = 0;
for (int i = bh; i < eh; i += 1) {
for (int j = bw; j < ew; j += 1) {
float cur = i_ptr[i * IW + j];
res += cur * scale;
}
}
o_ptr[cur_oh * OW + cur_ow] = res;
}