#include "concat.cuh" static __global__ void concat_f32_dim0(const float * x, const float * y, float * dst, const int ne0, const int ne00) { int nidx = threadIdx.x + blockIdx.x * blockDim.x; if (nidx >= ne0) { return; } int offset_dst = nidx + blockIdx.y * ne0 + blockIdx.z * ne0 * gridDim.y; if (nidx < ne00) { // src0 int offset_src = nidx + blockIdx.y * ne00 + blockIdx.z * ne00 * gridDim.y; dst[offset_dst] = x[offset_src]; } else { int offset_src = (nidx - ne00) + blockIdx.y * (ne0 - ne00) + blockIdx.z * (ne0 - ne00) * gridDim.y; dst[offset_dst] = y[offset_src]; } } static __global__ void concat_f32_dim1(const float * x, const float * y, float * dst, const int ne0, const int ne01) { int nidx = threadIdx.x + blockIdx.x * blockDim.x; if (nidx >= ne0) { return; } int offset_dst = nidx + blockIdx.y * ne0 + blockIdx.z * ne0 * gridDim.y; if (blockIdx.y < ne01) { // src0 int offset_src = nidx + blockIdx.y * ne0 + blockIdx.z * ne0 * ne01; dst[offset_dst] = x[offset_src]; } else { int offset_src = nidx + (blockIdx.y - ne01) * ne0 + blockIdx.z * ne0 * (gridDim.y - ne01); dst[offset_dst] = y[offset_src]; } } static __global__ void concat_f32_dim2(const float * x, const float * y, float * dst, const int ne0, const int ne02) { int nidx = threadIdx.x + blockIdx.x * blockDim.x; if (nidx >= ne0) { return; } int offset_dst = nidx + blockIdx.y * ne0 + blockIdx.z * ne0 * gridDim.y; if (blockIdx.z < ne02) { // src0 int offset_src = nidx + blockIdx.y * ne0 + blockIdx.z * ne0 * gridDim.y; dst[offset_dst] = x[offset_src]; } else { int offset_src = nidx + blockIdx.y * ne0 + (blockIdx.z - ne02) * ne0 * gridDim.y; dst[offset_dst] = y[offset_src]; } } static void concat_f32_cuda(const float * x, const float * y, float * dst, int ne00, int ne01, int ne02, int ne0, int ne1, int ne2, int dim, cudaStream_t stream) { int num_blocks = (ne0 + CUDA_CONCAT_BLOCK_SIZE - 1) / CUDA_CONCAT_BLOCK_SIZE; dim3 gridDim(num_blocks, ne1, ne2); if (dim == 0) { concat_f32_dim0<<>>(x, y, dst, ne0, ne00); return; } if (dim == 1) { concat_f32_dim1<<>>(x, y, dst, ne0, ne01); return; } concat_f32_dim2<<>>(x, y, dst, ne0, ne02); } void ggml_cuda_op_concat(ggml_backend_cuda_context & ctx, ggml_tensor * dst) { const ggml_tensor * src0 = dst->src[0]; const ggml_tensor * src1 = dst->src[1]; const float * src0_d = (const float *)src0->data; const float * src1_d = (const float *)src1->data; float * dst_d = (float *)dst->data; cudaStream_t stream = ctx.stream(); const int32_t dim = ((int32_t *) dst->op_params)[0]; GGML_ASSERT(ggml_is_contiguous(src0)); GGML_ASSERT(ggml_is_contiguous(src1)); GGML_ASSERT(src0->type == GGML_TYPE_F32); GGML_ASSERT(src1->type == GGML_TYPE_F32); GGML_ASSERT(dst->type == GGML_TYPE_F32); if (dim != 3) { for (int i3 = 0; i3 < dst->ne[3]; i3++) { concat_f32_cuda( src0_d + i3 * (src0->nb[3] / 4), src1_d + i3 * (src1->nb[3] / 4), dst_d + i3 * ( dst->nb[3] / 4), src0->ne[0], src0->ne[1], src0->ne[2], dst->ne[0], dst->ne[1], dst->ne[2], dim, stream); } } else { const size_t size0 = ggml_nbytes(src0); const size_t size1 = ggml_nbytes(src1); CUDA_CHECK(cudaMemcpyAsync(dst_d, src0_d, size0, cudaMemcpyDeviceToDevice, stream)); CUDA_CHECK(cudaMemcpyAsync(dst_d + size0/4, src1_d, size1, cudaMemcpyDeviceToDevice, stream)); } }