cuda : faster k-quants on older GPUs (#1930)
* k_quants: hopefully much faster Q4_K on older GPUs On the GTX-1660 that I have available to represent "old GPUs", token prediction drops from 65.5 ms/tok to 41.5 ms/tok! * k_quants: hopefully much faster Q3_K on older GPUs On the GTX-1660 that I have available to represent "old GPUs", token prediction drops from 60.3 ms/tok to 41.0 ms/tok! * k_quants: faster Q2_K on older GPUs It looks like I didn't need to change anything compared to what we already had, so this is just adding clarifying comments. But I now measure 36.3 ms/tok on the GTX-1660, instead fo the 47.2 ms/tok that I have written in the faster k-quants PR. * k_quants: faster Q5_K on older GPUs 68.5 ms/tok -> 62.0 ms/tok on GTX-1660. For some reason the same access pattern that leads to such resounding success for Q2_K to Q4_K did not work at all for Q5_K. It is also more difficult to measure because for Q5_K_S we only have 32 layers on the GTX-1660, so output, tok embeddings and kv cache are done on the CPU. --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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ggml-cuda.cu
83
ggml-cuda.cu
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@ -515,15 +515,15 @@ static __global__ void dequantize_mul_mat_vec_q2_k(const void * vx, const float
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const block_q2_K * x = (const block_q2_K *)vx + ib0;
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const int tid = threadIdx.x/K_QUANTS_PER_ITERATION; // 0...31
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const int ix = threadIdx.x%K_QUANTS_PER_ITERATION; // 0
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const int tid = threadIdx.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...15
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const int ix = threadIdx.x%K_QUANTS_PER_ITERATION; // 0 or 0,1
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const int step = 16/K_QUANTS_PER_ITERATION;
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const int im = tid/step; // 0 or 1. 0 computes 0..., 1 computes 128...
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const int in = tid - step*im; // 0...7
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const int im = tid/step; // 0 or 1. 0 computes 0..., 1 computes 128...
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const int in = tid - step*im; // 0...15 or 0...7
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const int l0 = K_QUANTS_PER_ITERATION*in; // 0...14 in steps of 4
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const int l0 = K_QUANTS_PER_ITERATION*in; // 0...15 or 0...14 in steps of 2
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const int q_offset = 32*im + l0;
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const int s_offset = 8*im;
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const int y_offset = 128*im + l0;
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@ -578,27 +578,30 @@ static __global__ void dequantize_mul_mat_vec_q2_k(const void * vx, const float
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}
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}
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static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float * yy, float * dst, const int ncols) {
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static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float * yy, float * dst, const int ncols, int nrows) {
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const uint16_t kmask1 = 0x0303;
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const uint16_t kmask2 = 0x0f0f;
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const int row = blockIdx.x;
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const int row = blockIdx.y*blockDim.y + threadIdx.y;
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if (row > nrows) return;
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const int num_blocks_per_row = ncols / QK_K;
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const int ib0 = row*num_blocks_per_row;
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const block_q3_K * x = (const block_q3_K *)vx + ib0;
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const int tid = threadIdx.x/2; // 0...15
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const int ix = threadIdx.x%2; // 0, 1
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const int tid = threadIdx.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16
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const int ix = threadIdx.x%K_QUANTS_PER_ITERATION; // 0 or 0,1
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const int n = 2; // iterations in the inner loop
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const int im = tid/8; // 0 or 1. 0 computes 0..., 1 computes 128...
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const int in = tid - 8*im; // 0...7
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const int n = K_QUANTS_PER_ITERATION; // iterations in the inner loop
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const int step = 16/K_QUANTS_PER_ITERATION;
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const int im = tid/step; // 0 or 1. 0 computes 0..., 1 computes 128...
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const int in = tid - step*im; // 0....15 or 0...7
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const uint8_t m = 1 << (4*im);
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const int l0 = n*in; // 0...28 in steps of 4
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const int l0 = n*in; // 0...15 or 0...14 in steps of 2
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const int q_offset = 32*im + l0;
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const int y_offset = 128*im + l0;
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@ -609,7 +612,7 @@ static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float
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float tmp = 0; // partial sum for thread in warp
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for (int i = ix; i < num_blocks_per_row; i += 2) {
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for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
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const float * y = yy + i * QK_K + y_offset;
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const uint8_t * q = x[i].qs + q_offset;
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@ -650,22 +653,25 @@ static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float
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}
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}
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static __global__ void dequantize_mul_mat_vec_q4_k(const void * vx, const float * yy, float * dst, const int ncols) {
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static __global__ void dequantize_mul_mat_vec_q4_k(const void * vx, const float * yy, float * dst, const int ncols, int nrows) {
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const uint16_t kmask1 = 0x3f3f;
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const uint16_t kmask2 = 0x0f0f;
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const uint16_t kmask3 = 0xc0c0;
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const int row = blockIdx.x;
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const int row = blockIdx.y*blockDim.y + threadIdx.y;
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if (row > nrows) return;
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const int num_blocks_per_row = ncols / QK_K;
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const int ib0 = row*num_blocks_per_row;
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const int tid = threadIdx.x/2; // 0...15
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const int ix = threadIdx.x%2;
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const int tid = threadIdx.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16
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const int ix = threadIdx.x%K_QUANTS_PER_ITERATION; // 0 or 0,1
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const int il = tid/4; // 0...3
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const int ir = tid - 4*il;// 0...3
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const int n = 4;
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const int step = 8/K_QUANTS_PER_ITERATION; // 8 or 4
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const int il = tid/step; // 0...3
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const int ir = tid - step*il; // 0...7 or 0...3
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const int n = 2 * K_QUANTS_PER_ITERATION; // 2 or 4
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const int im = il/2; // 0 or 1. 0 computes 0,32 + 128,160, 1 computes 64,96 + 192,224
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const int in = il%2;
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@ -681,7 +687,7 @@ static __global__ void dequantize_mul_mat_vec_q4_k(const void * vx, const float
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float tmp = 0; // partial sum for thread in warp
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for (int i = ix; i < num_blocks_per_row; i += 2) {
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for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
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const uint8_t * q1 = x[i].qs + q_offset;
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const uint8_t * q2 = q1 + 64;
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@ -736,7 +742,7 @@ static __global__ void dequantize_mul_mat_vec_q5_k(const void * vx, const float
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const int il = tid/4; // 0...3
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const int ir = tid - 4*il;// 0...3
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const int n = 4;
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const int n = 2;
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const int im = il/2; // 0 or 1. 0 computes 0,32 + 128,160, 1 computes 64,96 + 192,224
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const int in = il%2;
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@ -775,11 +781,16 @@ static __global__ void dequantize_mul_mat_vec_q5_k(const void * vx, const float
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float4 sum = {0.f, 0.f, 0.f, 0.f};
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float smin = 0;
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for (int l = 0; l < n; ++l) {
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sum.x += y1[l+ 0] * ((ql1[l] & 0xF) + (qh[l] & (hm1 << 0) ? 16 : 0));
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sum.y += y1[l+32] * ((ql1[l] >> 4) + (qh[l] & (hm1 << 1) ? 16 : 0));
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sum.z += y2[l+ 0] * ((ql2[l] & 0xF) + (qh[l] & (hm2 << 0) ? 16 : 0));
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sum.w += y2[l+32] * ((ql2[l] >> 4) + (qh[l] & (hm2 << 1) ? 16 : 0));
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smin += y1[l] * sc[2] + y1[l+32] * sc[3] + y2[l] * sc[6] + y2[l+32] * sc[7];
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sum.x += y1[l+ 0] * ((ql1[l+ 0] & 0xF) + (qh[l+ 0] & (hm1 << 0) ? 16 : 0))
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+ y1[l+16] * ((ql1[l+16] & 0xF) + (qh[l+16] & (hm1 << 0) ? 16 : 0));
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sum.y += y1[l+32] * ((ql1[l+ 0] >> 4) + (qh[l+ 0] & (hm1 << 1) ? 16 : 0))
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+ y1[l+48] * ((ql1[l+16] >> 4) + (qh[l+16] & (hm1 << 1) ? 16 : 0));
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sum.z += y2[l+ 0] * ((ql2[l+ 0] & 0xF) + (qh[l+ 0] & (hm2 << 0) ? 16 : 0))
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+ y2[l+16] * ((ql2[l+16] & 0xF) + (qh[l+16] & (hm2 << 0) ? 16 : 0));
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sum.w += y2[l+32] * ((ql2[l+ 0] >> 4) + (qh[l+ 0] & (hm2 << 1) ? 16 : 0))
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+ y2[l+48] * ((ql2[l+16] >> 4) + (qh[l+16] & (hm2 << 1) ? 16 : 0));
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smin += (y1[l] + y1[l+16]) * sc[2] + (y1[l+32] + y1[l+48]) * sc[3]
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+ (y2[l] + y2[l+16]) * sc[6] + (y2[l+32] + y2[l+48]) * sc[7];
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}
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tmp += dall * (sum.x * sc[0] + sum.y * sc[1] + sum.z * sc[4] + sum.w * sc[5]) - dmin * smin;
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@ -1311,7 +1322,7 @@ static void dequantize_mul_mat_vec_q8_0_cuda(const void * vx, const dfloat * y,
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static void dequantize_mul_mat_vec_q2_K_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % QK_K == 0);
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const int ny = 2;
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const int ny = 2; // very slightly faster than 1 even when K_QUANTS_PER_ITERATION = 2
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const int block_num_y = (nrows + ny - 1) / ny;
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const dim3 block_nums(1, block_num_y, 1);
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const dim3 block_dims(32, ny, 1);
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@ -1320,14 +1331,20 @@ static void dequantize_mul_mat_vec_q2_K_cuda(const void * vx, const float * y, f
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static void dequantize_mul_mat_vec_q3_K_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % QK_K == 0);
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const dim3 block_dims(32, 1, 1);
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dequantize_mul_mat_vec_q3_k<<<nrows, block_dims, 0, stream>>>(vx, y, dst, ncols);
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const int ny = 2 / K_QUANTS_PER_ITERATION;
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const int block_num_y = (nrows + ny - 1) / ny;
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const dim3 block_nums(1, block_num_y, 1);
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const dim3 block_dims(32, ny, 1);
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dequantize_mul_mat_vec_q3_k<<<block_nums, block_dims, 0, stream>>>(vx, y, dst, ncols, nrows);
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}
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static void dequantize_mul_mat_vec_q4_K_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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GGML_ASSERT(ncols % QK_K == 0);
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const dim3 block_dims(32, 1, 1);
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dequantize_mul_mat_vec_q4_k<<<nrows, block_dims, 0, stream>>>(vx, y, dst, ncols);
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const int ny = 2 / K_QUANTS_PER_ITERATION;
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const int block_num_y = (nrows + ny - 1) / ny;
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const dim3 block_nums(1, block_num_y, 1);
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const dim3 block_dims(32, ny, 1);
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dequantize_mul_mat_vec_q4_k<<<block_nums, block_dims, 0, stream>>>(vx, y, dst, ncols, nrows);
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}
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static void dequantize_mul_mat_vec_q5_K_cuda(const void * vx, const float * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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