#include "quantize.cuh" #include static __global__ void quantize_q8_1( const float * __restrict__ x, void * __restrict__ vy, const int64_t ne00, const int64_t s01, const int64_t s02, const int64_t s03, const int64_t ne0, const int ne1, const int ne2) { const int64_t i0 = (int64_t)blockDim.x*blockIdx.x + threadIdx.x; if (i0 >= ne0) { return; } const int64_t i1 = blockIdx.y; const int64_t i2 = blockIdx.z % ne2; const int64_t i3 = blockIdx.z / ne2; const int64_t & i00 = i0; const int64_t & i01 = i1; const int64_t & i02 = i2; const int64_t & i03 = i3; const int64_t i_cont = ((i3*ne2 + i2) * ne1 + i1) * ne0 + i0; block_q8_1 * y = (block_q8_1 *) vy; const int64_t ib = i_cont / QK8_1; // block index const int64_t iqs = i_cont % QK8_1; // quant index const float xi = i0 < ne00 ? x[i03*s03 + i02*s02 + i01*s01 + i00] : 0.0f; float amax = fabsf(xi); float sum = xi; amax = warp_reduce_max(amax); sum = warp_reduce_sum(sum); const float d = amax / 127; const int8_t q = amax == 0.0f ? 0 : roundf(xi / d); y[ib].qs[iqs] = q; if (iqs > 0) { return; } reinterpret_cast(y[ib].ds.x) = d; reinterpret_cast(y[ib].ds.y) = sum; } template static __global__ void quantize_mmq_q8_1( const float * __restrict__ x, const int32_t * __restrict__ ids, void * __restrict__ vy, const int64_t ne00, const int64_t s01, const int64_t s02, const int64_t s03, const int64_t ne0, const int ne1, const int ne2) { constexpr int vals_per_scale = ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6 ? 64 : 32; constexpr int vals_per_sum = ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6 ? 16 : 32; const int64_t i0 = ((int64_t)blockDim.x*blockIdx.x + threadIdx.x)*4; if (i0 >= ne0) { return; } const int64_t i1 = blockIdx.y; const int64_t i2 = blockIdx.z % ne2; const int64_t i3 = blockIdx.z / ne2; const int64_t i00 = i0; const int64_t i01 = ids ? ids[i1] : i1; const int64_t i02 = i2; const int64_t i03 = i3; const float4 * x4 = (const float4 *) x; block_q8_1_mmq * y = (block_q8_1_mmq *) vy; const int64_t ib0 = blockIdx.z*((int64_t)gridDim.y*gridDim.x*blockDim.x/QK8_1); // first block of channel const int64_t ib = ib0 + (i0 / (4*QK8_1))*ne1 + blockIdx.y; // block index in channel const int64_t iqs = i0 % (4*QK8_1); // quant index in block // Load 4 floats per thread and calculate max. abs. value between them: const float4 xi = i0 < ne00 ? x4[(i03*s03 + i02*s02 + i01*s01 + i00)/4] : make_float4(0.0f, 0.0f, 0.0f, 0.0f); float amax = fabsf(xi.x); amax = fmaxf(amax, fabsf(xi.y)); amax = fmaxf(amax, fabsf(xi.z)); amax = fmaxf(amax, fabsf(xi.w)); // Exchange max. abs. value between vals_per_scale/4 threads. #pragma unroll for (int offset = vals_per_scale/8; offset > 0; offset >>= 1) { amax = fmaxf(amax, __shfl_xor_sync(0xFFFFFFFF, amax, offset, WARP_SIZE)); } float sum; if (ds_layout != MMQ_Q8_1_DS_LAYOUT_D4) { sum = xi.x + xi.y + xi.z + xi.w; // Calculate sums across vals_per_sum/4 threads. #pragma unroll for (int offset = vals_per_sum/8; offset > 0; offset >>= 1) { sum += __shfl_xor_sync(0xFFFFFFFF, sum, offset, WARP_SIZE); } } const float d_inv = 127.0f / amax; char4 q; q.x = roundf(xi.x*d_inv); q.y = roundf(xi.y*d_inv); q.z = roundf(xi.z*d_inv); q.w = roundf(xi.w*d_inv); // Write back 4 int8 values as a single 32 bit value for better memroy bandwidth: char4 * yqs4 = (char4 *) y[ib].qs; yqs4[iqs/4] = q; if (ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6) { if (iqs % 16 != 0 || iqs >= 96) { return; } y[ib].d2s6[2 + iqs/16] = sum; if (iqs % 64 != 0) { return; } const float d = 1.0f / d_inv; y[ib].d2s6[iqs/64] = d; return; } if (iqs % 32 != 0) { return; } const float d = 1.0f / d_inv; if (ds_layout == MMQ_Q8_1_DS_LAYOUT_DS4) { y[ib].ds4[iqs/32] = make_half2(d, sum); } else { y[ib].d4[iqs/32] = d; } } void quantize_row_q8_1_cuda( const float * x, const int32_t * ids, void * vy, const ggml_type type_src0, const int64_t ne00, const int64_t s01, const int64_t s02, const int64_t s03, const int64_t ne0, const int64_t ne1, const int64_t ne2, const int64_t ne3, cudaStream_t stream) { GGML_ASSERT(!ids); GGML_ASSERT(ne0 % QK8_1 == 0); const int64_t block_num_x = (ne0 + CUDA_QUANTIZE_BLOCK_SIZE - 1) / CUDA_QUANTIZE_BLOCK_SIZE; const dim3 num_blocks(block_num_x, ne1, ne2*ne3); const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE, 1, 1); quantize_q8_1<<>>(x, vy, ne00, s01, s02, s03, ne0, ne1, ne2); GGML_UNUSED(type_src0); } void quantize_mmq_q8_1_cuda( const float * x, const int32_t * ids, void * vy, const ggml_type type_src0, const int64_t ne00, const int64_t s01, const int64_t s02, const int64_t s03, const int64_t ne0, const int64_t ne1, const int64_t ne2, const int64_t ne3, cudaStream_t stream) { GGML_ASSERT(ne0 % (4*QK8_1) == 0); const int64_t block_num_x = (ne0 + 4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ - 1) / (4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ); const dim3 num_blocks(block_num_x, ne1, ne2*ne3); const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE_MMQ, 1, 1); switch (mmq_get_q8_1_ds_layout(type_src0)) { case MMQ_Q8_1_DS_LAYOUT_D4: quantize_mmq_q8_1 <<>>(x, ids, vy, ne00, s01, s02, s03, ne0, ne1, ne2); break; case MMQ_Q8_1_DS_LAYOUT_DS4: quantize_mmq_q8_1 <<>>(x, ids, vy, ne00, s01, s02, s03, ne0, ne1, ne2); break; case MMQ_Q8_1_DS_LAYOUT_D2S6: quantize_mmq_q8_1 <<>>(x, ids, vy, ne00, s01, s02, s03, ne0, ne1, ne2); break; default: GGML_ABORT("fatal error"); break; } }