/** * llama.cpp - commit 3f1ae2e32cde00c39b96be6d01c2997c29bae555 - do not edit this file * * MIT License * * Copyright (c) 2023-2024 The ggml authors * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in all * copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ #include "quantize.cuh" #include static __global__ void quantize_q8_1(const float * __restrict__ x, void * __restrict__ vy, const int64_t kx, const int64_t kx0_padded) { const int64_t ix0 = (int64_t)blockDim.x*blockIdx.x + threadIdx.x; if (ix0 >= kx0_padded) { return; } const int64_t ix1 = blockIdx.y; const int64_t i_padded = ix1*kx0_padded + ix0; block_q8_1 * y = (block_q8_1 *) vy; const int64_t ib = i_padded / QK8_1; // block index const int64_t iqs = i_padded % QK8_1; // quant index const float xi = ix0 < kx ? x[ix1*kx + ix0] : 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, void * __restrict__ vy, const int64_t kx0, const int64_t kx1, const int64_t kx0_padded) { 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 ix0 = ((int64_t)blockDim.x*blockIdx.x + threadIdx.x)*4; if (ix0 >= kx0_padded) { return; } const float4 * x4 = (const float4 *) x; const int64_t ix1 = kx1*blockIdx.z + blockIdx.y; 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 + (ix0 / (4*QK8_1))*kx1 + blockIdx.y; // block index in channel const int64_t iqs = ix0 % (4*QK8_1); // quant index in block // Load 4 floats per thread and calculate max. abs. value between them: const float4 xi = ix0 < kx0 ? x4[(ix1*kx0 + ix0)/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 mask = vals_per_scale/8; mask > 0; mask >>= 1) { amax = fmaxf(amax, __shfl_xor_sync(0xFFFFFFFF, amax, mask, WARP_SIZE)); } float sum; if (ds_layout != MMQ_Q8_1_DS_LAYOUT_D4) { sum = xi.x + xi.y + xi.z + xi.w; // Exchange calculate sum across vals_per_sum/4 threads. #pragma unroll for (int mask = vals_per_sum/8; mask > 0; mask >>= 1) { sum += __shfl_xor_sync(0xFFFFFFFF, sum, mask, 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, void * vy, const int64_t kx0, const int64_t kx1, const int64_t channels, const int64_t kx0_padded, const ggml_type type_x, cudaStream_t stream) { GGML_ASSERT(kx0_padded % QK8_1 == 0); const int64_t block_num_x = (kx0_padded + CUDA_QUANTIZE_BLOCK_SIZE - 1) / CUDA_QUANTIZE_BLOCK_SIZE; const dim3 num_blocks(block_num_x, kx1*channels, 1); const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE, 1, 1); quantize_q8_1<<>>(x, vy, kx0, kx0_padded); GGML_UNUSED(type_x); } void quantize_mmq_q8_1_cuda( const float * x, void * vy, const int64_t kx0, const int64_t kx1, const int64_t channels, const int64_t kx0_padded, const ggml_type type_x, cudaStream_t stream) { GGML_ASSERT(kx0_padded % (4*QK8_1) == 0); const int64_t block_num_x = (kx0_padded + 4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ - 1) / (4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ); const dim3 num_blocks(block_num_x, kx1, channels); const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE_MMQ, 1, 1); switch (mmq_get_q8_1_ds_layout(type_x)) { case MMQ_Q8_1_DS_LAYOUT_D4: quantize_mmq_q8_1 <<>>(x, vy, kx0, kx1, kx0_padded); break; case MMQ_Q8_1_DS_LAYOUT_DS4: quantize_mmq_q8_1 <<>>(x, vy, kx0, kx1, kx0_padded); break; case MMQ_Q8_1_DS_LAYOUT_D2S6: quantize_mmq_q8_1 <<>>(x, vy, kx0, kx1, kx0_padded); break; default: GGML_ABORT("fatal error"); break; } }