#include using namespace metal; #define MAX(x, y) ((x) > (y) ? (x) : (y)) #define QK4_0 32 #define QR4_0 2 typedef struct { half d; // delta uint8_t qs[QK4_0 / 2]; // nibbles / quants } block_q4_0; #define QK4_1 32 typedef struct { half d; // delta half m; // min uint8_t qs[QK4_1 / 2]; // nibbles / quants } block_q4_1; #define QK8_0 32 typedef struct { half d; // delta int8_t qs[QK8_0]; // quants } block_q8_0; kernel void kernel_add( device const float4 * src0, device const float4 * src1, device float4 * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = src0[tpig] + src1[tpig]; } // assumption: src1 is a row // broadcast src1 into src0 kernel void kernel_add_row( device const float4 * src0, device const float4 * src1, device float4 * dst, constant int64_t & nb, uint tpig[[thread_position_in_grid]]) { dst[tpig] = src0[tpig] + src1[tpig % nb]; } kernel void kernel_mul( device const float4 * src0, device const float4 * src1, device float4 * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = src0[tpig] * src1[tpig]; } // assumption: src1 is a row // broadcast src1 into src0 kernel void kernel_mul_row( device const float4 * src0, device const float4 * src1, device float4 * dst, constant int64_t & nb, uint tpig[[thread_position_in_grid]]) { dst[tpig] = src0[tpig] * src1[tpig % nb]; } kernel void kernel_scale( device const float4 * src0, device float4 * dst, constant float & scale, uint tpig[[thread_position_in_grid]]) { dst[tpig] = src0[tpig] * scale; } kernel void kernel_silu( 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_relu( device const float * src0, device float * dst, uint tpig[[thread_position_in_grid]]) { dst[tpig] = max(0.0f, src0[tpig]); } constant float GELU_COEF_A = 0.044715f; constant float SQRT_2_OVER_PI = 0.79788456080286535587989211986876f; kernel void kernel_gelu( 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_soft_max( device const float * src0, device float * dst, constant int64_t & ne00, constant int64_t & ne01, constant int64_t & ne02, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { const int64_t i03 = tgpig[2]; const int64_t i02 = tgpig[1]; const int64_t i01 = tgpig[0]; device const float * psrc0 = src0 + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00; device float * pdst = dst + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00; // parallel max float lmax = tpitg[0] < ne00 ? psrc0[tpitg[0]] : -INFINITY; for (int i00 = tpitg[0] + ntg[0]; i00 < ne00; i00 += ntg[0]) { lmax = MAX(lmax, psrc0[i00]); } const float max = simd_max(lmax); // parallel sum float lsum = 0.0f; for (int i00 = tpitg[0]; i00 < ne00; i00 += ntg[0]) { const float exp_psrc0 = exp(psrc0[i00] - max); lsum += exp_psrc0; // Remember the result of exp here. exp is expensive, so we really do not // whish to compute it twice. pdst[i00] = exp_psrc0; } const float sum = simd_sum(lsum); for (int i00 = tpitg[0]; i00 < ne00; i00 += ntg[0]) { pdst[i00] /= sum; } } kernel void kernel_soft_max_4( device const float * src0, device float * dst, constant int64_t & ne00, constant int64_t & ne01, constant int64_t & ne02, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { const int64_t i03 = tgpig[2]; const int64_t i02 = tgpig[1]; const int64_t i01 = tgpig[0]; device const float4 * psrc4 = (device const float4 *)(src0 + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00); device float4 * pdst4 = (device float4 *)(dst + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00); // parallel max float4 lmax4 = tpitg[0] < ne00/4 ? psrc4[tpitg[0]] : -INFINITY; for (int i00 = tpitg[0] + ntg[0]; i00 < ne00/4; i00 += ntg[0]) { lmax4 = fmax(lmax4, psrc4[i00]); } float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3])); const float max = simd_max(lmax); // parallel sum float4 lsum4 = 0.0f; for (int i00 = tpitg[0]; i00 < ne00/4; i00 += ntg[0]) { const float4 exp_psrc4 = exp(psrc4[i00] - max); lsum4 += exp_psrc4; pdst4[i00] = exp_psrc4; } float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3]; const float sum = simd_sum(lsum); for (int i00 = tpitg[0]; i00 < ne00/4; i00 += ntg[0]) { pdst4[i00] /= sum; } } 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; } } } kernel void kernel_norm( device const void * src0, device float * dst, constant int64_t & ne00, constant uint64_t & nb01, constant float & eps, threadgroup float * sum [[threadgroup(0)]], uint tgpig[[threadgroup_position_in_grid]], uint tpitg[[thread_position_in_threadgroup]], uint ntg[[threads_per_threadgroup]]) { device const float * x = (device const float *) ((device const char *) src0 + tgpig*nb01); // MEAN // parallel sum sum[tpitg] = 0.0f; for (int i00 = tpitg; i00 < ne00; i00 += ntg) { sum[tpitg] += x[i00]; } // reduce threadgroup_barrier(mem_flags::mem_threadgroup); for (uint i = ntg/2; i > 0; i /= 2) { if (tpitg < i) { sum[tpitg] += sum[tpitg + i]; } threadgroup_barrier(mem_flags::mem_threadgroup); } const float mean = sum[0] / ne00; // recenter and VARIANCE threadgroup_barrier(mem_flags::mem_threadgroup); device float * y = dst + tgpig*ne00; sum[tpitg] = 0.0f; for (int i00 = tpitg; i00 < ne00; i00 += ntg) { y[i00] = x[i00] - mean; sum[tpitg] += y[i00] * y[i00]; } // reduce threadgroup_barrier(mem_flags::mem_threadgroup); for (uint i = ntg/2; i > 0; i /= 2) { if (tpitg < i) { sum[tpitg] += sum[tpitg + i]; } threadgroup_barrier(mem_flags::mem_threadgroup); } const float variance = sum[0] / ne00; const float scale = 1.0f/sqrt(variance + eps); for (int i00 = tpitg; i00 < ne00; i00 += ntg) { y[i00] = y[i00] * scale; } } kernel void kernel_rms_norm( device const void * src0, device float * dst, constant int64_t & ne00, constant uint64_t & nb01, constant float & eps, threadgroup float * sum [[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]]) { device const float4 * x = (device const float4 *) ((device const char *) src0 + tgpig*nb01); device const float * x_scalar = (device const float *) x; float4 sumf=0; float all_sum=0; // parallel sum for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) { sumf += x[i00] * x[i00]; } all_sum = sumf[0] + sumf[1] + sumf[2] + sumf[3]; all_sum = simd_sum(all_sum); if (tiisg == 0) { sum[sgitg] = all_sum; } threadgroup_barrier(mem_flags::mem_threadgroup); // broadcast, simd group number is ntg / 32 for (uint i = ntg / 32 / 2; i > 0; i /= 2) { if (tpitg < i) { sum[tpitg] += sum[tpitg + i]; } } if (tpitg == 0) { for (int i = 4 * (ne00 / 4); i < ne00; i++) {sum[0] += x_scalar[i];} sum[0] /= ne00; } threadgroup_barrier(mem_flags::mem_threadgroup); const float mean = sum[0]; const float scale = 1.0f/sqrt(mean + eps); device float4 * y = (device float4 *) (dst + tgpig*ne00); device float * y_scalar = (device float *) y; for (int i00 = tpitg; i00 < ne00/4; i00 += ntg) { y[i00] = x[i00] * scale; } if (tpitg == 0) { for (int i00 = 4 * (ne00 / 4); i00 < ne00; i00++) {y_scalar[i00] = x_scalar[i00] * 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; float2 acc = 0.f; 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) + yl[i + 1] * (qs[i / 2] & 0x0F00); acc[1] += yl[i + 8] * (qs[i / 2] & 0x00F0) + yl[i + 9] * (qs[i / 2] & 0xF000); } return d * (sumy * -8.f + acc[0] + acc[1]); } // 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; device const uint16_t * qs = ((device const uint16_t *)qb_curr + 2 + il/2); float2 acc = 0.f; for (int i = 0; i < 8; i+=2) { acc[0] += yl[i + 0] * (qs[i / 2] & 0x000F) + yl[i + 1] * (qs[i / 2] & 0x0F00); acc[1] += yl[i + 8] * (qs[i / 2] & 0x00F0) + yl[i + 9] * (qs[i / 2] & 0xF000); } return d * (acc[0] + acc[1]) + 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 #define N_SIMDWIDTH 32 // assuming SIMD group size is 32 //Note: This is a template, but strictly speaking it only applies to // quantizations where the block size is 32. It also does not // giard against the number of rows not being divisible by // N_DST, so this is another explicit assumption of the implementation. template void mul_vec_q_n_f32(device const void * src0, device const float * src1, device float * dst, int64_t ne00, int64_t ne01, int64_t ne02, int64_t ne10, int64_t ne12, int64_t ne0, int64_t ne1, uint gqa, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 offset0 = first_row * nb + im/gqa*(nb*ne0); device const block_q_type * x = (device const block_q_type *) src0 + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; float yl[16]; // src1 vector cache float sumf[nr]={0.f}; const int ix = tiisg/2; const int il = 8*(tiisg%2); 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 = 0; for (int i = 0; i < 8; i += 2) { sumy += yb[i] + yb[i+1]; yl[i+0] = yb[i+ 0]; yl[i+1] = yb[i+ 1]/256.f; sumy += yb[i+16] + yb[i+17]; yl[i+8] = yb[i+16]/16.f; yl[i+9] = yb[i+17]/4096.f; } for (int row = 0; row < nr; row++) { sumf[row] += block_q_n_dot_y(x+ib+row*nb, sumy, yl, il); } yb += QK4_0 * 16; } for (int row = 0; row < nr; ++row) { const float tot = simd_sum(sumf[row]); if (tiisg == 0 && first_row + row < ne01) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = tot; } } } kernel void kernel_mul_mat_q4_0_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { mul_vec_q_n_f32(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,gqa,tgpig,tiisg,sgitg); } kernel void kernel_mul_mat_q4_1_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { mul_vec_q_n_f32(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,gqa,tgpig,tiisg,sgitg); } #define NB_Q8_0 8 kernel void kernel_mul_mat_q8_0_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const int nr = N_DST; const int nsg = N_SIMDGROUP; const int nw = N_SIMDWIDTH; const int nb = 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 offset0 = first_row * nb + im/gqa*(nb*ne0); device const block_q8_0 * x = (device const block_q8_0 *) src0 + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; float yl[NB_Q8_0]; float sumf[nr]={0.f}; const int ix = tiisg/4; const int il = tiisg%4; device const float * yb = y + ix * QK8_0 + NB_Q8_0*il; // 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 (int i = 0; i < NB_Q8_0; ++i) { yl[i] = yb[i]; } for (int row = 0; row < nr; row++) { device const int8_t * qs = x[ib+row*nb].qs + NB_Q8_0*il; float sumq = 0.f; for (int iq = 0; iq < NB_Q8_0; ++iq) { sumq += qs[iq] * yl[iq]; } sumf[row] += sumq*x[ib+row*nb].d; } yb += NB_Q8_0 * nw; } for (int row = 0; row < nr; ++row) { const float tot = simd_sum(sumf[row]); if (tiisg == 0 && first_row + row < ne01) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = tot; } } } kernel void kernel_mul_mat_f16_f32_1row( device const char * src0, device const char * 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 int64_t & ne12, constant uint64_t & nb10, constant uint64_t & nb11, constant uint64_t & nb12, constant int64_t & ne0, constant int64_t & ne1, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]]) { const int64_t r0 = tgpig.x; const int64_t r1 = tgpig.y; const int64_t im = tgpig.z; device const half * x = (device const half *) (src0 + r0*nb01 + im/(ne12/ne02)*nb02); device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12); float sumf = 0; if (ne00 < 128) { for (int i = tiisg; i < ne00; i += 32) { sumf += (float) x[i] * (float) y[i]; } float all_sum = simd_sum(sumf); if (tiisg == 0) { dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum; } } else { device const half4 * x4 = (device const half4 *) x; device const float4 * y4 = (device const float4 *) y; for (int i = tiisg; i < ne00/4; i += 32) { for (int k = 0; k < 4; ++k) sumf += (float)x4[i][k] * y4[i][k]; } float all_sum = simd_sum(sumf); if (tiisg == 0) { for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) x[i] * y[i]; dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum; } } } #define N_F16_F32 4 kernel void kernel_mul_mat_f16_f32( device const char * src0, device const char * 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 int64_t & ne12, constant uint64_t & nb10, constant uint64_t & nb11, constant uint64_t & nb12, constant int64_t & ne0, constant int64_t & ne1, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]]) { const int64_t r0 = tgpig.x; const int64_t rb = tgpig.y*N_F16_F32; const int64_t im = tgpig.z; device const half * x = (device const half *) (src0 + r0*nb01 + im/(ne12/ne02)*nb02); if (ne00 < 128) { for (int row = 0; row < N_F16_F32; ++row) { int r1 = rb + row; if (r1 >= ne11) { break; } device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12); float sumf = 0; for (int i = tiisg; i < ne00; i += 32) { sumf += (float) x[i] * (float) y[i]; } float all_sum = simd_sum(sumf); if (tiisg == 0) { dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum; } } } else { device const half4 * x4 = (device const half4 *)x; for (int row = 0; row < N_F16_F32; ++row) { int r1 = rb + row; if (r1 >= ne11) { break; } device const float * y = (device const float *) (src1 + r1*nb11 + im*nb12); device const float4 * y4 = (device const float4 *) y; float sumf = 0; for (int i = tiisg; i < ne00/4; i += 32) { for (int k = 0; k < 4; ++k) sumf += (float) x4[i][k] * y4[i][k]; } float all_sum = simd_sum(sumf); if (tiisg == 0) { for (int i = 4*(ne00/4); i < ne00; ++i) all_sum += (float) x[i] * y[i]; dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum; } } } } // Assumes row size (ne00) is a multiple of 4 kernel void kernel_mul_mat_f16_f32_l4( device const char * src0, device const char * 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 int64_t & ne12, constant uint64_t & nb10, constant uint64_t & nb11, constant uint64_t & nb12, constant int64_t & ne0, constant int64_t & ne1, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]]) { const int nrows = ne11; const int64_t r0 = tgpig.x; const int64_t im = tgpig.z; device const half4 * x4 = (device const half4 *) (src0 + r0*nb01 + im/(ne12/ne02)*nb02); for (int r1 = 0; r1 < nrows; ++r1) { device const float4 * y4 = (device const float4 *) (src1 + r1*nb11 + im*nb12); float sumf = 0; for (int i = tiisg; i < ne00/4; i += 32) { for (int k = 0; k < 4; ++k) sumf += (float) x4[i][k] * y4[i][k]; } float all_sum = simd_sum(sumf); if (tiisg == 0) { dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum; } } } kernel void kernel_alibi_f32( 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 & 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 & m0, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { const int64_t i03 = tgpig[2]; const int64_t i02 = tgpig[1]; const int64_t i01 = tgpig[0]; const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00; const int64_t i3 = n / (ne2*ne1*ne0); const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0); const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0; const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0); device float * dst_data = (device float *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); float m_k = pow(m0, i2 + 1); for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00); dst_data[i00] = src[0] + m_k * (i00 - ne00 + 1); } } kernel void kernel_rope( device const void * 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 & 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 int & n_past, constant int & n_dims, constant int & mode, constant float & freq_base, constant float & freq_scale, uint tiitg[[thread_index_in_threadgroup]], uint3 tptg[[threads_per_threadgroup]], uint3 tgpig[[threadgroup_position_in_grid]]) { const int64_t i3 = tgpig[2]; const int64_t i2 = tgpig[1]; const int64_t i1 = tgpig[0]; const bool is_neox = mode & 2; const int64_t p = ((mode & 1) == 0 ? n_past + i2 : i2); const float theta_0 = freq_scale * (float)p; const float inv_ndims = -1.f/n_dims; if (!is_neox) { for (int64_t i0 = 2*tiitg; i0 < ne0; i0 += 2*tptg.x) { const float theta = theta_0 * pow(freq_base, inv_ndims*i0); const float cos_theta = cos(theta); const float sin_theta = sin(theta); device const float * const src = (device float *)((device char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00); device float * dst_data = (device float *)((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*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 { for (int64_t ib = 0; ib < ne0/n_dims; ++ib) { for (int64_t ic = 2*tiitg; ic < n_dims; ic += 2*tptg.x) { const float theta = theta_0 * pow(freq_base, inv_ndims*ic - ib); const float cos_theta = cos(theta); const float sin_theta = sin(theta); const int64_t i0 = ib*n_dims + ic/2; device const float * const src = (device float *)((device char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00); device float * dst_data = (device float *)((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); const float x0 = src[0]; const float x1 = src[n_dims/2]; dst_data[0] = x0*cos_theta - x1*sin_theta; dst_data[n_dims/2] = x0*sin_theta + x1*cos_theta; } } } } kernel void kernel_cpy_f16_f16( device const half * src0, device half * 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 i03 = tgpig[2]; const int64_t i02 = tgpig[1]; const int64_t i01 = tgpig[0]; const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00; const int64_t i3 = n / (ne2*ne1*ne0); const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0); const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0; const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0); device half * dst_data = (device half *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) { device const half * src = (device half *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00); dst_data[i00] = src[0]; } } kernel void kernel_cpy_f32_f16( device const float * src0, device half * 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 i03 = tgpig[2]; const int64_t i02 = tgpig[1]; const int64_t i01 = tgpig[0]; const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00; const int64_t i3 = n / (ne2*ne1*ne0); const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0); const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0; const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0); device half * dst_data = (device half *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00); dst_data[i00] = src[0]; } } kernel void kernel_cpy_f32_f32( 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 & 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 i03 = tgpig[2]; const int64_t i02 = tgpig[1]; const int64_t i01 = tgpig[0]; const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00; const int64_t i3 = n / (ne2*ne1*ne0); const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0); const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0; const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0); device float * dst_data = (device float *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x; i00 < ne00; i00 += ntg.x) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00); dst_data[i00] = src[0]; } } //============================================ k-quants ====================================================== #ifndef QK_K #define QK_K 256 #else static_assert(QK_K == 256 || QK_K == 64, "QK_K must be 256 or 64"); #endif #if QK_K == 256 #define K_SCALE_SIZE 12 #else #define K_SCALE_SIZE 4 #endif typedef struct { uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits uint8_t qs[QK_K/4]; // quants half d; // super-block scale for quantized scales half dmin; // super-block scale for quantized mins } block_q2_K; // 84 bytes / block typedef struct { uint8_t hmask[QK_K/8]; // quants - high bit uint8_t qs[QK_K/4]; // quants - low 2 bits #if QK_K == 64 uint8_t scales[2]; #else uint8_t scales[K_SCALE_SIZE]; // scales, quantized with 6 bits #endif half d; // super-block scale } block_q3_K; #if QK_K == 64 typedef struct { half d[2]; // super-block scales/mins uint8_t scales[2]; uint8_t qs[QK_K/2]; // 4-bit quants } block_q4_K; #else typedef struct { half d; // super-block scale for quantized scales half dmin; // super-block scale for quantized mins uint8_t scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits uint8_t qs[QK_K/2]; // 4--bit quants } block_q4_K; #endif #if QK_K == 64 typedef struct { half d; // super-block scales/mins int8_t scales[QK_K/16]; // 8-bit block scales uint8_t qh[QK_K/8]; // quants, high bit uint8_t qs[QK_K/2]; // quants, low 4 bits } block_q5_K; #else typedef struct { half d; // super-block scale for quantized scales half dmin; // super-block scale for quantized mins uint8_t scales[3*QK_K/64]; // scales and mins, quantized with 6 bits uint8_t qh[QK_K/8]; // quants, high bit uint8_t qs[QK_K/2]; // quants, low 4 bits } block_q5_K; // 176 bytes / block #endif typedef struct { uint8_t ql[QK_K/2]; // quants, lower 4 bits uint8_t qh[QK_K/4]; // quants, upper 2 bits int8_t scales[QK_K/16]; // scales, quantized with 8 bits half d; // super-block scale } block_q6_K; // 210 bytes / block static inline uchar4 get_scale_min_k4(int j, device const uint8_t * q) { uchar4 r; if (j < 4) { r[0] = q[j+0] & 63; r[2] = q[j+1] & 63; r[1] = q[j+4] & 63; r[3] = q[j+5] & 63; } else { r[0] = (q[j+4] & 0xF) | ((q[j-4] >> 6) << 4); r[2] = (q[j+5] & 0xF) | ((q[j-3] >> 6) << 4); r[1] = (q[j+4] >> 4) | ((q[j-0] >> 6) << 4); r[3] = (q[j+5] >> 4) | ((q[j+1] >> 6) << 4); } return r; } //====================================== dot products ========================= kernel void kernel_mul_mat_q2_K_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const int nb = ne00/QK_K; const int r0 = tgpig.x; const int r1 = tgpig.y; const int r2 = tgpig.z; const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST; const int ib_row = first_row * nb; const uint offset0 = r2/gqa*(nb*ne0); device const block_q2_K * x = (device const block_q2_K *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + r2*ne00*ne1; float yl[32]; float sumf[N_DST]={0.f}, all_sum; const int step = sizeof(block_q2_K) * nb; #if QK_K == 256 const int ix = tiisg/8; // 0...3 const int it = tiisg%8; // 0...7 const int im = 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 * im + 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*im + is; device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 16 * im + 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 += step/2; sc += step; dh += step/2; } y4 += 4 * QK_K; } #else const int ix = tiisg/2; // 0...15 const int it = tiisg%2; // 0...1 device const float * y4 = y + ix * QK_K + 8 * it; for (int ib = ix; ib < nb; ib += 16) { 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+16]; sumy[1] += yl[i+ 8]; yl[i+16] = y4[i+32]; sumy[2] += yl[i+16]; yl[i+24] = y4[i+48]; sumy[3] += yl[i+24]; } device const uint8_t * sc = (device const uint8_t *)x[ib].scales; device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 4 * it; 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]; 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[1] & 0xF) * 1.f/ 4.f + (acc1[2] + 1.f/256.f * acc2[2]) * (sc[2] & 0xF) * 1.f/16.f + (acc1[3] + 1.f/256.f * acc2[3]) * (sc[3] & 0xF) * 1.f/64.f) - dmin * (sumy[0] * (sc[0] >> 4) + sumy[1] * (sc[1] >> 4) + sumy[2] * (sc[2] >> 4) + sumy[3] * (sc[3] >> 4)); qs += step/2; sc += step; dh += step/2; } y4 += 16 * QK_K; } #endif for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + r2*ne0*ne1 + first_row + row] = all_sum; } } } #if QK_K == 256 kernel void kernel_mul_mat_q3_K_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const int nb = ne00/QK_K; const int64_t r0 = tgpig.x; const int64_t r1 = tgpig.y; const int64_t r2 = tgpig.z; const int first_row = (r0 * N_SIMDGROUP + sgitg) * 2; const uint offset0 = r2/gqa*(nb*ne0); device const block_q3_K * x = (device const block_q3_K *) src0 + first_row*nb + offset0; device const float * yy = (device const float *) src1 + r1*ne10 + r2*ne00*ne1; 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 int 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; const int step = sizeof(block_q3_K) * nb / 2; 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 += step; h += step; a += step; dh += step; } 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); } if (tiisg == 0) { for (int row = 0; row < 2; ++row) { dst[r1*ne0 + r2*ne0*ne1 + first_row + row] = sumf1[row]; } } } #else kernel void kernel_mul_mat_q3_K_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const int nb = ne00/QK_K; const int64_t r0 = tgpig.x; const int64_t r1 = tgpig.y; const int64_t r2 = tgpig.z; const int row = 2 * r0 + sgitg; const uint offset0 = r2/gqa*(nb*ne0); device const block_q3_K * x = (device const block_q3_K *) src0 + row*nb + offset0; device const float * yy = (device const float *) src1 + r1*ne10 + r2*ne00*ne1; const int ix = tiisg/4; const int il = 4 * (tiisg%4);// 0, 4, 8, 12 const int im = il/8; // 0, 0, 1, 1 const int in = il%8; // 0, 4, 0, 4 float2 sum = {0.f, 0.f}; for (int i = ix; i < nb; i += 8) { const float d_all = (float)(x[i].d); device const uint16_t * q = (device const uint16_t *)(x[i].qs + il); device const uint16_t * h = (device const uint16_t *)(x[i].hmask + in); device const uint16_t * s = (device const uint16_t *)(x[i].scales); device const float * y = yy + i * QK_K + il; const float d1 = d_all * ((int32_t)(s[0] & 0x000F) - 8); const float d2 = d_all * ((int32_t)(s[0] & 0x00F0) - 128) * 1.f/64.f; const float d3 = d_all * ((int32_t)(s[0] & 0x0F00) - 2048) * 1.f/4096.f; const float d4 = d_all * ((int32_t)(s[0] & 0xF000) - 32768) * 1.f/262144.f; for (int l = 0; l < 4; l += 2) { const uint16_t hm = h[l/2] >> im; sum[0] += y[l+ 0] * d1 * ((int32_t)(q[l/2] & 0x0003) - ((hm & 0x0001) ? 0 : 4)) + y[l+16] * d2 * ((int32_t)(q[l/2] & 0x000c) - ((hm & 0x0004) ? 0 : 16)) + y[l+32] * d3 * ((int32_t)(q[l/2] & 0x0030) - ((hm & 0x0010) ? 0 : 64)) + y[l+48] * d4 * ((int32_t)(q[l/2] & 0x00c0) - ((hm & 0x0040) ? 0 : 256)); sum[1] += y[l+ 1] * d1 * ((int32_t)(q[l/2] & 0x0300) - ((hm & 0x0100) ? 0 : 1024)) + y[l+17] * d2 * ((int32_t)(q[l/2] & 0x0c00) - ((hm & 0x0400) ? 0 : 4096)) + y[l+33] * d3 * ((int32_t)(q[l/2] & 0x3000) - ((hm & 0x1000) ? 0 : 16384)) + y[l+49] * d4 * ((int32_t)(q[l/2] & 0xc000) - ((hm & 0x4000) ? 0 : 65536)); } } const float sumf = sum[0] + sum[1] * 1.f/256.f; const float tot = simd_sum(sumf); if (tiisg == 0) { dst[r1*ne0 + r2*ne0*ne1 + row] = tot; } } #endif #if QK_K == 256 kernel void kernel_mul_mat_q4_K_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { 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 im = it/4; // 0 or 1 const int ir = it%4; // 0...3 const int nb = ne00/QK_K; const int r0 = tgpig.x; const int r1 = tgpig.y; const int r2 = tgpig.z; //const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST; const int first_row = r0 * N_DST; const int ib_row = first_row * nb; const uint offset0 = r2/gqa*(nb*ne0); device const block_q4_K * x = (device const block_q4_K *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + r2*ne00*ne1; float yl[16]; float yh[16]; float sumf[N_DST]={0.f}, all_sum; const int step = sizeof(block_q4_K) * nb / 2; device const float * y4 = y + ix * QK_K + 64 * im + 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 + im; device const uint16_t * q1 = (device const uint16_t *)x[ib].qs + 16 * im + 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 += step; sc += step; dh += step; } y4 += 4 * QK_K; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + r2*ne0*ne1 + first_row + row] = all_sum; } } } #else kernel void kernel_mul_mat_q4_K_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const int ix = tiisg/4; // 0...7 const int it = tiisg%4; // 0...3 const int nb = ne00/QK_K; const int r0 = tgpig.x; const int r1 = tgpig.y; const int r2 = tgpig.z; const int first_row = (r0 * N_SIMDGROUP + sgitg) * N_DST; const int ib_row = first_row * nb; const uint offset0 = r2/gqa*(nb*ne0); device const block_q4_K * x = (device const block_q4_K *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + r2*ne00*ne1; float yl[8]; float yh[8]; float sumf[N_DST]={0.f}, all_sum; const int step = sizeof(block_q4_K) * nb / 2; device const float * y4 = y + ix * QK_K + 8 * it; uint16_t sc16[4]; for (int ib = ix; ib < nb; ib += 8) { float2 sumy = {0.f, 0.f}; for (int i = 0; i < 8; ++i) { yl[i] = y4[i+ 0]; sumy[0] += yl[i]; yh[i] = y4[i+32]; sumy[1] += yh[i]; } device const uint16_t * sc = (device const uint16_t *)x[ib].scales; device const uint16_t * qs = (device const uint16_t *)x[ib].qs + 4 * it; device const half * dh = x[ib].d; for (int row = 0; row < N_DST; row++) { sc16[0] = sc[0] & 0x000f; sc16[1] = sc[0] & 0x0f00; sc16[2] = sc[0] & 0x00f0; sc16[3] = sc[0] & 0xf000; float2 acc1 = {0.f, 0.f}; float2 acc2 = {0.f, 0.f}; for (int i = 0; i < 8; i += 2) { acc1[0] += yl[i+0] * (qs[i/2] & 0x000F); acc1[1] += yl[i+1] * (qs[i/2] & 0x0F00); acc2[0] += yh[i+0] * (qs[i/2] & 0x00F0); acc2[1] += yh[i+1] * (qs[i/2] & 0xF000); } float dall = dh[0]; float dmin = dh[1]; sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc1[1]) * sc16[0] + (acc2[0] + 1.f/256.f * acc2[1]) * sc16[1] * 1.f/4096.f) - dmin * 1.f/16.f * (sumy[0] * sc16[2] + sumy[1] * sc16[3] * 1.f/256.f); qs += step; sc += step; dh += step; } y4 += 8 * QK_K; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0+ r2*ne0*ne1 + first_row + row] = all_sum; } } } #endif kernel void kernel_mul_mat_q5_K_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const int nb = ne00/QK_K; const int64_t r0 = tgpig.x; const int64_t r1 = tgpig.y; const int r2 = tgpig.z; const int first_row = (r0 * N_SIMDGROUP + sgitg) * 2; const uint offset0 = r2/gqa*(nb*ne0); device const block_q5_K * x = (device const block_q5_K *) src0 + first_row*nb + offset0; device const float * yy = (device const float *) src1 + r1*ne10 + r2*ne00*ne1; float sumf[2]={0.f}; const int step = sizeof(block_q5_K) * nb; #if QK_K == 256 # 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 im = tid/4; const int ir = tid%4; const int n = 8; const int l0 = n*ir; const int q_offset = 32*im + l0; const int y_offset = 64*im + l0; const uint8_t hm1 = 1u << (2*im); 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 + im; 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 += step; qh += step; dh += step/2; a += step/2; } y1 += 4 * QK_K; } #else float yl[8], yh[8]; const int il = 4 * (tiisg/8); // 0, 4, 8, 12 const int ix = tiisg%8; const int im = il/8; // 0, 0, 1, 1 const int in = il%8; // 0, 4, 0, 4 device const float * y = yy + ix*QK_K + il; for (int i = ix; i < nb; i += 8) { for (int l = 0; l < 4; ++l) { yl[l+0] = y[l+ 0]; yl[l+4] = y[l+16]; yh[l+0] = y[l+32]; yh[l+4] = y[l+48]; } device const half * dh = &x[i].d; device const uint8_t * q = x[i].qs + il; device const uint8_t * h = x[i].qh + in; device const int8_t * s = x[i].scales; for (int row = 0; row < 2; ++row) { const float d = dh[0]; float2 acc = {0.f, 0.f}; for (int l = 0; l < 4; ++l) { const uint8_t hl = h[l] >> im; acc[0] += yl[l+0] * s[0] * ((int16_t)(q[l+ 0] & 0x0F) - (hl & 0x01 ? 0 : 16)) + yl[l+4] * s[1] * ((int16_t)(q[l+16] & 0x0F) - (hl & 0x04 ? 0 : 16)); acc[1] += yh[l+0] * s[2] * ((int16_t)(q[l+ 0] & 0xF0) - (hl & 0x10 ? 0 : 256)) + yh[l+4] * s[3] * ((int16_t)(q[l+16] & 0xF0) - (hl & 0x40 ? 0 : 256)); } sumf[row] += d * (acc[0] + 1.f/16.f * acc[1]); q += step; h += step; s += step; dh += step/2; } y += 8 * QK_K; } #endif for (int row = 0; row < 2; ++row) { const float tot = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + r2*ne0*ne1 + first_row + row] = tot; } } } kernel void kernel_mul_mat_q6_K_f32( device const void * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne01[[buffer(4)]], constant int64_t & ne02[[buffer(5)]], constant int64_t & ne10[[buffer(9)]], constant int64_t & ne12[[buffer(11)]], constant int64_t & ne0[[buffer(15)]], constant int64_t & ne1[[buffer(16)]], constant uint & gqa[[buffer(17)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const uint8_t kmask1 = 0x03; const uint8_t kmask2 = 0x0C; const uint8_t kmask3 = 0x30; const uint8_t kmask4 = 0xC0; const int nb = ne00/QK_K; const int64_t r0 = tgpig.x; const int64_t r1 = tgpig.y; const int r2 = tgpig.z; const int row = 2 * r0 + sgitg; const uint offset0 = r2/gqa*(nb*ne0); device const block_q6_K * x = (device const block_q6_K *) src0 + row * nb + offset0; device const float * yy = (device const float *) src1 + r1*ne10 + r2*ne00*ne1; float sumf = 0; #if QK_K == 256 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]); } #else const int ix = tiisg/4; const int il = 4*(tiisg%4); for (int i = ix; i < nb; i += 8) { device const float * y = yy + i * QK_K + il; device const uint8_t * ql = x[i].ql + il; device const uint8_t * qh = x[i].qh + il; device const int8_t * s = x[i].scales; const float d = x[i].d; float4 sums = {0.f, 0.f, 0.f, 0.f}; for (int l = 0; l < 4; ++l) { sums[0] += y[l+ 0] * ((int8_t)((ql[l+ 0] & 0xF) | ((qh[l] & kmask1) << 4)) - 32); sums[1] += y[l+16] * ((int8_t)((ql[l+16] & 0xF) | ((qh[l] & kmask2) << 2)) - 32); sums[2] += y[l+32] * ((int8_t)((ql[l+ 0] >> 4) | ((qh[l] & kmask3) >> 0)) - 32); sums[3] += y[l+48] * ((int8_t)((ql[l+16] >> 4) | ((qh[l] & kmask4) >> 2)) - 32); } sumf += d * (sums[0] * s[0] + sums[1] * s[1] + sums[2] * s[2] + sums[3] * s[3]); } #endif const float tot = simd_sum(sumf); if (tiisg == 0) { dst[r1*ne0 + r2*ne0*ne1 + row] = tot; } } //============================= templates and their specializations ============================= template void dequantize_f16(device const half4x4 * src, short il, thread type4x4 & reg) { half4x4 temp = *(((device half4x4 *)src)); for (int i = 0; i < 16; i++){ reg[i/4][i%4] = temp[i/4][i%4]; } } template 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; for (int i=0;i<8;i++) { reg[i/2][2*(i%2)+0] = d1 * (qs[i] & mask0) + md; reg[i/2][2*(i%2)+1] = d2 * (qs[i] & mask1) + md; } } template 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; for (int i=0;i<8;i++) { reg[i/2][2*(i%2)+0] = ((qs[i] & mask0) * d1) + m; reg[i/2][2*(i%2)+1] = ((qs[i] & mask1) * d2) + m; } } template 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; for (int i=0;i<16;i++) { reg[i/4][i%4] = (qs[i + 16*il] * d); } } template void dequantize_q2_K(device const block_q2_K *xb, short il, thread type4x4 & reg) { const half d = xb->d; const half min = xb->dmin; device const uint8_t * q = (device const uint8_t *)xb->qs; half dl, ml; uint8_t sc = xb->scales[il]; #if QK_K == 256 q = q + 32*(il/8) + 16*(il&1); il = (il/2)%4; #endif 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 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; #if QK_K == 256 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); half dl = il<8 ? d_all * (dl_int - 32.h) : d_all * (dl_int / 16.h - 32.h); const half ml = 4.h * 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); } #else float kcoef = il&1 ? 1.f/16.f : 1.f; uint16_t kmask = il&1 ? 0xF0 : 0x0F; float dl = d_all * ((scales[il/2] & kmask) * kcoef - 8); float coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h); uint8_t mask = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3); uint8_t m = 1<<(il*2); for (int i = 0; i < 16; ++i) { reg[i/4][i%4] = coef * dl * ((q[i] & mask) - ((h[i%8] & (m * (1 + i/8))) ? 0 : 4.f/coef)); } #endif } 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 void dequantize_q4_K(device const block_q4_K *xb, short il, thread type4x4 & reg) { device const uchar * q = xb->qs; #if QK_K == 256 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 half d = il < 2 ? xb->d : xb->d / 16.h; const half min = xb->dmin; const half dl = d * sc[0]; const half ml = min * sc[1]; #else q = q + 16 * (il&1); device const uint8_t * s = xb->scales; device const half2 * dh = (device const half2 *)xb->d; const float2 d = (float2)dh[0]; const float dl = il<2 ? d[0] * (s[0]&0xF) : d[0] * (s[1]&0xF)/16.h; const float ml = il<2 ? d[1] * (s[0]>>4) : d[1] * (s[1]>>4); #endif 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 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; #if QK_K == 256 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 half d = il < 2 ? xb->d : xb->d / 16.h; const half min = xb->dmin; const half dl = d * sc[0]; const half ml = min * sc[1]; const ushort mask = il<2 ? 0x0F : 0xF0; const half qh_val = il<2 ? 16.h : 256.h; for (int i = 0; i < 16; ++i) { reg[i/4][i%4] = dl * ((q[i] & mask) + (qh[i] & ul ? qh_val : 0)) - ml; } #else q = q + 16 * (il&1); device const int8_t * s = xb->scales; const float dl = xb->d * s[il]; uint8_t m = 1<<(il*2); const float coef = il<2 ? 1.f : 1.f/16.f; const ushort mask = il<2 ? 0x0F : 0xF0; for (int i = 0; i < 16; ++i) { reg[i/4][i%4] = coef * dl * ((q[i] & mask) - (qh[i%8] & (m*(1+i/8)) ? 0.f : 16.f/coef)); } #endif } template 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; #if QK_K == 256 ql = ql + 64*(il/8) + 32*((il/2)&1) + 16*(il&1); qh = qh + 32*(il/8) + 16*(il&1); half sc = scales[(il%2) + 2 * ((il/2))]; il = (il/2) & 3; #else ql = ql + 16 * (il&1); half sc = scales[il]; #endif const uint16_t kmask1 = il>1 ? (il>2 ? 192 : 48) : (il>0 ? 12 : 3); const uint16_t kmask2 = il>1 ? 0xF0 : 0x0F; const half coef = il>1 ? 1.f/16.h : 1.h; const half ml = d_all * sc * 32.h; const half 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 kernel void kernel_get_rows( device const void * src0, device const int * src1, device float * dst, constant int64_t & ne00, constant uint64_t & nb01, constant uint64_t & nb1, uint tgpig[[threadgroup_position_in_grid]], uint tiitg[[thread_index_in_threadgroup]], uint tptg[[threads_per_threadgroup]]) { const int i = tgpig; const int r = ((device int32_t *) src1)[i]; for (int ind = tiitg; ind < ne00/16; ind += tptg) { float4x4 temp; dequantize_func( ((device const block_q *) ((device char *) src0 + r*nb01)) + ind/nl, ind%nl, temp); *(((device float4x4 *) ((device char *) dst + i*nb1)) + ind) = temp; } } #define BLOCK_SIZE_M 64 // 8 simdgroup matrices from matrix A #define BLOCK_SIZE_N 32 // 4 simdgroup matrices from matrix A #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 kernel void kernel_mul_mm(device const uchar * src0, device const float * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne02, constant int64_t & nb01, constant int64_t & nb02, constant int64_t & ne12, constant int64_t & ne0, constant int64_t & ne1, constant uint & gqa, threadgroup uchar * shared_memory [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiitg[[thread_index_in_threadgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { threadgroup half * sa = ((threadgroup half *)shared_memory); threadgroup float * sb = (threadgroup float *)(shared_memory + 4096); const uint r0 = tgpig.y; const uint r1 = tgpig.x; 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; // 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 c_res[8]; for (int i = 0; i < 8; i++){ c_res[i] = make_filled_simdgroup_matrix(0.f); } short il = (tiitg % THREAD_PER_ROW); uint offset0 = im/gqa*nb02; 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 float * y = src1 + (r1 * BLOCK_SIZE_N + thread_col) * ne00 \ + BLOCK_SIZE_K / THREAD_PER_COL * (tiitg % THREAD_PER_COL) + im * ne00 * ne1; 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); #pragma unroll(16) for (int i = 0; i < 16; i++) { *(sa + SG_MAT_SIZE * ((tiitg / THREAD_PER_ROW / 8) \ + 16 * (tiitg % THREAD_PER_ROW) + 8 * (i / 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(4) 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(c_res[i], mb[i/4], ma[i%4], c_res[i]); } } } 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); } } 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_barrier(mem_flags::mem_threadgroup); device float *C = dst + BLOCK_SIZE_M * r0 + (BLOCK_SIZE_N * r1) * ne0 + im*ne1*ne0; if (sgitg==0) { for (int i = 0; i < n_rows; i++) { for (int j = tiitg; j< n_cols; j += BLOCK_SIZE_N) { *(C + i + j * ne0) = *(temp_str + i + j * BLOCK_SIZE_M); } } } } } #if QK_K == 256 #define QK_NL 16 #else #define QK_NL 4 #endif typedef void (get_rows_t)(device const void *, device const int *, device float *, constant int64_t &, \ constant uint64_t &, constant uint64_t &, uint, uint, uint); template [[host_name("kernel_get_rows_f16")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q4_0")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q4_1")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q8_0")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q2_K")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q3_K")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q4_K")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q5_K")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q6_K")]] kernel get_rows_t kernel_get_rows; typedef void (mat_mm_t)(device const uchar *, device const float *, device float *, constant int64_t &,\ constant int64_t &, constant int64_t &, constant int64_t &, constant int64_t &, \ constant int64_t &, constant int64_t &, constant uint &, threadgroup uchar *, uint3, uint, uint); template [[host_name("kernel_mul_mm_f16_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q4_0_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q4_1_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q8_0_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q2_K_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q3_K_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q4_K_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q5_K_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q6_K_f32")]] kernel mat_mm_t kernel_mul_mm;