Horovod
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About
Horovod is a powerful distributed deep learning training framework developed by Uber. It supports frameworks like TensorFlow, Keras, PyTorch, and Apache MXNet, allowing users to scale their model training across hundreds of GPUs with minimal coding effort. Horovod significantly reduces model training times from days and weeks to hours and minutes. It can be installed on-premise or utilized on cloud platforms such as AWS, Azure, and Databricks, and it is also compatible with Apache Spark for streamlined data processing and model training pipelines. The platform is open source under the LF AI Foundation and encourages community contributions.
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Features
• open source project with community involvement
• integration with apache spark for unified data processing and model training
• compatibility with on-premise and cloud environments
• easy integration with just a few lines of python code
• fast distributed deep learning with up to 90% scaling efficiency
• support for tensorflow, keras, pytorch, and apache mxnet
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