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@@ -410,19 +410,27 @@ Building the program with BLAS support may lead to some performance improvements
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This provides BLAS acceleration on HIP-supported AMD GPUs.
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Make sure to have ROCm installed.
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You can download it from your Linux distro's package manager or from here: [ROCm Quick Start (Linux)](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html).
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- Windows support is coming soon...
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- Using `make`:
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```bash
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make LLAMA_HIPBLAS=1
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```
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- - Using `CMake`:
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+ - Using `CMake` for Linux:
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```bash
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mkdir build
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cd build
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CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++ cmake .. -DLLAMA_HIPBLAS=ON
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cmake --build .
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```
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+ - Using `CMake` for Windows:
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+ ```bash
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+ mkdir build
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+ cd build
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+ cmake -G Ninja -DAMDGPU_TARGETS=gfx1100 -DLLAMA_HIPBLAS=ON -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ ..
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+ cmake --build .
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+ ```
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+ Make sure that `AMDGPU_TARGETS` is set to the GPU arch you want to compile for. The above example uses `gfx1100` that corresponds to Radeon RX 7900XTX/XT/GRE. You can find a list of targets [here](https://llvm.org/docs/AMDGPUUsage.html#processors)
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+
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The environment variable [`HIP_VISIBLE_DEVICES`](https://rocm.docs.amd.com/en/latest/understand/gpu_isolation.html#hip-visible-devices) can be used to specify which GPU(s) will be used.
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If your GPU is not officially supported you can use the environment variable [`HSA_OVERRIDE_GFX_VERSION`] set to a similar GPU, for example 10.3.0 on RDNA2 or 11.0.0 on RDNA3.
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