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@@ -82,6 +82,9 @@ If using Open MPI, the status of CUDA support can be checked via the
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If your MPI implementation has been compiled with ROCm support (AMDGPU), then `AMDGPU.ROCArray`s (from the
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[AMDGPU.jl](https://github.com/JuliaGPU/AMDGPU.jl) package) can be passed directly as send and receive buffers for point-to-point and collective operations (they may also work with one-sided operations, but these are not often supported).
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Successfully running the [alltoall_test_rocm.jl](https://gist.github.com/luraess/c228ec08629737888a18c6a1e397643c) should confirm your MPI implementation to have the ROCm support (AMDGPU) enabled. Moreover, successfully running the [alltoall_test_rocm_mulitgpu.jl](https://gist.github.com/luraess/d478b3f98eae984931fd39a7158f4b9e) should confirm your ROCm-aware MPI implementation to use multiple AMD GPUs (one GPU per rank).
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Successfully running the [alltoall\_test\_rocm.jl](https://gist.github.com/luraess/c228ec08629737888a18c6a1e397643c)
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should confirm your MPI implementation to have the ROCm support (AMDGPU) enabled. Moreover, successfully running the
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[alltoall\_test\_rocm\_multigpu.jl](https://gist.github.com/luraess/a47931d7fb668bd4348a2c730d5489f4) should confirm
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your ROCm-aware MPI implementation to use multiple AMD GPUs (one GPU per rank).
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The status of ROCm (AMDGPU) support cannot currently be queried.
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