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NCCL tests rely on MPI to run on multiple processes. The master node (`DSTACK_NODE_RANK=0`) generates `hostfile` (using `DSTACK_NODES_IPS`)
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and waits until other nodes are accessible via MPI.
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Then, it executes `/nccl-tests/build/all_reduce_perf` across all GPUs.
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Non-master nodes use a `FIFO` pipe to wait for until the MPI run is finished.
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There is an open [issue :material-arrow-top-right-thin:{ .external }](https://github.com/dstackai/dstack/issues/2467){:target="_blank"} to simplify the use of MPI with distributed tasks.
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!!! info "Docker image"
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The `dstackai/efa` image used in the example comes with MPI and NCCL tests pre-installed. While it is optimized for
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[AWS EFA :material-arrow-top-right-thin:{ .external }](https://aws.amazon.com/hpc/efa/){:target="_blank"}, it can also
@@ -84,7 +56,7 @@ To run a configuration, use the [`dstack apply`](https://dstack.ai/docs/referenc
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