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ROCm Port (#1087)
* use hipblas based on cublas * Update Makefile for the Cuda kernels * Expand arch list and make it overrideable * Fix multi GPU on multiple amd architectures with rocblas_initialize() (#5) * add hipBLAS to README * new build arg LLAMA_CUDA_MMQ_Y * fix half2 decomposition * Add intrinsics polyfills for AMD * AMD assembly optimized __dp4a * Allow overriding CC_TURING * use "ROCm" instead of "CUDA" * ignore all build dirs * Add Dockerfiles * fix llama-bench * fix -nommq help for non CUDA/HIP --------- Co-authored-by: YellowRoseCx <80486540+YellowRoseCx@users.noreply.github.com> Co-authored-by: ardfork <134447697+ardfork@users.noreply.github.com> Co-authored-by: funnbot <22226942+funnbot@users.noreply.github.com> Co-authored-by: Engininja2 <139037756+Engininja2@users.noreply.github.com> Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com> Co-authored-by: jammm <2500920+jammm@users.noreply.github.com> Co-authored-by: jdecourval <7315817+jdecourval@users.noreply.github.com>
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@@ -613,9 +613,11 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
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fprintf(stdout, " how to split tensors across multiple GPUs, comma-separated list of proportions, e.g. 3,1\n");
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fprintf(stdout, " -mg i, --main-gpu i the GPU to use for scratch and small tensors\n");
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fprintf(stdout, " -lv, --low-vram don't allocate VRAM scratch buffer\n");
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#ifdef GGML_USE_CUBLAS
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fprintf(stdout, " -nommq, --no-mul-mat-q\n");
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fprintf(stdout, " use cuBLAS instead of custom mul_mat_q CUDA kernels.\n");
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fprintf(stdout, " use " GGML_CUBLAS_NAME " instead of custom mul_mat_q " GGML_CUDA_NAME " kernels.\n");
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fprintf(stdout, " Not recommended since this is both slower and uses more VRAM.\n");
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#endif // GGML_USE_CUBLAS
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#endif
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fprintf(stdout, " --mtest compute maximum memory usage\n");
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fprintf(stdout, " --export export the computation graph to 'llama.ggml'\n");
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