Deprecation Notice

PROJECT NOT UNDER ACTIVE MANAGEMENT

This project will no longer be maintained by Intel.

Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project.

Intel no longer accepts patches to this project. If you have an ongoing need to use this project, are interested in independently developing it, or would like to maintain patches for the open source software community, please create your own fork of this project.

Thanks to all the contributors and users who supported this project!

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Intel® Optimization for Horovod* is the distributed training framework for TensorFlow*. The goal is to make distributed Deep Learning workload run faster and easier to use on Intel GPU devices. It's developed based on latest release version v0.28.1 of public Horovod.

Install

Hardware Requirements

• Intel® Data Center GPU Max Series, Driver Version: 803

Software	Installation requirement
Intel® oneAPI Base Toolkit	Install Intel® oneAPI Base Toolkit
TensorFlow	Install tensorflow 2.15.1
Intel® Extension for TensorFlow*	Install Intel® Extension for TensorFlow*
System	Ubuntu 22.04, SUSE Linux Enterprise Server(SLES) 15 SP3/SP4
Python	3.9-3.11
Pip	19.0 or later (requires manylinux2014 support)

Install GPU Drivers

OS	Intel GPU	Install Intel GPU Driver
Ubuntu 22.04, RedHat 8.6, SLES 15 SP3/SP4	Intel® Data Center GPU Max Series	Refer to the Installation Guides for latest driver installation. If install the verified Intel® Data Center GPU Max Series/Intel® Data Center GPU Flex Series 803, please append the specific version after components.

Installation Channel:

Intel® Optimization for Horovod* can be installed through the following channels:

PyPI	Source
Install from pip	Build from source

Install for GPU

Installing Intel® Optimization for Horovod* with different frameworks is feasible. You could choose Intel® Extension for TensorFlow* as dependency.

1. Installing Intel® Extension for TensorFlow* and Intel® Optimization for Horovod* with command:
   

   pip install tensorflow==2.15.1
   pip install --upgrade intel-extension-for-tensorflow[xpu]
   pip install intel-optimization-for-horovod

Running Intel® Optimization for Horovod*

The example commands below show how to run distributed training.

1. To run on a machine with 2 Intel GPUs, which have 4 titles totally.

   horovodrun -np 4 python train.py

2. To run on 4 machines with 2 GPUs(4 tiles) each:

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

Running Intel® Optimization for Horovod* with tensorflow on Intel GPU

It is easy to train models with Intel® Extension for TensorFlow. You can refer to tensorflow examples for more details