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NCCL tests

This example shows how to run distributed NCCL tests :material-arrow-top-right-thin:{ .external }{:target="_blank"} with MPI using dstack.

Running as a task

Here's an example of a task that runs AllReduce test on 2 nodes, each with 4 GPUs (8 processes in total).

type: task
name: nccl-tests

nodes: 2
startup_order: workers-first
stop_criteria: master-done

image: dstackai/efa
env:
  - NCCL_DEBUG=INFO
commands:
  - cd /root/nccl-tests/build
  - |
    if [ $DSTACK_NODE_RANK -eq 0 ]; then
      mpirun \
        --allow-run-as-root \
        --hostfile $DSTACK_MPI_HOSTFILE \
        -n $DSTACK_GPUS_NUM \
        -N $DSTACK_GPUS_PER_NODE \
        --mca btl_tcp_if_exclude lo,docker0 \
        --bind-to none \
        ./all_reduce_perf -b 8 -e 8G -f 2 -g 1
    else
      sleep infinity
    fi

resources:
  gpu: nvidia:4:16GB
  shm_size: 16GB

!!! info "Docker image" The dstackai/efa image used in the example comes with MPI and NCCL tests pre-installed. While it is optimized for AWS EFA :material-arrow-top-right-thin:{ .external }{:target="_blank"}, it can also be used with regular TCP/IP network adapters and InfiniBand.

See the [source code :material-arrow-top-right-thin:{ .external }](https://github.com/dstackai/dstack/blob/master/docker/efa) for the image.

Apply a configuration

To run a configuration, use the dstack apply command.

$ dstack apply -f examples/clusters/nccl-tests/.dstack.yml

 #  BACKEND  REGION     INSTANCE       RESOURCES                                   SPOT  PRICE
 1  aws      us-east-1  g4dn.12xlarge  48xCPU, 192GB, 4xT4 (16GB), 100.0GB (disk)  no    $3.912
 2  aws      us-west-2  g4dn.12xlarge  48xCPU, 192GB, 4xT4 (16GB), 100.0GB (disk)  no    $3.912
 3  aws      us-east-2  g4dn.12xlarge  48xCPU, 192GB, 4xT4 (16GB), 100.0GB (disk)  no    $3.912

Submit the run nccl-tests? [y/n]: y

Source code

The source-code of this example can be found in examples/clusters/nccl-tests :material-arrow-top-right-thin:{ .external }.

What's next?

  1. Check dev environments, tasks, services, and fleets.