Train a CNN Model on Multiple Intel® Arc™ GPUs | Intel Software

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Distributed training for deep learning usually requires datacenter or cloud platform. Watch this demo to learn how to perform distributed training of a TensorFlow CNN model using a PC with two Intel® Arc™ 380 GPUs.

Training deep learning models usually requires distributing the workload across multiple GPUs, which typically means you need access to cloud or enterprise platforms.

This demo walks through an example available in Intel® Extension for TensorFlow*. This example shows how to perform distributed training of a CNN model on a PC with 2 Intel® Arc™ 380 GPUs. It leverages Intel® Optimization for Horovod*, which speeds up distributed training running on Intel GPUs.

The video walks through the steps so you can follow along to download and install all the tools necessary to run this distributed training workload.

Example: https://github.com/intel/intel-extension-for-tensorflow/tree/main/examples/train_horovod/mnist

Intel Extension for TensorFlow: https://www.intel.com/content/www/us/en/developer/tools/oneapi/optimization-for-tensorflow.html

Intel AI Software: https://www.developer.intel.com/ai

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Train a CNN Model on Multiple Intel® Arc™ GPUs | Intel Software




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