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CUDA: add mean operation (#14313)
* CUDA: add mean operation * add back sum_rows_f32_cuda * Review: early exit if col!=0
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@@ -1,25 +1,9 @@
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#include "sumrows.cuh"
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static __global__ void k_sum_rows_f32(const float * x, float * dst, const int ncols) {
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const int row = blockIdx.x;
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const int col = threadIdx.x;
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float sum = 0.0f;
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for (int i = col; i < ncols; i += blockDim.x) {
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sum += x[row * ncols + i];
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}
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sum = warp_reduce_sum(sum);
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if (col == 0) {
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dst[row] = sum;
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}
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}
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void sum_rows_f32_cuda(const float * x, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
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const dim3 block_dims(WARP_SIZE, 1, 1);
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const dim3 block_nums(nrows, 1, 1);
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k_sum_rows_f32<<<block_nums, block_dims, 0, stream>>>(x, dst, ncols);
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reduce_rows_f32</*norm*/false><<<block_nums, block_dims, 0, stream>>>(x, dst, ncols);
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}
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void ggml_cuda_op_sum_rows(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
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@@ -35,5 +19,8 @@ void ggml_cuda_op_sum_rows(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
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const int64_t ncols = src0->ne[0];
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const int64_t nrows = ggml_nrows(src0);
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sum_rows_f32_cuda(src0_d, dst_d, ncols, nrows, stream);
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const dim3 block_dims(WARP_SIZE, 1, 1);
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const dim3 block_nums(nrows, 1, 1);
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reduce_rows_f32</*norm=*/false><<<block_nums, block_dims, 0, stream>>>(src0_d, dst_d, ncols);
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}
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