mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2025-01-01 06:14:35 +00:00
metal : int -> short, style
ggml-ci
This commit is contained in:
parent
535050572a
commit
3d1fe1bb4d
@ -6317,8 +6317,8 @@ kernel void kernel_mul_mm(device const uchar * src0,
|
||||
const uint im = tgpig.z;
|
||||
|
||||
// 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;
|
||||
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;
|
||||
@ -6326,9 +6326,10 @@ kernel void kernel_mul_mm(device const uchar * src0,
|
||||
|
||||
simdgroup_T8x8 ma[4];
|
||||
simdgroup_float8x8 mb[2];
|
||||
simdgroup_float8x8 c_res[8];
|
||||
for (int i = 0; i < 8; i++){
|
||||
c_res[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
|
||||
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);
|
||||
@ -6339,7 +6340,7 @@ kernel void kernel_mul_mm(device const uchar * src0,
|
||||
uint offset0 = (i12/r2)*nb02 + (i13/r3)*nb03;
|
||||
ushort offset1 = il/nl;
|
||||
|
||||
device const block_q * x = (device const block_q *)(src0 + (r0 * BLOCK_SIZE_M + thread_row) * nb01 + offset0) + offset1;
|
||||
device const block_q * x = (device const block_q *)(src0 + (r0*BLOCK_SIZE_M + thread_row)*nb01 + offset0) + offset1;
|
||||
device const float * y = (device const float *)(src1
|
||||
+ nb13 * i13
|
||||
+ nb12 * i12
|
||||
@ -6353,13 +6354,13 @@ kernel void kernel_mul_mm(device const uchar * src0,
|
||||
threadgroup_barrier(mem_flags::mem_threadgroup);
|
||||
|
||||
#pragma unroll(16)
|
||||
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];
|
||||
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);
|
||||
*(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;
|
||||
@ -6368,27 +6369,27 @@ kernel void kernel_mul_mm(device const uchar * src0,
|
||||
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));
|
||||
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 (int ik = 0; ik < BLOCK_SIZE_K / 8; ik++) {
|
||||
for (short 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);
|
||||
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 (int i = 0; i < 2; i++) {
|
||||
simdgroup_load(mb[i],lsmb + SG_MAT_SIZE * i);
|
||||
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;
|
||||
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(c_res[i], mb[i/4], ma[i%4], c_res[i]);
|
||||
for (short i = 0; i < 8; i++){
|
||||
simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -6396,16 +6397,16 @@ kernel void kernel_mul_mm(device const uchar * src0,
|
||||
if ((r0 + 1) * BLOCK_SIZE_M <= ne0 && (r1 + 1) * BLOCK_SIZE_N <= ne1) {
|
||||
device float * C = dst + (BLOCK_SIZE_M * r0 + 32 * (sgitg & 1)) \
|
||||
+ (BLOCK_SIZE_N * r1 + 16 * (sgitg >> 1)) * ne0 + im*ne1*ne0;
|
||||
for (int i = 0; i < 8; i++) {
|
||||
simdgroup_store(c_res[i], C + 8 * (i%4) + 8 * ne0 * (i/4), ne0);
|
||||
for (short i = 0; i < 8; i++) {
|
||||
simdgroup_store(mc[i], C + 8 * (i%4) + 8 * ne0 * (i/4), 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 *)shared_memory) \
|
||||
+ 32 * (sgitg&1) + (16 * (sgitg>>1)) * BLOCK_SIZE_M;
|
||||
for (int i = 0; i < 8; i++) {
|
||||
simdgroup_store(c_res[i], temp_str + 8 * (i%4) + 8 * BLOCK_SIZE_M * (i/4), BLOCK_SIZE_M);
|
||||
threadgroup float * temp_str = ((threadgroup float *) shared_memory) \
|
||||
+ 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);
|
||||
|
Loading…
Reference in New Issue
Block a user