diff --git a/ggml-cuda.cu b/ggml-cuda.cu index f890d228976f9..5a5b4e8ba3434 100644 --- a/ggml-cuda.cu +++ b/ggml-cuda.cu @@ -1721,6 +1721,32 @@ static __global__ void k_get_rows( dst_row[iybs + iqs + y_offset] = v.y; } +template +static __global__ void k_get_rows_float( + const src0_t * src0, const int32_t * src1, dst_t * dst, + int64_t ne00, /*int64_t ne01, int64_t ne02, int64_t ne03,*/ + /*int64_t ne10, int64_t ne11,*/ int64_t ne12, /*int64_t ne13,*/ + /*size_t s0,*/ size_t s1, size_t s2, size_t s3, + /*size_t nb00,*/ size_t nb01, size_t nb02, size_t nb03, + size_t s10, size_t s11, size_t s12/*, size_t s13*/) { + + const int i00 = blockIdx.x*blockDim.x + threadIdx.x; + const int i10 = blockDim.y*blockIdx.y + threadIdx.y; + const int i11 = (blockIdx.z*blockDim.z + threadIdx.z)/ne12; + const int i12 = (blockIdx.z*blockDim.z + threadIdx.z)%ne12; + + if (i00 >= ne00) { + return; + } + + const int i01 = src1[i10*s10 + i11*s11 + i12*s12]; + + dst_t * dst_row = dst + i10*s1 + i11*s2 + i12*s3; + const src0_t * src0_row = (const src0_t *)((const char *)src0 + i01*nb01 + i11*nb02 + i12*nb03); + + dst_row[i00] = src0_row[i00]; +} + template static __global__ void dequantize_block(const void * __restrict__ vx, dst_t * __restrict__ y, const int k) { const int i = blockDim.x*blockIdx.x + 2*threadIdx.x; @@ -5083,6 +5109,8 @@ static void get_rows_cuda(const ggml_tensor * src0, const ggml_tensor * src1, gg const size_t s12 = nb12 / ggml_element_size(src1); //const size_t s13 = nb13 / ggml_element_size(src1); + GGML_ASSERT(ne00 % 2 == 0); + k_get_rows<<>>( src0_dd, src1_dd, dst_dd, ne00, /*ne01, ne02, ne03,*/ @@ -5094,6 +5122,38 @@ static void get_rows_cuda(const ggml_tensor * src0, const ggml_tensor * src1, gg (void) dst; } +template +static void get_rows_cuda_float(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, + const src0_t * src0_dd, const int32_t * src1_dd, float * dst_dd, cudaStream_t stream) { + + GGML_TENSOR_BINARY_OP_LOCALS + + const dim3 block_dims(CUDA_GET_ROWS_BLOCK_SIZE, 1, 1); + const int block_num_x = (ne00 + CUDA_GET_ROWS_BLOCK_SIZE - 1) / CUDA_GET_ROWS_BLOCK_SIZE; + const dim3 block_nums(block_num_x, ne10, ne11*ne12); + + // strides in elements + //const size_t s0 = nb0 / ggml_element_size(dst); + const size_t s1 = nb1 / ggml_element_size(dst); + const size_t s2 = nb2 / ggml_element_size(dst); + const size_t s3 = nb3 / ggml_element_size(dst); + + const size_t s10 = nb10 / ggml_element_size(src1); + const size_t s11 = nb11 / ggml_element_size(src1); + const size_t s12 = nb12 / ggml_element_size(src1); + //const size_t s13 = nb13 / ggml_element_size(src1); + + k_get_rows_float<<>>( + src0_dd, src1_dd, dst_dd, + ne00, /*ne01, ne02, ne03,*/ + /*ne10, ne11,*/ ne12, /*ne13,*/ + /* s0,*/ s1, s2, s3, + /* nb00,*/ nb01, nb02, nb03, + s10, s11, s12/*, s13*/); + + (void) dst; +} + template struct bin_bcast_cuda { template @@ -6491,10 +6551,10 @@ static void ggml_cuda_op_get_rows( switch (src0->type) { case GGML_TYPE_F16: - get_rows_cuda<1, 1, convert_f16>(src0, src1, dst, src0_d, src1_i32, dst_d, stream); + get_rows_cuda_float(src0, src1, dst, (const half *)src0_d, src1_i32, dst_d, stream); break; case GGML_TYPE_F32: - get_rows_cuda<1, 1, convert_f32>(src0, src1, dst, src0_d, src1_i32, dst_d, stream); + get_rows_cuda_float(src0, src1, dst, src0_d, src1_i32, dst_d, stream); break; case GGML_TYPE_Q4_0: get_rows_cuda(src0, src1, dst, src0_d, src1_i32, dst_d, stream);