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@@ -3529,13 +3529,12 @@ static void ggml_cuda_op(const ggml_tensor * src0, const ggml_tensor * src1, ggm
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if (split) {
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// src0 = weight matrix is saved as a transposed matrix for better memory layout.
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// dst is NOT transposed.
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- // The outputs of cuBLAS matrix matrix multiplications can therefore NOT simply be concatenated for >1 GPU.
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+ // The outputs of matrix matrix multiplications can therefore NOT simply be concatenated for >1 GPU.
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// Instead they need to be copied to the correct slice in ne0 = dst row index.
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// If dst is a vector with ne0 == 1 then you don't have to do this but it still produces correct results.
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- for (int64_t j = 0; j < ne1; ++j) {
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- float * dhf_dst_i = (float *) ((char *) dst_off_device + (j*ne0 + i01_low)*sizeof(float) + i02*nb2 + i03*nb3);
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- CUDA_CHECK(cudaMemcpyAsync(dhf_dst_i, dst_ddf_i + j*i01_diff, i01_diff*sizeof(float), kind, cudaStream_main));
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- }
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+ float * dhf_dst_i = (float *) ((char *) dst_off_device + i01_low*sizeof(float) + i02*nb2 + i03*nb3);
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+ CUDA_CHECK(cudaMemcpy2DAsync(dhf_dst_i, ne0*sizeof(float), dst_ddf_i, i01_diff*sizeof(float),
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+ i01_diff*sizeof(float), ne1, kind, cudaStream_main));
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} else {
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float * dhf_dst_i = (float *) ((char *) dst_off_device + i02*nb2 + i03*nb3);
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CUDA_CHECK(cudaMemcpyAsync(dhf_dst_i, dst_ddf_i, dst_stride*sizeof(float), kind, cudaStream_main));
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