running.rst

Run Horovod

This page includes examples for Open MPI that use horovodrun. Check your MPI documentation for arguments to the mpirun command on your system.

Typically one GPU will be allocated per process, so if a server has 4 GPUs, you would run 4 processes. In horovodrun, the number of processes is specified with the -np flag.

To run on a machine with 4 GPUs:

$ horovodrun -np 4 -H localhost:4 python train.py

To run on 4 machines with 4 GPUs each:

$ horovodrun -np 16 -H server1:4,server2:4,server3:4,server4:4 python train.py

Failures due to SSH issues

The host where horovodrun is executed must be able to SSH to all other hosts without any prompts.

If horovodrun fails with permission error, verify that you can ssh to every other server without entering a password or answering questions like this:

The authenticity of host '<hostname> (<ip address>)' can't be established. RSA key fingerprint is xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx. Are you sure you want to continue connecting (yes/no)?

To learn more about setting up passwordless authentication, see this page.

To avoid The authenticity of host '<hostname> (<ip address>)' can't be established prompts, add all the hosts to the ~/.ssh/known_hosts file using ssh-keyscan:

$ ssh-keyscan -t rsa,dsa server1 server2 > ~/.ssh/known_hosts

Advanced: Run Horovod with Open MPI

In some advanced cases you might want fine-grained control over options passed to Open MPI. To learn how run Horovod training directly using Open MPI, read Run Horovod with Open MPI.