CUDA: mul_mat_vec_q max. batch size 8 -> 4 (#5370)

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Johannes Gäßler 2024-02-06 18:43:06 +01:00 committed by GitHub
parent b08f22c882
commit 17c97fb062
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@ -6831,7 +6831,7 @@ static void mul_mat_vec_q_cuda(
const int ncols_x, const int nrows_x, const int nrows_y, const int ncols_y, cudaStream_t stream) { const int ncols_x, const int nrows_x, const int nrows_y, const int ncols_y, cudaStream_t stream) {
GGML_ASSERT(ncols_x % qk == 0); GGML_ASSERT(ncols_x % qk == 0);
GGML_ASSERT(ncols_y <= 8); GGML_ASSERT(ncols_y <= 4);
const int block_num_y = (nrows_x + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y; const int block_num_y = (nrows_x + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y;
const dim3 block_nums(block_num_y, 1, 1); const dim3 block_nums(block_num_y, 1, 1);
@ -6853,22 +6853,22 @@ static void mul_mat_vec_q_cuda(
mul_mat_vec_q<4, qk, qi, block_q_t, vdr, vec_dot> mul_mat_vec_q<4, qk, qi, block_q_t, vdr, vec_dot>
<<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y); <<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y);
break; break;
case 5: // case 5:
mul_mat_vec_q<5, qk, qi, block_q_t, vdr, vec_dot> // mul_mat_vec_q<5, qk, qi, block_q_t, vdr, vec_dot>
<<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y); // <<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y);
break; // break;
case 6: // case 6:
mul_mat_vec_q<6, qk, qi, block_q_t, vdr, vec_dot> // mul_mat_vec_q<6, qk, qi, block_q_t, vdr, vec_dot>
<<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y); // <<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y);
break; // break;
case 7: // case 7:
mul_mat_vec_q<7, qk, qi, block_q_t, vdr, vec_dot> // mul_mat_vec_q<7, qk, qi, block_q_t, vdr, vec_dot>
<<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y); // <<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y);
break; // break;
case 8: // case 8:
mul_mat_vec_q<8, qk, qi, block_q_t, vdr, vec_dot> // mul_mat_vec_q<8, qk, qi, block_q_t, vdr, vec_dot>
<<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y); // <<<block_nums, block_dims, 0, stream>>>(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y);
break; // break;
default: default:
GGML_ASSERT(false); GGML_ASSERT(false);
// mul_mat_vec_q<0, qk, qi, block_q_t, vdr, vec_dot> // mul_mat_vec_q<0, qk, qi, block_q_t, vdr, vec_dot>
@ -9909,7 +9909,7 @@ static void ggml_cuda_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1
ggml_cuda_op_mul_mat(src0, src1, dst, ggml_cuda_op_dequantize_mul_mat_vec, false); ggml_cuda_op_mul_mat(src0, src1, dst, ggml_cuda_op_dequantize_mul_mat_vec, false);
} }
} else { } else {
if (src1->ne[1] <= 8 && min_compute_capability >= MIN_CC_DP4A && ggml_is_quantized(src0->type)) { if (src1->ne[1] <= 4 && min_compute_capability >= MIN_CC_DP4A && ggml_is_quantized(src0->type)) {
ggml_cuda_op_mul_mat(src0, src1, dst, ggml_cuda_op_mul_mat_vec_q, true); ggml_cuda_op_mul_mat(src0, src1, dst, ggml_cuda_op_mul_mat_vec_q, true);
} else if (use_mul_mat_q) { } else if (use_mul_mat_q) {
ggml_cuda_op_mul_mat(src0, src1, dst, ggml_cuda_op_mul_mat_q, true); ggml_cuda_op_mul_mat(src0, src1, dst, ggml_cuda_op_mul_mat_q, true);