mirror of
https://github.com/ggerganov/whisper.cpp.git
synced 2025-05-08 03:28:24 +00:00
189 lines
6.3 KiB
Plaintext
189 lines
6.3 KiB
Plaintext
#include "quantize.cuh"
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#include <cstdint>
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static __global__ void quantize_q8_1(
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const float * __restrict__ x, void * __restrict__ vy,
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const int64_t ne00, const int64_t s01, const int64_t s02, const int64_t s03,
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const int64_t ne0, const int ne1, const int ne2) {
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const int64_t i0 = (int64_t)blockDim.x*blockIdx.x + threadIdx.x;
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if (i0 >= ne0) {
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return;
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}
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const int64_t i1 = blockIdx.y;
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const int64_t i2 = blockIdx.z % ne2;
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const int64_t i3 = blockIdx.z / ne2;
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const int64_t & i00 = i0;
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const int64_t & i01 = i1;
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const int64_t & i02 = i2;
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const int64_t & i03 = i3;
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const int64_t i_cont = ((i3*ne2 + i2) * ne1 + i1) * ne0 + i0;
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block_q8_1 * y = (block_q8_1 *) vy;
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const int64_t ib = i_cont / QK8_1; // block index
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const int64_t iqs = i_cont % QK8_1; // quant index
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const float xi = i0 < ne00 ? x[i03*s03 + i02*s02 + i01*s01 + i00] : 0.0f;
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float amax = fabsf(xi);
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float sum = xi;
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amax = warp_reduce_max(amax);
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sum = warp_reduce_sum(sum);
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const float d = amax / 127;
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const int8_t q = amax == 0.0f ? 0 : roundf(xi / d);
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y[ib].qs[iqs] = q;
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if (iqs > 0) {
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return;
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}
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reinterpret_cast<half&>(y[ib].ds.x) = d;
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reinterpret_cast<half&>(y[ib].ds.y) = sum;
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}
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template <mmq_q8_1_ds_layout ds_layout>
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static __global__ void quantize_mmq_q8_1(
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const float * __restrict__ x, const int32_t * __restrict__ ids, void * __restrict__ vy,
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const int64_t ne00, const int64_t s01, const int64_t s02, const int64_t s03,
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const int64_t ne0, const int ne1, const int ne2) {
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constexpr int vals_per_scale = ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6 ? 64 : 32;
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constexpr int vals_per_sum = ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6 ? 16 : 32;
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const int64_t i0 = ((int64_t)blockDim.x*blockIdx.x + threadIdx.x)*4;
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if (i0 >= ne0) {
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return;
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}
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const int64_t i1 = blockIdx.y;
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const int64_t i2 = blockIdx.z % ne2;
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const int64_t i3 = blockIdx.z / ne2;
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const int64_t i00 = i0;
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const int64_t i01 = ids ? ids[i1] : i1;
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const int64_t i02 = i2;
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const int64_t i03 = i3;
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const float4 * x4 = (const float4 *) x;
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block_q8_1_mmq * y = (block_q8_1_mmq *) vy;
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const int64_t ib0 = blockIdx.z*((int64_t)gridDim.y*gridDim.x*blockDim.x/QK8_1); // first block of channel
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const int64_t ib = ib0 + (i0 / (4*QK8_1))*ne1 + blockIdx.y; // block index in channel
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const int64_t iqs = i0 % (4*QK8_1); // quant index in block
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// Load 4 floats per thread and calculate max. abs. value between them:
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const float4 xi = i0 < ne00 ? x4[(i03*s03 + i02*s02 + i01*s01 + i00)/4] : make_float4(0.0f, 0.0f, 0.0f, 0.0f);
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float amax = fabsf(xi.x);
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amax = fmaxf(amax, fabsf(xi.y));
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amax = fmaxf(amax, fabsf(xi.z));
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amax = fmaxf(amax, fabsf(xi.w));
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// Exchange max. abs. value between vals_per_scale/4 threads.
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#pragma unroll
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for (int offset = vals_per_scale/8; offset > 0; offset >>= 1) {
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amax = fmaxf(amax, __shfl_xor_sync(0xFFFFFFFF, amax, offset, WARP_SIZE));
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}
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float sum;
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if (ds_layout != MMQ_Q8_1_DS_LAYOUT_D4) {
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sum = xi.x + xi.y + xi.z + xi.w;
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// Calculate sums across vals_per_sum/4 threads.
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#pragma unroll
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for (int offset = vals_per_sum/8; offset > 0; offset >>= 1) {
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sum += __shfl_xor_sync(0xFFFFFFFF, sum, offset, WARP_SIZE);
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}
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}
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const float d_inv = 127.0f / amax;
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char4 q;
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q.x = roundf(xi.x*d_inv);
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q.y = roundf(xi.y*d_inv);
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q.z = roundf(xi.z*d_inv);
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q.w = roundf(xi.w*d_inv);
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// Write back 4 int8 values as a single 32 bit value for better memroy bandwidth:
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char4 * yqs4 = (char4 *) y[ib].qs;
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yqs4[iqs/4] = q;
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if (ds_layout == MMQ_Q8_1_DS_LAYOUT_D2S6) {
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if (iqs % 16 != 0 || iqs >= 96) {
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return;
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}
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y[ib].d2s6[2 + iqs/16] = sum;
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if (iqs % 64 != 0) {
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return;
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}
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const float d = 1.0f / d_inv;
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y[ib].d2s6[iqs/64] = d;
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return;
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}
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if (iqs % 32 != 0) {
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return;
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}
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const float d = 1.0f / d_inv;
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if (ds_layout == MMQ_Q8_1_DS_LAYOUT_DS4) {
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y[ib].ds4[iqs/32] = make_half2(d, sum);
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} else {
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y[ib].d4[iqs/32] = d;
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}
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}
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void quantize_row_q8_1_cuda(
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const float * x, const int32_t * ids, void * vy, const ggml_type type_src0,
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const int64_t ne00, const int64_t s01, const int64_t s02, const int64_t s03,
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const int64_t ne0, const int64_t ne1, const int64_t ne2, const int64_t ne3, cudaStream_t stream) {
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GGML_ASSERT(!ids);
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GGML_ASSERT(ne0 % QK8_1 == 0);
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const int64_t block_num_x = (ne0 + CUDA_QUANTIZE_BLOCK_SIZE - 1) / CUDA_QUANTIZE_BLOCK_SIZE;
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const dim3 num_blocks(block_num_x, ne1, ne2*ne3);
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const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE, 1, 1);
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quantize_q8_1<<<num_blocks, block_size, 0, stream>>>(x, vy, ne00, s01, s02, s03, ne0, ne1, ne2);
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GGML_UNUSED(type_src0);
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}
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void quantize_mmq_q8_1_cuda(
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const float * x, const int32_t * ids, void * vy, const ggml_type type_src0,
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const int64_t ne00, const int64_t s01, const int64_t s02, const int64_t s03,
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const int64_t ne0, const int64_t ne1, const int64_t ne2, const int64_t ne3, cudaStream_t stream) {
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GGML_ASSERT(ne0 % (4*QK8_1) == 0);
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const int64_t block_num_x = (ne0 + 4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ - 1) / (4*CUDA_QUANTIZE_BLOCK_SIZE_MMQ);
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const dim3 num_blocks(block_num_x, ne1, ne2*ne3);
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const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE_MMQ, 1, 1);
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switch (mmq_get_q8_1_ds_layout(type_src0)) {
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case MMQ_Q8_1_DS_LAYOUT_D4:
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quantize_mmq_q8_1<MMQ_Q8_1_DS_LAYOUT_D4>
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<<<num_blocks, block_size, 0, stream>>>(x, ids, vy, ne00, s01, s02, s03, ne0, ne1, ne2);
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break;
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case MMQ_Q8_1_DS_LAYOUT_DS4:
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quantize_mmq_q8_1<MMQ_Q8_1_DS_LAYOUT_DS4>
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<<<num_blocks, block_size, 0, stream>>>(x, ids, vy, ne00, s01, s02, s03, ne0, ne1, ne2);
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break;
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case MMQ_Q8_1_DS_LAYOUT_D2S6:
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quantize_mmq_q8_1<MMQ_Q8_1_DS_LAYOUT_D2S6>
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<<<num_blocks, block_size, 0, stream>>>(x, ids, vy, ne00, s01, s02, s03, ne0, ne1, ne2);
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break;
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default:
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GGML_ABORT("fatal error");
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break;
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}
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}
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