From a62bcc891cccdd3c3a6eb3d60e034726b69705b8 Mon Sep 17 00:00:00 2001 From: JohannesGaessler Date: Thu, 27 Jul 2023 21:39:04 +0200 Subject: [PATCH] q3_k --- ggml-cuda.cu | 72 +++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 71 insertions(+), 1 deletion(-) diff --git a/ggml-cuda.cu b/ggml-cuda.cu index 4b51c3757..d1ae5076a 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -1861,6 +1861,61 @@ static __device__ __forceinline__ float vec_dot_q3_K_q8_1( return vec_dot_q3_K_q8_1_impl(vl, vh, u, bq3_K->scales, scale_offset, d, d8); } +static __device__ __forceinline__ void allocate_tiles_q3_K(int ** x_ql, half2 ** x_dm, int ** x_qh, int ** x_sc) { + + __shared__ int tile_x_ql[(2*WARP_SIZE) * (WARP_SIZE + 1)]; + __shared__ half2 tile_x_dm[(2*WARP_SIZE) * (WARP_SIZE / QI2_K)]; + __shared__ int tile_x_qh[(2*WARP_SIZE) * (WARP_SIZE / 2)]; + __shared__ int tile_x_sc[(2*WARP_SIZE) * (WARP_SIZE / 4)]; + + *x_ql = tile_x_ql; + *x_dm = tile_x_dm; + *x_qh = tile_x_qh; + *x_sc = tile_x_sc; +} + +static __device__ __forceinline__ void load_tiles_q3_K( + const void * __restrict__ vx, int * __restrict__ x_ql, half2 * __restrict__ x_dm, int * __restrict__ x_qh, + int * __restrict__ x_sc, const int & i, const int & k, const int & blocks_per_row) { + + const int kbx = k / QI3_K; + const int kqsx = k % QI3_K; + + const block_q3_K * bx = ((block_q3_K *) vx) + i*blocks_per_row + kbx; + + x_ql[i * (WARP_SIZE + 1) + k] = get_int_from_uint8(bx->qs, kqsx); + x_dm[i * (WARP_SIZE / QI3_K) + kbx].x = bx->d; + x_qh[i * (WARP_SIZE / 2) + k/2] = get_int_from_uint8(bx->hmask, kqsx / 2); + x_sc[i * (WARP_SIZE / 4) + k/4] = get_int_from_uint8(bx->scales, kqsx / 4); +} + +static __device__ __forceinline__ float vec_dot_q3_K_q8_1_mul_mat( + const int * __restrict__ x_ql, const half2 * __restrict__ x_dm, const int * __restrict__ x_qh, const int * __restrict__ x_sc, + const int * __restrict__ y_qs, const half2 * __restrict__ y_ds, const int & i, const int & j, const int & k) { + + const int kbx = k / QI3_K; + const int kqsx = k % QI3_K; + + const int bq8_offset = QR3_K * (kqsx / (QI3_K/2)); + const int scale_offset = kqsx - kqsx % QI8_1 + (kqsx % QI8_1) / (QI8_1/2); + + const uint8_t * scales = ((uint8_t *) (x_sc + i * (WARP_SIZE/4))) + kbx*16; + + // invert the mask with ~ so that a 0/1 results in 4/0 being subtracted + const int vh = ~x_qh[i * (WARP_SIZE/2) + kbx * (QI3_K/2) + kqsx % (QI3_K/2)] >> bq8_offset; + + int u[QR3_K]; + float d8[QR3_K]; + + for (int l = 0; l < QR3_K; ++ l) { + const int y_qs_index = j * (QR3_K*WARP_SIZE) + kbx * (QR3_K*QI3_K) + (bq8_offset + l)*QI8_1 + kqsx % QI8_1; + u[l] = y_qs[y_qs_index]; + d8[l] = y_ds[y_qs_index / QI8_1].x; + } + + return vec_dot_q3_K_q8_1_impl(x_ql[i * (WARP_SIZE + 1) + k], vh, u, scales, scale_offset, x_dm[i * (WARP_SIZE/QI2_K) + kbx].x, d8); +} + static __device__ __forceinline__ float vec_dot_q4_K_q8_1_impl( const int * v, const int * u, const uint8_t * sc, const uint8_t * m, const half2 & dm4, const float * d8) { @@ -3070,6 +3125,18 @@ static void ggml_mul_mat_q2_K_q8_1_cuda( <<>>(vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst); } +static void ggml_mul_mat_q3_K_q8_1_cuda( + const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, + const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { + + const int block_num_x = (nrows_x + 2*WARP_SIZE - 1) / (2*WARP_SIZE); + const int block_num_y = (ncols_y + WARP_SIZE - 1) / WARP_SIZE; + const dim3 block_nums(block_num_x, block_num_y, 1); + const dim3 block_dims(WARP_SIZE, WARP_SIZE/4, 1); + mul_mat_q + <<>>(vx, vy, dst, ncols_x, nrows_x, ncols_y, nrows_y, nrows_dst); +} + static void ggml_mul_mat_q6_K_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int ncols_y, const int nrows_y, const int nrows_dst, cudaStream_t stream) { @@ -3598,6 +3665,9 @@ inline void ggml_cuda_op_mul_mat_q( case GGML_TYPE_Q2_K: ggml_mul_mat_q2_K_q8_1_cuda(src0_ddq_i, src1_q8_1, dst_ddf_i, ne00, i01_diff, ne11, padded_row_size, nrows_dst, cudaStream_main); break; + case GGML_TYPE_Q3_K: + ggml_mul_mat_q3_K_q8_1_cuda(src0_ddq_i, src1_q8_1, dst_ddf_i, ne00, i01_diff, ne11, padded_row_size, nrows_dst, cudaStream_main); + break; case GGML_TYPE_Q6_K: ggml_mul_mat_q6_K_q8_1_cuda(src0_ddq_i, src1_q8_1, dst_ddf_i, ne00, i01_diff, ne11, padded_row_size, nrows_dst, cudaStream_main); break; @@ -4370,7 +4440,7 @@ void ggml_cuda_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1, ggml_ } else { if (src0->type == GGML_TYPE_Q4_0 || src0->type == GGML_TYPE_Q4_1 || src0->type == GGML_TYPE_Q5_0 || src0->type == GGML_TYPE_Q5_1 || src0->type == GGML_TYPE_Q8_0 || - src0->type == GGML_TYPE_Q2_K || src0->type == GGML_TYPE_Q6_K) { + src0->type == GGML_TYPE_Q2_K || src0->type == GGML_TYPE_Q3_K || src0->type == GGML_TYPE_Q6_K) { ggml_cuda_op(src0, src1, dst, ggml_cuda_op_mul_mat_q, false, false); } else { ggml_cuda_op(src0, src1, dst, ggml_cuda_op_mul_mat_cublas, true, false);