Horovod Horovod fails with 'no such device'

What is Horovod Horovod fails with 'no such device'

Understanding Horovod

Horovod is an open-source distributed deep learning framework that makes it easy to train models across multiple GPUs and nodes. It is built on top of popular deep learning frameworks like TensorFlow, Keras, PyTorch, and Apache MXNet, and is designed to improve the speed and efficiency of training large-scale models.

Identifying the Symptom

When using Horovod, you might encounter an error message that reads: 'no such device'. This error typically occurs during the initialization phase of a distributed training session.

What You Observe

The training process fails to start, and the error message is logged, indicating that Horovod cannot access a specified device.

Explaining the Issue

The error message 'no such device' suggests that Horovod is attempting to access a GPU or other hardware device that does not exist or is not available on the system. This can happen if the device IDs specified in the configuration are incorrect or if the hardware is not properly configured.

Common Causes

Incorrect device IDs specified in the training script. Hardware devices not properly installed or recognized by the system. Misconfiguration of environment variables related to device visibility.

Steps to Fix the Issue

To resolve the 'no such device' error, follow these steps:

Step 1: Verify Device Availability

Ensure that the devices you intend to use are available and properly configured. You can list available GPUs using the following command:

nvidia-smi

This command will display a list of all GPUs recognized by the system. Ensure that the device IDs you plan to use are listed.

Step 2: Check Device IDs

Review your training script to ensure that the correct device IDs are specified. For example, in a TensorFlow script, you might specify devices like this:

with tf.device('/gpu:0'):

Ensure that the device IDs match those listed by nvidia-smi.

Step 3: Configure Environment Variables

Ensure that environment variables related to device visibility are correctly set. For instance, you can limit visible devices using:

export CUDA_VISIBLE_DEVICES=0,1

This command restricts the visible devices to GPUs 0 and 1.

Additional Resources

For more information on configuring and troubleshooting Horovod, refer to the following resources:

Horovod Documentation NVIDIA System Management Interface TensorFlow GPU Guide