Intel® Optimization for Horovod* is the distributed training framework for TensorFlow* and PyTorch*. 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 v0.26.1 of public Horovod.

Install

Hardware Requirements

• Intel® Data Center GPU Max Series, Driver Version: 602

Software Requirement

• Note: The patched PyTorch 1.13.0a0 is required to work with Intel® Extension for PyTorch* on Intel® graphics card for now.

Software	Installation requirement
Intel® oneAPI Base Toolkit	Install Intel® oneAPI Base Toolkit
TensorFlow	Install tensorflow 2.12.0
Intel® Extension for TensorFlow*	Install Intel® Extension for TensorFlow*
Pytorch	Install Pytorch 1.13.0a0
Intel® Extension for Pytorch*	Install Intel® Extension for Pytorch*
System	Ubuntu 22.04, RedHat 8.6 (64-bit), SUSE Linux Enterprise Server(SLES) 15 SP3/SP4
Python	3.8-3.10
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 602, 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 either Intel® Extension for TensorFlow* or Intel® Extension for Pytorch* as dependency.

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

   pip install tensorflow==2.12.0
   pip install --upgrade intel-extension-for-tensorflow[gpu]
   pip install intel-optimization-for-horovod

2. Installing Intel® Extension for Pytorch* and Intel® Optimization for Horovod* with command:

   python -m pip install torch==1.13.0a0 -f https://developer.intel.com/ipex-whl-stable-xpu
   python -m pip install intel_extension_for_pytorch==1.13.120+xpu -f https://developer.intel.com/ipex-whl-stable-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.