#define GGML_COMMON_DECL_METAL #define GGML_COMMON_IMPL_METAL #include "ggml-common.h" #include 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 enum ggml_sort_order { GGML_SORT_ORDER_ASC, GGML_SORT_ORDER_DESC, }; // general-purpose kernel for addition, 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( device const char * src0, device const char * src1, 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 & 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, constant int64_t & offs, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { const int64_t i03 = tgpig.z; const int64_t i02 = tgpig.y; const int64_t i01 = tgpig.x; const int64_t i13 = i03 % ne13; const int64_t i12 = i02 % ne12; const int64_t i11 = i01 % ne11; device const char * src0_ptr = src0 + i03*nb03 + i02*nb02 + i01*nb01 + offs; device const char * src1_ptr = src1 + i13*nb13 + i12*nb12 + i11*nb11; device char * dst_ptr = dst + i03*nb3 + i02*nb2 + i01*nb1 + offs; for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) { const int i10 = i0 % ne10; *((device float *)(dst_ptr + i0*nb0)) = *((device float *)(src0_ptr + i0*nb00)) + *((device float *)(src1_ptr + i10*nb10)); } } kernel void kernel_mul( device const char * src0, device const char * src1, 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 & 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 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { const int64_t i03 = tgpig.z; const int64_t i02 = tgpig.y; const int64_t i01 = tgpig.x; const int64_t i13 = i03 % ne13; const int64_t i12 = i02 % ne12; const int64_t i11 = i01 % ne11; device const char * src0_ptr = src0 + i03*nb03 + i02*nb02 + i01*nb01; device const char * src1_ptr = src1 + i13*nb13 + i12*nb12 + i11*nb11; device char * dst_ptr = dst + i03*nb3 + i02*nb2 + i01*nb1; for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) { const int i10 = i0 % ne10; *((device float *)(dst_ptr + i0*nb0)) = *((device float *)(src0_ptr + i0*nb00)) * *((device float *)(src1_ptr + i10*nb10)); } } kernel void kernel_div( device const char * src0, device const char * src1, 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 & 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 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { const int64_t i03 = tgpig.z; const int64_t i02 = tgpig.y; const int64_t i01 = tgpig.x; const int64_t i13 = i03 % ne13; const int64_t i12 = i02 % ne12; const int64_t i11 = i01 % ne11; device const char * src0_ptr = src0 + i03*nb03 + i02*nb02 + i01*nb01; device const char * src1_ptr = src1 + i13*nb13 + i12*nb12 + i11*nb11; device char * dst_ptr = dst + i03*nb3 + i02*nb2 + i01*nb1; for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) { const int i10 = i0 % ne10; *((device float *)(dst_ptr + i0*nb0)) = *((device float *)(src0_ptr + i0*nb00)) / *((device float *)(src1_ptr + i10*nb10)); } } // 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 uint64_t & nb [[buffer(28)]], uint tpig[[thread_position_in_grid]]) { dst[tpig] = src0[tpig] + src1[tpig % nb]; } kernel void kernel_mul_row( device const float4 * src0, device const float4 * src1, device float4 * dst, constant uint64_t & nb [[buffer(28)]], uint tpig[[thread_position_in_grid]]) { dst[tpig] = src0[tpig] * src1[tpig % nb]; } kernel void kernel_div_row( device const float4 * src0, device const float4 * src1, device float4 * dst, constant uint64_t & nb [[buffer(28)]], uint tpig[[thread_position_in_grid]]) { 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_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 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 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) kernel_soft_max_t; typedef decltype(kernel_soft_max_4) kernel_soft_max_4_t; template [[host_name("kernel_soft_max_f16")]] kernel kernel_soft_max_t kernel_soft_max; template [[host_name("kernel_soft_max_f32")]] kernel kernel_soft_max_t kernel_soft_max; template [[host_name("kernel_soft_max_f16_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4; template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4; 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 * 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]]) { device const float4 * x = (device const float4 *) ((device const char *) src0 + tgpig*nb01); 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 (ntg > N_SIMDWIDTH) { if (sgitg == 0) { buf[tiisg] = 0.0f; } threadgroup_barrier(mem_flags::mem_threadgroup); if (tiisg == 0) { buf[sgitg] = all_sum; } threadgroup_barrier(mem_flags::mem_threadgroup); all_sum = buf[tiisg]; all_sum = simd_sum(all_sum); } const float mean = all_sum/ne00; const float scale = 1.0f/sqrt(mean + eps); device float4 * y = (device float4 *) (dst + tgpig*ne00); for (int i00 = tpitg; i00 < 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; 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; float2 acc = 0.f; 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) + 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; } // 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; float2 acc = 0.f; 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)) + yl[i + 1] * ((qs[i / 2] & 0x0F00) | ((qh >> (i+1+il ) << 12) & 0x01000)); acc[1] += yl[i + 8] * ((qs[i / 2] & 0x00F0) | ((qh >> (i+0+il+QK5_0/2) << 8 ) & 0x00100)) + 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]); } // 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; float2 acc = 0.f; 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)) + yl[i + 1] * ((qs[i / 2] & 0x0F00) | ((qh >> (i+1+il ) << 12) & 0x01000)); acc[1] += yl[i + 8] * ((qs[i / 2] & 0x00F0) | ((qh >> (i+0+il+QK5_0/2) << 8 ) & 0x00100)) + yl[i + 9] * ((qs[i / 2] & 0xF000) | ((qh >> (i+1+il+QK5_0/2) << 16) & 0x10000)); } 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 //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 void mul_vec_q_n_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, 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 i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = first_row * nb + (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); 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 = (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 = 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[im*ne0*ne1 + r1*ne0 + first_row + row] = tot; } } } kernel void kernel_mul_mv_q4_0_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { mul_vec_q_n_f32_impl(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,nullptr,tgpig,tiisg,sgitg); } kernel void kernel_mul_mv_q4_1_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { mul_vec_q_n_f32_impl(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,nullptr,tgpig,tiisg,sgitg); } kernel void kernel_mul_mv_q5_0_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { mul_vec_q_n_f32_impl(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,nullptr,tgpig,tiisg,sgitg); } kernel void kernel_mul_mv_q5_1_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { mul_vec_q_n_f32_impl(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,nullptr,tgpig,tiisg,sgitg); } #define NB_Q8_0 8 void kernel_mul_mv_q8_0_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { 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 i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = first_row * nb + (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); 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; } } } [[host_name("kernel_mul_mv_q8_0_f32")]] kernel void kernel_mul_mv_q8_0_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_q8_0_f32_impl(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,nullptr,tgpig,tiisg,sgitg); } #define N_F32_F32 4 void kernel_mul_mv_f32_f32_impl( device const char * src0, device const char * src1, device float * dst, int64_t ne00, int64_t ne01, int64_t ne02, uint64_t nb00, uint64_t nb01, uint64_t nb02, int64_t ne10, int64_t ne11, int64_t ne12, uint64_t nb10, uint64_t nb11, uint64_t nb12, int64_t ne0, int64_t ne1, uint r2, uint r3, uint3 tgpig, uint tiisg) { const int64_t r0 = tgpig.x; const int64_t rb = tgpig.y*N_F32_F32; const int64_t im = tgpig.z; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02; device const float * x = (device const float *) (src0 + offset0); if (ne00 < 128) { for (int row = 0; row < N_F32_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 float4 * x4 = (device const float4 *)x; for (int row = 0; row < N_F32_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; } } } } [[host_name("kernel_mul_mv_f32_f32")]] kernel void kernel_mul_mv_f32_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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]]) { kernel_mul_mv_f32_f32_impl(src0, src1, dst, ne00, ne01, ne02, nb00, nb01, nb02, ne10, ne11, ne12, nb10, nb11, nb12, ne0, ne1, r2, r3, tgpig, tiisg); } #define N_F16_F16 4 kernel void kernel_mul_mv_f16_f16( 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, constant uint & r2, constant uint & r3, 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_F16; const int64_t im = tgpig.z; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02; device const half * x = (device const half *) (src0 + offset0); if (ne00 < 128) { for (int row = 0; row < N_F16_F16; ++row) { int r1 = rb + row; if (r1 >= ne11) { break; } device const half * y = (device const half *) (src1 + r1*nb11 + im*nb12); float sumf = 0; for (int i = tiisg; i < ne00; i += 32) { sumf += (half) x[i] * (half) 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_F16; ++row) { int r1 = rb + row; if (r1 >= ne11) { break; } device const half * y = (device const half *) (src1 + r1*nb11 + im*nb12); device const half4 * y4 = (device const half4 *) y; float sumf = 0; for (int i = tiisg; i < ne00/4; i += 32) { for (int k = 0; k < 4; ++k) sumf += (half) 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 += (half) x[i] * y[i]; dst[im*ne1*ne0 + r1*ne0 + r0] = all_sum; } } } } void kernel_mul_mv_f16_f32_1row_impl( 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, constant uint & r2, constant uint & r3, 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; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02; device const half * x = (device const half *) (src0 + offset0); 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; } } } [[host_name("kernel_mul_mv_f16_f32_1row")]] kernel void kernel_mul_mv_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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]]) { kernel_mul_mv_f16_f32_1row_impl(src0, src1, dst, ne00, ne01, ne02, nb00, nb01, nb02, ne10, ne11, ne12, nb10, nb11, nb12, ne0, ne1, r2, r3, tgpig, tiisg); } #define N_F16_F32 4 void kernel_mul_mv_f16_f32_impl( device const char * src0, device const char * src1, device float * dst, int64_t ne00, int64_t ne01, int64_t ne02, uint64_t nb00, uint64_t nb01, uint64_t nb02, int64_t ne10, int64_t ne11, int64_t ne12, uint64_t nb10, uint64_t nb11, uint64_t nb12, int64_t ne0, int64_t ne1, uint r2, uint r3, uint3 tgpig, uint tiisg) { const int64_t r0 = tgpig.x; const int64_t rb = tgpig.y*N_F16_F32; const int64_t im = tgpig.z; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02; device const half * x = (device const half *) (src0 + offset0); 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; } } } } [[host_name("kernel_mul_mv_f16_f32")]] kernel void kernel_mul_mv_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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]]) { kernel_mul_mv_f16_f32_impl(src0, src1, dst, ne00, ne01, ne02, nb00, nb01, nb02, ne10, ne11, ne12, nb10, nb11, nb12, ne0, ne1, r2, r3, tgpig, tiisg); } // Assumes row size (ne00) is a multiple of 4 kernel void kernel_mul_mv_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, constant uint & r2, constant uint & r3, 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; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = r0*nb01 + (i12/r2)*nb02 + (i13/r3)*nb02*ne02; device const half4 * x4 = (device const half4 *) (src0 + offset0); 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; } } } 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], int64_t 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_orig_ctx, float n_rot, float base) { return n_dims * log(n_orig_ctx / (n_rot * 2 * M_PI_F)) / (2 * log(base)); } static void rope_yarn_corr_dims( int n_dims, int n_orig_ctx, 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_orig_ctx, beta_fast, freq_base))); dims[1] = min(n_dims - 1.0f, ceil(rope_yarn_corr_factor(n_dims, n_orig_ctx, beta_slow, freq_base))); } typedef void (rope_t)( device const void * src0, device const int32_t * src1, device const float * src2, 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 int & n_orig_ctx, constant float & freq_base, constant float & freq_scale, constant float & ext_factor, constant float & attn_factor, constant float & beta_fast, constant float & beta_slow, uint tiitg[[thread_index_in_threadgroup]], uint3 tptg[[threads_per_threadgroup]], uint3 tgpig[[threadgroup_position_in_grid]]); template kernel void kernel_rope( device const void * src0, device const int32_t * src1, device const float * src2, 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 int & n_orig_ctx, constant float & freq_base, constant float & freq_scale, constant float & ext_factor, constant float & attn_factor, constant float & beta_fast, constant float & beta_slow, 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; float corr_dims[2]; rope_yarn_corr_dims(n_dims, n_orig_ctx, freq_base, beta_fast, beta_slow, corr_dims); device const int32_t * pos = src1; const int64_t p = pos[i2]; const float theta_0 = (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); float cos_theta, sin_theta; rope_yarn(theta, freq_scale, corr_dims, i0, ext_factor, attn_factor, &cos_theta, &sin_theta); device const T * const src = (device T *)((device char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00); device T * dst_data = (device T *)((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); const T x0 = src[0]; const T 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 ic = 2*tiitg; ic < ne0; ic += 2*tptg.x) { if (ic < n_dims) { const int64_t ib = 0; // simplified from `(ib * n_dims + ic) * inv_ndims` const float cur_rot = inv_ndims*ic - ib; const float freq_factor = src2 != src0 ? src2[ic/2] : 1.0f; const float theta = theta_0 * pow(freq_base, cur_rot) / freq_factor; float cos_theta, sin_theta; rope_yarn(theta, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor, &cos_theta, &sin_theta); const int64_t i0 = ib*n_dims + ic/2; device const T * const src = (device T *)((device char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00); device T * dst_data = (device T *)((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; } else { const int64_t i0 = ic; device const T * const src = (device T *)((device char *) src0 + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00); device T * dst_data = (device T *)((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); dst_data[0] = src[0]; dst_data[1] = src[1]; } } } } template [[host_name("kernel_rope_f32")]] kernel rope_t kernel_rope; template [[host_name("kernel_rope_f16")]] kernel rope_t kernel_rope; 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 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; template [[host_name("kernel_im2col_f16")]] kernel im2col_t kernel_im2col; 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 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; template [[host_name("kernel_argsort_f32_i32_desc")]] kernel argsort_t kernel_argsort_f32_i32; 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; } typedef void (flash_attn_ext_f16_t)( device const char * q, device const char * k, device const char * v, device const char * mask, device float * dst, constant int64_t & ne01, constant int64_t & ne02, constant int64_t & ne03, constant uint64_t & nb01, constant uint64_t & nb02, constant uint64_t & nb03, constant int64_t & ne11, constant int64_t & ne12, constant int64_t & ne13, constant uint64_t & nb11, constant uint64_t & nb12, constant uint64_t & nb13, constant uint64_t & nb21, constant uint64_t & nb22, constant uint64_t & nb23, constant uint64_t & nb31, constant int64_t & ne1, constant int64_t & ne2, constant float & scale, constant float & max_bias, constant float & m0, constant float & m1, constant uint32_t & n_head_log2, threadgroup half * shared, uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]], ushort tiisg[[thread_index_in_simdgroup]], ushort sgitg[[simdgroup_index_in_threadgroup]]); // ref: https://arxiv.org/pdf/2307.08691.pdf template // head size, queries per threadgroup, cache items per threadgroup kernel void kernel_flash_attn_ext_f16( device const char * q, device const char * k, device const char * v, device const char * mask, device float * dst, constant int64_t & ne01, constant int64_t & ne02, constant int64_t & ne03, constant uint64_t & nb01, constant uint64_t & nb02, constant uint64_t & nb03, constant int64_t & ne11, constant int64_t & ne12, constant int64_t & ne13, constant uint64_t & nb11, constant uint64_t & nb12, constant uint64_t & nb13, constant uint64_t & nb21, constant uint64_t & nb22, constant uint64_t & nb23, constant uint64_t & nb31, constant int64_t & ne1, constant int64_t & ne2, constant float & scale, constant float & max_bias, constant float & m0, constant float & m1, constant uint32_t & n_head_log2, threadgroup half * shared [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 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 short iq3 = tgpig[2]; const short iq2 = tgpig[1]; const short iq1 = tgpig[0]*Q; const short D4 = D/4; const short D8 = D/8; //const short Q8 = Q/8; const short NW = N_SIMDWIDTH; const short SH = (C + Q); // shared memory per simdgroup in (half) const short T = D + 2*nsg*SH; // shared memory size per query in (half) const short TF = T/2; // shared memory size per query in (float) const short T4 = T/4; // shared memory size per query in (half4) threadgroup half * sq = (threadgroup half *) (shared + 0*D); // holds the query data threadgroup half4 * sq4 = (threadgroup half4 *) (shared + 0*D); // same as above but in half4 threadgroup float * ss = (threadgroup float *) (shared + 2*sgitg*SH + 1*D); // scratch buffer for attention and diagonal matrix // store the result for all queries in local memory in 8x8 matrices (the O matrix from the paper) simdgroup_half8x8 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)*nb01 + iq2*nb02 + iq3*nb03)); for (short i = tiisg; i < D4; i += NW) { if (iq1 + j < ne01) { sq4[j*T4 + i] = (half4) q4[i]; } else { sq4[j*T4 + i] = 0.0h; } } } // zero out lo for (short i = 0; i < D8; ++i) { lo[i] = make_filled_simdgroup_matrix(0.0h); } // zero out shared memory SH for (short j = 0; j < Q; ++j) { for (short i = tiisg; i < SH; i += NW) { ss[j*TF + i] = 0.0f; } } threadgroup_barrier(mem_flags::mem_threadgroup); { float S[Q] = { [0 ... Q-1] = 0.0h }; float M[Q] = { [0 ... Q-1] = -FLT_MAX/2 }; // assume K and V are same shape const short ne22 = ne12; const short ne23 = ne13; // broadcast const short rk2 = ne02/ne12; const short rk3 = ne03/ne13; const short rv2 = ne02/ne22; const short rv3 = ne03/ne23; // k indices const short ik2 = iq2/rk2; const short ik3 = iq3/rk3; // v indices const short iv2 = iq2/rv2; const short iv3 = iq3/rv3; // load the queries from shared memory into local memory simdgroup_half8x8 mq[D8]; for (short i = 0; i < D8; ++i) { simdgroup_load(mq[i], sq + i*8, T); } // pointer to the mask device const half * mp = (device const half *) (mask + iq1*nb31); float slope = 1.0f; // ALiBi if (max_bias > 0.0f) { const uint32_t h = iq2; const float base = h < n_head_log2 ? m0 : m1; const int exph = h < n_head_log2 ? h + 1 : 2*(h - 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 < ne11; ic0 += C*nsg) { const int ic = ic0 + C*sgitg; if (ic >= ne11) { break; } // Q*K^T { for (short cc = 0; cc < C/8; ++cc) { simdgroup_float8x8 mqk = make_filled_simdgroup_matrix(0.h); device const half * pk = (device const half *) ((device const char *) k + ((ic + 8*cc)*nb11 + ik2*nb12 + ik3*nb13)); for (short i = 0; i < D8; ++i) { simdgroup_half8x8 mk; simdgroup_load(mk, pk + i*8, nb11/sizeof(half), 0, true); // transpose simdgroup_multiply_accumulate(mqk, mq[i], mk, mqk); } simdgroup_store(mqk, ss + 8*cc, TF, 0, false); const short tx = tiisg%4; const short ty = tiisg/4; if (mask != q) { // mqk = mqk*scale + mask*slope ss[8*cc + ty*TF + 2*tx + 0] = scale*ss[8*cc + ty*TF + 2*tx + 0] + slope*mp[ic + 8*cc + ty*nb31/sizeof(half) + 2*tx + 0]; ss[8*cc + ty*TF + 2*tx + 1] = scale*ss[8*cc + ty*TF + 2*tx + 1] + slope*mp[ic + 8*cc + ty*nb31/sizeof(half) + 2*tx + 1]; } else { // mqk = mqk*scale ss[8*cc + ty*TF + 2*tx + 0] *= scale; ss[8*cc + ty*TF + 2*tx + 1] *= scale; } } } // used to detect blocks full of -INF float smax = -INFINITY; // online softmax { float ms[Q]; for (short j = 0; j < Q; ++j) { const short p = tiisg; const float m = M[j]; const float s = ss[j*TF + p]; smax = simd_max(max(smax, s)); M[j] = simd_max(max(M[j], s)); ms[j] = exp(m - M[j]); const float vs = exp(s - M[j]); S[j] = S[j]*ms[j] + simd_sum(vs); // the P matrix from the paper (Q rows, C columns) ss[j*TF + p] = vs; } // create a QxQ diagonal matrix for rescaling the output if (tiisg < Q) { ss[tiisg*TF + C + tiisg] = ms[tiisg]; } } // skip -INF blocks if (smax == -INFINITY) { continue; } // O = diag(ms)*O { simdgroup_float8x8 mm; simdgroup_load(mm, ss + C, TF, 0, false); 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) { device const half * pv = (device const half *) ((device const char *) v + ((ic + 8*cc)*nb21 + iv2*nb22 + iv3*nb23)); for (short i = 0; i < D8; ++i) { simdgroup_half8x8 mk; simdgroup_load(mk, pv + i*8, nb21/sizeof(half), 0, false); simdgroup_float8x8 mv; simdgroup_load(mv, ss + 8*cc, TF, 0, false); simdgroup_multiply_accumulate(lo[i], mv, mk, lo[i]); } } } } // 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*TF + 0] = S[j]; ss[j*TF + 1] = M[j]; } } } // reduce the warps sequentially for (short sg = 1; sg < nsg; ++sg) { float S = { 0.0h }; float M = { -FLT_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], sq + i*8, T, 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 float S0 = ss[j*TF + 0]; const float S1 = ss[j*TF + sg*SH + 0]; const float M0 = ss[j*TF + 1]; const float M1 = ss[j*TF + sg*SH + 1]; M = max(M0, M1); const float ms0 = exp(M0 - M); const float ms1 = exp(M1 - M); S = S0*ms0 + S1*ms1; if (tiisg == 0) { ss[j*TF + 0] = S; ss[j*TF + 1] = M; ss[j*TF + C + j ] = ms0; ss[j*TF + C + j + sg*SH] = ms1; } } // O_0 = diag(ms0)*O_0 + diag(ms1)*O_1 { simdgroup_half8x8 t; simdgroup_float8x8 ms0; simdgroup_float8x8 ms1; simdgroup_load(ms0, ss + C, TF, 0, false); simdgroup_load(ms1, ss + C + sg*SH, TF, 0, false); for (short i = 0; i < D8; ++i) { simdgroup_load (t, sq + i*8, T, 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], sq + i*8, T, 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 < ne01; ++j) { const float S = ss[j*TF + 0]; for (short i = tiisg; i < D4; i += NW) { dst4[(iq3*ne2*ne1 + iq2 + (iq1 + j)*ne1)*D4 + i] = (float4) sq4[j*T4 + i]/S; } } } } template [[host_name("kernel_flash_attn_ext_f16_h64" )]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_f16<64>; template [[host_name("kernel_flash_attn_ext_f16_h80" )]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_f16<80>; template [[host_name("kernel_flash_attn_ext_f16_h96" )]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_f16<96>; template [[host_name("kernel_flash_attn_ext_f16_h112")]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_f16<112>; template [[host_name("kernel_flash_attn_ext_f16_h128")]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_f16<128>; template [[host_name("kernel_flash_attn_ext_f16_h256")]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_f16<256>; template // head size, queries per threadgroup, cache items per threadgroup kernel void kernel_flash_attn_ext_vec_f16( device const char * q, device const char * k, device const char * v, device const char * mask, device float * dst, constant int64_t & ne01, constant int64_t & ne02, constant int64_t & ne03, constant uint64_t & nb01, constant uint64_t & nb02, constant uint64_t & nb03, constant int64_t & ne11, constant int64_t & ne12, constant int64_t & ne13, constant uint64_t & nb11, constant uint64_t & nb12, constant uint64_t & nb13, constant uint64_t & nb21, constant uint64_t & nb22, constant uint64_t & nb23, constant uint64_t & nb31, constant int64_t & ne1, constant int64_t & ne2, constant float & scale, constant float & max_bias, constant float & m0, constant float & m1, constant uint32_t & n_head_log2, threadgroup half * shared [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 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 short iq3 = tgpig[2]; const short iq2 = tgpig[1]; const short iq1 = tgpig[0]; const short D4 = D/4; const short NW = N_SIMDWIDTH; const short SH = (C + Q); // shared memory per simdgroup in (half) const short T = D + 2*nsg*SH; // shared memory size per query in (half) float slope = 1.0f; // ALiBi if (max_bias > 0.0f) { const uint32_t h = iq2; 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); } //threadgroup half * sq = (threadgroup half *) (shared + 0*D); // holds the query data threadgroup half4 * sq4 = (threadgroup half4 *) (shared + 0*D); // same as above but in half4 threadgroup float * ss = (threadgroup float *) (shared + 2*sgitg*SH + 1*D); // scratch buffer for attention and diagonal matrix threadgroup float4 * ss4 = (threadgroup float4 *) (shared + 2*sgitg*SH + 1*D); // same as above but in half4 threadgroup half4 * sr4 = (threadgroup half4 *) (shared + sgitg*D + 1*T); // scratch buffer for the results // store the result for all queries in local memory in 8x8 matrices (the O matrix from the paper) half4 lo[D4/NW]; // load heads from Q to shared memory device const float4 * q4 = (device const float4 *) ((device const char *) q + (iq1*nb01 + iq2*nb02 + iq3*nb03)); for (short i = tiisg; i < D4; i += NW) { if (iq1 < ne01) { sq4[i] = (half4) q4[i]; } else { sq4[i] = 0.0h; } } // zero out lo for (short i = tiisg; i < D4; i += NW) { lo[i/NW] = 0.0h; } // zero out shared memory SH for (short i = tiisg; i < SH/4; i += NW) { ss4[i] = 0.0h; } threadgroup_barrier(mem_flags::mem_threadgroup); { float S = { 0.0h }; float M = { -FLT_MAX/2 }; // assume K and V are same shape const short ne22 = ne12; const short ne23 = ne13; // broadcast const short rk2 = ne02/ne12; const short rk3 = ne03/ne13; const short rv2 = ne02/ne22; const short rv3 = ne03/ne23; // k indices const short ik2 = iq2 / rk2; const short ik3 = iq3 / rk3; // v indices const short iv2 = iq2 / rv2; const short iv3 = iq3 / rv3; // load the queries from shared memory into local memory half4 mq[D4]; for (short ii = 0; ii < D4; ii += NW) { short i = ii + tiisg; mq[i] = sq4[i]; } // pointer to the mask device const half4 * mp4 = (device const half4 *) (mask + iq1*nb31); // loop over the KV cache // each simdgroup handles blocks of Q rows and C columns for (int ic0 = 0; ic0 < ne11; ic0 += C*nsg) { const int ic = ic0 + C*sgitg; if (ic >= ne11) { break; } // Q*K^T { #pragma unroll for (short cc = 0; cc < C/4; ++cc) { float4 mqk = { 0.0h }; device const half4 * pk4 = (device const half4 *) ((device const char *) k + ((ic + 4*cc)*nb11 + ik2*nb12 + ik3*nb13)); #pragma unroll for (short ii = 0; ii < D4; ii += NW) { const short i = ii + tiisg; half4x4 mk; mk[0] = pk4[i + 0*(nb11/8)]; mk[1] = pk4[i + 1*(nb11/8)]; mk[2] = pk4[i + 2*(nb11/8)]; mk[3] = pk4[i + 3*(nb11/8)]; mqk += (float4) (mq[i] * mk); } // reduce the results from the threads in the simdgroup 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 (tiisg == 0) { mqk = mqk*scale + ((mask != q) ? ((float4) mp4[ic/4 + cc])*slope : (float4) 0.0f); ss4[cc] = mqk; } } } // online softmax { const short p = tiisg; const float m = M; const float s = ss[p]; M = simd_max(max(M, s)); const float ms = exp(m - M); const float vs = exp(s - M); S = S*ms + simd_sum(vs); // the P matrix from the paper (Q rows, C columns) ss[p] = vs; // O = diag(ms)*O #pragma unroll for (short ii = 0; ii < D4; ii += NW) { const short i = ii + tiisg; lo[i/NW] *= ms; } } // O = O + (Q*K^T)*V { #pragma unroll for (short cc = 0; cc < C/4; ++cc) { device const half4 * pv4 = (device const half4 *) ((device const char *) v + ((ic + 4*cc)*nb21 + iv2*nb22 + iv3*nb23)); #pragma unroll for (short ii = 0; ii < D4; ii += NW) { const short i = ii + tiisg; lo[i/NW] += pv4[i + 0*(nb21/8)] * ss[4*cc + 0]; lo[i/NW] += pv4[i + 1*(nb21/8)] * ss[4*cc + 1]; lo[i/NW] += pv4[i + 2*(nb21/8)] * ss[4*cc + 2]; lo[i/NW] += pv4[i + 3*(nb21/8)] * ss[4*cc + 3]; } } } } // these are needed for reducing the results from the simdgroups (reuse the ss buffer) if (tiisg == 0) { ss[0] = S; ss[1] = M; } } // store results to shared memory for (short ii = 0; ii < D4; ii += NW) { short i = ii + tiisg; sr4[i] = lo[ii/NW]; } threadgroup_barrier(mem_flags::mem_threadgroup); // parallel reduce for (short r = nsg/2; r > 0; r >>= 1) { if (sgitg < r) { const float S0 = ss[ 0]; const float S1 = ss[r*SH + 0]; const float M0 = ss[ 1]; const float M1 = ss[r*SH + 1]; const float M = max(M0, M1); const float ms0 = exp(M0 - M); const float ms1 = exp(M1 - M); const float 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 ii = 0; ii < D4; ii += NW) { short i = ii + tiisg; sr4[i] = sr4[i]*ms0 + sr4[i + r*D4]*ms1; } } threadgroup_barrier(mem_flags::mem_threadgroup); } device float4 * dst4 = (device float4 *) dst; // final rescale with 1/S and store to global memory if (sgitg == 0) { const float S = ss[0]; for (short ii = 0; ii < D4; ii += NW) { short i = ii + tiisg; dst4[(iq3*ne2*ne1 + iq2 + (iq1)*ne1)*D4 + i] = (float4) sr4[i]/S; } } } template [[host_name("kernel_flash_attn_ext_vec_f16_h128")]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_vec_f16<128>; template [[host_name("kernel_flash_attn_ext_vec_f16_h256")]] kernel flash_attn_ext_f16_t kernel_flash_attn_ext_vec_f16<256>; 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_f16_f32( device const half * 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 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]; } } kernel void kernel_cpy_f32_q8_0( device const float * src0, device void * 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)/QK8_0; device block_q8_0 * dst_data = (device block_q8_0 *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x*QK8_0; i00 < ne00; i00 += ntg.x*QK8_0) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*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( device const float * src0, device void * 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)/QK4_0; device block_q4_0 * dst_data = (device block_q4_0 *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x*QK4_0; i00 < ne00; i00 += ntg.x*QK4_0) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*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( device const float * src0, device void * 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)/QK4_1; device block_q4_1 * dst_data = (device block_q4_1 *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x*QK4_1; i00 < ne00; i00 += ntg.x*QK4_1) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*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( device const float * src0, device void * 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)/QK5_0; device block_q5_0 * dst_data = (device block_q5_0 *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x*QK5_0; i00 < ne00; i00 += ntg.x*QK5_0) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*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( device const float * src0, device void * 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)/QK5_1; device block_q5_1 * dst_data = (device block_q5_1 *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x*QK5_1; i00 < ne00; i00 += ntg.x*QK5_1) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*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; } 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 }; kernel void kernel_cpy_f32_iq4_nl( device const float * src0, device void * 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)/QK4_NL; device block_iq4_nl * dst_data = (device block_iq4_nl *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); for (int64_t i00 = tpitg.x*QK4_NL; i00 < ne00; i00 += ntg.x*QK4_NL) { device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*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( device const char * src0, device const char * src1, 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 & 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 tgpig[[threadgroup_position_in_grid]], uint3 tpitg[[thread_position_in_threadgroup]], uint3 ntg[[threads_per_threadgroup]]) { const int64_t i03 = tgpig.z; const int64_t i02 = tgpig.y; const int64_t i01 = tgpig.x; const int64_t i13 = i03 % ne13; const int64_t i12 = i02 % ne12; const int64_t i11 = i01 % ne11; device const char * src0_ptr = src0 + i03*nb03 + i02*nb02 + i01*nb01 + tpitg.x*nb00; device const char * src1_ptr = src1 + i13*nb13 + i12*nb12 + i11*nb11 + tpitg.x*nb10; device char * dst_ptr = dst + i03*nb3 + i02*nb2 + i01*nb1 + tpitg.x*nb0; for (int i0 = tpitg.x; i0 < ne0; i0 += ntg.x) { if (i02 < ne02) { ((device float *)dst_ptr)[0] = ((device float *)src0_ptr)[0]; src0_ptr += ntg.x*nb00; } else { ((device float *)dst_ptr)[0] = ((device float *)src1_ptr)[0]; src1_ptr += ntg.x*nb10; } dst_ptr += ntg.x*nb0; } } void kernel_mul_mv_q2_K_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); 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 + im*ne00*ne1; float yl[32]; float sumf[N_DST]={0.f}, all_sum; const int step = sizeof(block_q2_K) * nb; 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 += step/2; sc += step; dh += step/2; } y4 += 4 * QK_K; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum; } } } [[host_name("kernel_mul_mv_q2_K_f32")]] kernel void kernel_mul_mv_q2_K_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_q2_K_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg); } void kernel_mul_mv_q3_K_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = ne00/QK_K; const int64_t r0 = tgpig.x; const int64_t r1 = tgpig.y; const int64_t im = tgpig.z; const int first_row = (r0 * N_SIMDGROUP + sgitg) * 2; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); 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 + im*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 + im*ne0*ne1 + first_row + row] = sumf1[row]; } } } [[host_name("kernel_mul_mv_q3_K_f32")]] kernel void kernel_mul_mv_q3_K_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_q3_K_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg); } void kernel_mul_mv_q4_K_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint 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 = 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 int ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); 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 + im*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 * 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 += 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 + im*ne0*ne1 + first_row + row] = all_sum; } } } [[host_name("kernel_mul_mv_q4_K_f32")]] kernel void kernel_mul_mv_q4_K_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_q4_K_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg); } void kernel_mul_mv_q5_K_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = ne00/QK_K; const int64_t r0 = tgpig.x; const int64_t r1 = tgpig.y; const int im = tgpig.z; const int first_row = (r0 * N_SIMDGROUP + sgitg) * 2; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); 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 + im*ne00*ne1; float sumf[2]={0.f}; const int step = sizeof(block_q5_K) * nb; 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 += step; qh += step; dh += step/2; a += step/2; } y1 += 4 * QK_K; } for (int row = 0; row < 2; ++row) { const float tot = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = tot; } } } [[host_name("kernel_mul_mv_q5_K_f32")]] kernel void kernel_mul_mv_q5_K_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_q5_K_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg); } void kernel_mul_mv_q6_K_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { 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 im = tgpig.z; const int row = 2 * r0 + sgitg; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); 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 + im*ne00*ne1; 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]); } const float tot = simd_sum(sumf); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + row] = tot; } } [[host_name("kernel_mul_mv_q6_K_f32")]] kernel void kernel_mul_mv_q6_K_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_q6_K_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg); } // ======================= "True" 2-bit void kernel_mul_mv_iq2_xxs_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq2_xxs * x = (device const block_iq2_xxs *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; float yl[32]; float sumf[N_DST]={0.f}, all_sum; const int nb32 = nb * (QK_K / 32); threadgroup uint64_t * values = (threadgroup uint64_t *)shared_values; threadgroup uint8_t * shared_signs = (threadgroup uint8_t *)(values + 256); { int nval = 4; int pos = (32*sgitg + tiisg)*nval; for (int i = 0; i < nval; ++i) values[pos + i] = iq2xxs_grid[pos + i]; nval = 2; pos = (32*sgitg + tiisg)*nval; for (int i = 0; i < nval; ++i) shared_signs[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 *)(values + aux8[l]); const uint8_t signs = shared_signs[(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 += nb*sizeof(block_iq2_xxs)/2; q2 += nb*sizeof(block_iq2_xxs)/2; } y4 += 32 * 32; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum * 0.25f; } } } [[host_name("kernel_mul_mv_iq2_xxs_f32")]] kernel void kernel_mul_mv_iq2_xxs_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, threadgroup int8_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq2_xxs_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg); } void kernel_mul_mv_iq2_xs_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq2_xs * x = (device const block_iq2_xs *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; float yl[32]; float sumf[N_DST]={0.f}, all_sum; const int nb32 = nb * (QK_K / 32); threadgroup uint64_t * values = (threadgroup uint64_t *)shared_values; threadgroup uint8_t * shared_signs = (threadgroup uint8_t *)(values + 512); { int nval = 8; int pos = (32*sgitg + tiisg)*nval; for (int i = 0; i < nval; ++i) values[pos + i] = iq2xs_grid[pos + i]; nval = 2; pos = (32*sgitg + tiisg)*nval; for (int i = 0; i < nval; ++i) shared_signs[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 *)(values + (q2[l] & 511)); const uint8_t signs = shared_signs[(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 *)(values + (q2[l] & 511)); const uint8_t signs = shared_signs[(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 += nb*sizeof(block_iq2_xs)/2; q2 += nb*sizeof(block_iq2_xs)/2; sc += nb*sizeof(block_iq2_xs); } y4 += 32 * 32; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum * 0.25f; } } } [[host_name("kernel_mul_mv_iq2_xs_f32")]] kernel void kernel_mul_mv_iq2_xs_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, threadgroup int8_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq2_xs_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg); } void kernel_mul_mv_iq3_xxs_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq3_xxs * x = (device const block_iq3_xxs *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; float yl[32]; float sumf[N_DST]={0.f}, all_sum; const int nb32 = nb * (QK_K / 32); threadgroup uint32_t * values = (threadgroup uint32_t *)shared_values; threadgroup uint8_t * shared_signs = (threadgroup uint8_t *)(values + 256); { int nval = 4; int pos = (32*sgitg + tiisg)*nval; for (int i = 0; i < nval; ++i) values[pos + i] = iq3xxs_grid[pos + i]; nval = 2; pos = (32*sgitg + tiisg)*nval; for (int i = 0; i < nval; ++i) shared_signs[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 *)(values + q3[2*l+0]); const threadgroup uint8_t * grid2 = (const threadgroup uint8_t *)(values + q3[2*l+1]); const uint8_t signs = shared_signs[(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 += nb*sizeof(block_iq3_xxs)/2; q3 += nb*sizeof(block_iq3_xxs); gas += nb*sizeof(block_iq3_xxs)/2; } y4 += 32 * 32; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum * 0.5f; } } } [[host_name("kernel_mul_mv_iq3_xxs_f32")]] kernel void kernel_mul_mv_iq3_xxs_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, threadgroup int8_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq3_xxs_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg); } void kernel_mul_mv_iq3_s_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq3_s * x = (device const block_iq3_s *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; float yl[32]; float sumf[N_DST]={0.f}, all_sum; const int nb32 = nb * (QK_K / 32); threadgroup uint32_t * values = (threadgroup uint32_t *)shared_values; { int nval = 8; int pos = (32*sgitg + tiisg)*nval; for (int i = 0; i < nval; ++i) values[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] ? values + 256 : values; const threadgroup uint32_t * table2 = qh[0] & kmask_iq2xs[2*l+1] ? values + 256 : values; 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 += nb*sizeof(block_iq3_s)/2; qs += nb*sizeof(block_iq3_s); qh += nb*sizeof(block_iq3_s); sc += nb*sizeof(block_iq3_s); signs += nb*sizeof(block_iq3_s); } y4 += 32 * 32; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum; } } } [[host_name("kernel_mul_mv_iq3_s_f32")]] kernel void kernel_mul_mv_iq3_s_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, threadgroup int8_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq3_s_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg); } void kernel_mul_mv_iq2_s_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq2_s * x = (device const block_iq2_s *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; float yl[32]; float sumf[N_DST]={0.f}, all_sum; const int nb32 = nb * (QK_K / 32); //threadgroup uint64_t * values = (threadgroup uint64_t *)shared_values; //{ // int nval = 32; // int pos = (32*sgitg + tiisg)*nval; // for (int i = 0; i < nval; ++i) values[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 *)(values + (qs[l+0] | ((qh[0] << (8-2*l)) & 0x300))); //const threadgroup uint8_t * grid2 = (const threadgroup uint8_t *)(values + (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 += nb*sizeof(block_iq2_s)/2; qs += nb*sizeof(block_iq2_s); qh += nb*sizeof(block_iq2_s); sc += nb*sizeof(block_iq2_s); signs += nb*sizeof(block_iq2_s); } y4 += 32 * 32; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum * 0.25f; } } } [[host_name("kernel_mul_mv_iq2_s_f32")]] kernel void kernel_mul_mv_iq2_s_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, threadgroup int8_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq2_s_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg); } void kernel_mul_mv_iq1_s_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_value, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq1_s * x = (device const block_iq1_s *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; 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 += nb*sizeof(block_iq1_s)/2; qs += nb*sizeof(block_iq1_s); qh += nb*sizeof(block_iq1_s)/2; } y4 += 32 * 32; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum; } } } void kernel_mul_mv_iq1_m_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_value, uint3 tgpig, uint tiisg, uint sgitg) { const int nb = 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 ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq1_m * x = (device const block_iq1_m *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; 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 += nb*sizeof(block_iq1_m)/2; qs += nb*sizeof(block_iq1_m); qh += nb*sizeof(block_iq1_m); } y4 += 32 * 32; } for (int row = 0; row < N_DST; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum; } } } void kernel_mul_mv_iq4_nl_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values_i8, uint3 tgpig, uint tiisg, uint sgitg) { threadgroup float * shared_values = (threadgroup float *)shared_values_i8; const int nb = 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 int ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq4_nl * x = (device const block_iq4_nl *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; const int ix = tiisg/2; // 0...15 const int it = tiisg%2; // 0 or 1 shared_values[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; ++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 = {shared_values[q8[0]], shared_values[q8[1]], shared_values[q8[2]], shared_values[q8[3]]}; qf2 = {shared_values[q8[4]], shared_values[q8[5]], shared_values[q8[6]], shared_values[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 = {shared_values[q8[0]], shared_values[q8[1]], shared_values[q8[2]], shared_values[q8[3]]}; qf2 = {shared_values[q8[4]], shared_values[q8[5]], shared_values[q8[6]], shared_values[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; } for (int row = 0; row < 2; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum; } } } void kernel_mul_mv_iq4_xs_f32_impl( 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 r2, uint r3, threadgroup int8_t * shared_values_i8, uint3 tgpig, uint tiisg, uint sgitg) { threadgroup float * shared_values = (threadgroup float *)shared_values_i8; const int nb = 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 int ib_row = first_row * nb; const uint i12 = im%ne12; const uint i13 = im/ne12; const uint offset0 = (i12/r2)*(nb*ne01) + (i13/r3)*(nb*ne01*ne02); device const block_iq4_xs * x = (device const block_iq4_xs *) src0 + ib_row + offset0; device const float * y = (device const float *) src1 + r1*ne10 + im*ne00*ne1; 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; shared_values[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 = {shared_values[q8[0]], shared_values[q8[1]], shared_values[q8[2]], shared_values[q8[3]]}; qf2 = {shared_values[q8[4]], shared_values[q8[5]], shared_values[q8[6]], shared_values[q8[7]]}; acc1 += yl[0] * qf1; acc2 += yl[1] * qf2; aux32[0] = q4[1] & 0x0f0f0f0f; aux32[1] = (q4[1] >> 4) & 0x0f0f0f0f; qf1 = {shared_values[q8[0]], shared_values[q8[1]], shared_values[q8[2]], shared_values[q8[3]]}; qf2 = {shared_values[q8[4]], shared_values[q8[5]], shared_values[q8[6]], shared_values[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; } for (int row = 0; row < 2; ++row) { all_sum = simd_sum(sumf[row]); if (tiisg == 0) { dst[r1*ne0 + im*ne0*ne1 + first_row + row] = all_sum; } } } [[host_name("kernel_mul_mv_iq1_s_f32")]] kernel void kernel_mul_mv_iq1_s_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq1_s_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg); } [[host_name("kernel_mul_mv_iq1_m_f32")]] kernel void kernel_mul_mv_iq1_m_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq1_m_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, nullptr, tgpig, tiisg, sgitg); } [[host_name("kernel_mul_mv_iq4_nl_f32")]] kernel void kernel_mul_mv_iq4_nl_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, threadgroup int8_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq4_nl_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg); } [[host_name("kernel_mul_mv_iq4_xs_f32")]] kernel void kernel_mul_mv_iq4_xs_f32( device const void * src0, device const float * 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, constant uint & r2, constant uint & r3, threadgroup int8_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mv_iq4_xs_f32_impl(src0, src1, dst, ne00, ne01, ne02, ne10, ne12, ne0, ne1, r2, r3, shared_values, tgpig, tiisg, sgitg); } //============================= templates and their specializations ============================= // NOTE: this is not dequantizing - we are simply fitting the template template void dequantize_f32(device const float4x4 * src, short il, thread type4x4 & reg) { float4x4 temp = *(((device float4x4 *)src)); for (int i = 0; i < 16; i++){ reg[i/4][i%4] = temp[i/4][i%4]; } } 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_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; 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[i/2][2*(i%2)+0] = d * x0 + md; reg[i/2][2*(i%2)+1] = d * x1 + md; } } template 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; 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[i/2][2*(i%2)+0] = d * x0 + m; reg[i/2][2*(i%2)+1] = d * x1 + 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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]]; } } template kernel void kernel_get_rows( device const void * src0, device const char * 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 i = tgpig; //const int64_t r = ((device int32_t *) src1)[i]; const int64_t i10 = tgpig.x; const int64_t i11 = tgpig.y; const int64_t r = ((device int32_t *) ((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 *) ((device char *) src0 + r*nb01 + i02*nb02)) + ind/nl, ind%nl, temp); *(((device float4x4 *) ((device char *) dst + i11*nb2 + i10*nb1)) + ind) = temp; } } kernel void kernel_get_rows_f32( device const void * src0, device const char * 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 = ((device int32_t *) ((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] = ((device float *) ((device char *) src0 + r*nb01 + i02*nb02))[ind]; } } kernel void kernel_get_rows_f16( device const void * src0, device const char * 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 = ((device int32_t *) ((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] = ((device half *) ((device char *) src0 + r*nb01 + i02*nb02))[ind]; } } kernel void kernel_get_rows_i32( device const void * src0, device const char * 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 = ((device int32_t *) ((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] = ((device int32_t *) ((device char *) src0 + r*nb01 + i02*nb02))[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 void kernel_mul_mm_impl(device const uchar * src0, device const uchar * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne02, constant uint64_t & nb01, constant uint64_t & nb02, constant int64_t & ne12, constant uint64_t & nb10, constant uint64_t & nb11, constant uint64_t & nb12, constant int64_t & ne0, constant int64_t & ne1, constant uint & r2, constant uint & r3, 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); const uint i12 = im%ne12; const uint i13 = im/ne12; uint offset0 = (i12/r2)*nb02 + (i13/r3)*(nb02*ne02); 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 = (device const float *)(src1 + nb12 * im + nb11 * (r1 * BLOCK_SIZE_N + thread_col) + 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); #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]; } *(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); } } } } } // same as kernel_mul_mm_impl, but src1 and dst are accessed via indices stored in rowids template void kernel_mul_mm_id_impl( device const uchar * src0, device const uchar * src1, threadgroup ushort2 * rowids, device float * dst, constant int64_t & ne00, constant int64_t & ne02, constant uint64_t & nb01, constant uint64_t & nb02, constant int64_t & ne11, constant int64_t & ne12, constant uint64_t & nb10, constant uint64_t & nb11, constant uint64_t & nb12, constant int64_t & ne0, int64_t ne1, int64_t ne0ne1, threadgroup uchar * shared_memory, 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; 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 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); 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)); for (int ik = 0; ik < BLOCK_SIZE_K / 8; ik++) { for (int i = 0; i < 4; i++) { simdgroup_load(ma[i], lsma + SG_MAT_SIZE * i); } simdgroup_barrier(mem_flags::mem_none); 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; for (int i = 0; i < 8; i++){ simdgroup_multiply_accumulate(c_res[i], mb[i/4], ma[i%4], c_res[i]); } } } { 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); if (sgitg == 0) { for (int j = tiitg; j < n_cols; j += BLOCK_SIZE_N) { threadgroup const auto & jid = rowids[r1 * BLOCK_SIZE_N + j]; int joff = jid[0] * ne0 + jid[1] * ne0ne1; for (int i = 0; i < n_rows; i++) { *(C + i + joff) = *(temp_str + i + j * BLOCK_SIZE_M); } } } } } template kernel void kernel_mul_mm(device const uchar * src0, device const uchar * src1, device float * dst, constant int64_t & ne00, constant int64_t & ne02, constant uint64_t & nb01, constant uint64_t & nb02, constant int64_t & ne12, constant uint64_t & nb10, constant uint64_t & nb11, constant uint64_t & nb12, constant int64_t & ne0, constant int64_t & ne1, constant uint & r2, constant uint & r3, threadgroup uchar * shared_memory [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiitg[[thread_index_in_threadgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { kernel_mul_mm_impl( src0, src1, dst, ne00, ne02, nb01, nb02, ne12, nb10, nb11, nb12, ne0, ne1, r2, r3, shared_memory, tgpig, tiitg, sgitg); } template kernel void kernel_mul_mm_id( device const uchar * src0s, device const uchar * src1, device float * dst, device const uchar * ids, constant int64_t & nei0, constant int64_t & nei1, constant uint64_t & nbi1, constant int64_t & ne00, constant int64_t & ne02, constant uint64_t & nb01, constant uint64_t & nb02, 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 int64_t & ne0, constant int64_t & ne1, constant uint64_t & nb1, threadgroup uchar * shared_memory [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiitg[[thread_index_in_threadgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const int32_t i02 = tgpig.z; tgpig.z = 0; device const uchar * src0 = src0s + i02*nb02; // row indices threadgroup ushort2 * rowids = (threadgroup ushort2 *)(shared_memory + 8192); // TODO: parallelize this loop int64_t _ne1 = 0; for (ushort ii1 = 0; ii1 < nei1; ii1++) { for (ushort ii0 = 0; ii0 < nei0; ii0++) { int32_t id = ((device int32_t *) (ids + ii1*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( src0, src1, rowids, dst, ne00, ne02, nb01, nb02, ne11, ne12, nb10, nb11, nb12, ne0, _ne1, ne0*ne1, shared_memory, tgpig, tiitg, sgitg); } #define QK_NL 16 // // get rows // typedef void (get_rows_t)( device const void * src0, device const char * 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, uint, uint3); //template [[host_name("kernel_get_rows_f32")]] kernel get_rows_t kernel_get_rows; //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_q5_0")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_q5_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; template [[host_name("kernel_get_rows_iq2_xxs")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_iq2_xs")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_iq3_xxs")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_iq3_s")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_iq2_s")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_iq1_s")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_iq1_m")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_iq4_nl")]] kernel get_rows_t kernel_get_rows; template [[host_name("kernel_get_rows_iq4_xs")]] kernel get_rows_t kernel_get_rows; // // matrix-matrix multiplication // typedef decltype(kernel_mul_mm) mat_mm_t; template [[host_name("kernel_mul_mm_f32_f32")]] kernel mat_mm_t kernel_mul_mm; 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_q5_0_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q5_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; template [[host_name("kernel_mul_mm_iq2_xxs_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_iq2_xs_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_iq3_xxs_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_iq3_s_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_iq2_s_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_iq1_s_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_iq1_m_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_iq4_nl_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_iq4_xs_f32")]] kernel mat_mm_t kernel_mul_mm; // // indirect matrix-matrix multiplication // typedef decltype(kernel_mul_mm_id) mat_mm_id_t; template [[host_name("kernel_mul_mm_id_f32_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_f16_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q4_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q4_1_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q5_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q5_1_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q8_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q2_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q3_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q4_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q5_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q6_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq2_xxs_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq2_xs_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq3_xxs_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq3_s_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq2_s_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq1_s_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq1_m_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq4_nl_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_iq4_xs_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; // // matrix-vector multiplication // typedef void (kernel_mul_mv_impl_t)( device const char * src0, device const char * src1, device float * dst, int64_t ne00, int64_t ne01, int64_t ne02, uint64_t nb00, uint64_t nb01, uint64_t nb02, int64_t ne10, int64_t ne11, int64_t ne12, uint64_t nb10, uint64_t nb11, uint64_t nb12, int64_t ne0, int64_t ne1, uint r2, uint r3, uint3 tgpig, uint tiisg); typedef void (kernel_mul_mv2_impl_t)( 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 r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiisg, uint sgitg); template void mmv_fn( device const char * src0, device const char * src1, device float * dst, int64_t ne00, int64_t ne01, int64_t ne02, uint64_t nb00, uint64_t nb01, uint64_t nb02, int64_t ne10, int64_t ne11, int64_t ne12, int64_t ne13, uint64_t nb10, uint64_t nb11, uint64_t nb12, int64_t ne0, int64_t ne1, uint64_t nb1, uint r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiitg, uint tiisg, uint sgitg) { impl_fn(src0,src1,dst,ne00,ne01,ne02,nb00,nb01,nb02,ne10,ne11,ne12,nb10,nb11,nb12,ne0,ne1,r2,r3,tgpig,tiisg); } template void mmv_fn( device const char * src0, device const char * src1, device float * dst, int64_t ne00, int64_t ne01, int64_t ne02, uint64_t nb00, uint64_t nb01, uint64_t nb02, int64_t ne10, int64_t ne11, int64_t ne12, int64_t ne13, uint64_t nb10, uint64_t nb11, uint64_t nb12, int64_t ne0, int64_t ne1, uint64_t nb1, uint r2, uint r3, threadgroup int8_t * shared_values, uint3 tgpig, uint tiitg, uint tiisg, uint sgitg) { impl_fn(src0,(const device float *)src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,shared_values,tgpig,tiisg,sgitg); } typedef decltype(mmv_fn) mul_mv_impl_fn_t; template kernel void kernel_mul_mv_id( device const char * src0s, device const char * src1, device float * dst, device const char * ids, constant int64_t & nei0, constant int64_t & nei1, constant uint64_t & nbi1, 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 int64_t & ne13, constant uint64_t & nb10, constant uint64_t & nb11, constant uint64_t & nb12, constant int64_t & ne0, constant int64_t & ne1, constant uint64_t & nb1, threadgroup int8_t * shared_values [[threadgroup(0)]], uint3 tgpig[[threadgroup_position_in_grid]], uint tiitg[[thread_index_in_threadgroup]], uint tiisg[[thread_index_in_simdgroup]], uint sgitg[[simdgroup_index_in_threadgroup]]) { const int iid1 = tgpig.z/nei0; const int idx = tgpig.z%nei0; tgpig.z = 0; const int32_t i02 = ((device const int32_t *) (ids + iid1*nbi1))[idx]; const int64_t i11 = idx % ne11; const int64_t i12 = iid1; const int64_t i1 = idx; const int64_t i2 = i12; device const char * src0_cur = src0s + i02*nb02; device const char * src1_cur = src1 + i11*nb11 + i12*nb12; device float * dst_cur = dst + i1*ne0 + i2*ne1*ne0; impl_fn( /* src0 */ src0_cur, /* src1 */ src1_cur, /* dst */ dst_cur, /* ne00 */ ne00, /* ne01 */ ne01, /* ne02 */ 1,//ne02, /* nb00 */ nb00, /* nb01 */ nb01, /* nb02 */ nb02, /* ne10 */ ne10, /* ne11 */ 1,//ne11, /* ne12 */ 1,//ne12, /* ne13 */ 1,//ne13, /* nb10 */ nb10, /* nb11 */ nb11, /* nb12 */ nb12, /* ne0 */ ne0, /* ne1 */ 1,//ne1, /* nb1 */ nb1, /* r2 */ 1, /* r3 */ 1, shared_values, tgpig, tiitg, tiisg, sgitg); } typedef decltype(kernel_mul_mv_id>) kernel_mul_mv_id_t; template [[host_name("kernel_mul_mv_id_f32_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_f16_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_q8_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_q4_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; template [[host_name("kernel_mul_mv_id_q4_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; template [[host_name("kernel_mul_mv_id_q5_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; template [[host_name("kernel_mul_mv_id_q5_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; template [[host_name("kernel_mul_mv_id_q2_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_q3_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_q4_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_q5_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_q6_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq1_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq1_m_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq2_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq2_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq3_xxs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq3_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq2_s_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq4_nl_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_iq4_xs_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>;