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# Sagemaker Distributed Data Parallel - Release Notes
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- First Release
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- Getting Started
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## First Release
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SageMaker's distributed data parallel library extends SageMaker’s training
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capabilities on deep learning models with near-linear scaling efficiency,
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achieving fast time-to-train with minimal code changes.
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SageMaker Distributed Data Parallel :
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- optimizes your training job for AWS network infrastructure and EC2 instance topology.
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- takes advantage of gradient update to communicate between nodes with a custom AllReduce algorithm.
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The library currently supports Tensorflow v2 and PyTorch via [AWS Deep Learning Containers](https://aws.amazon.com/machine-learning/containers/).
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## Getting Started
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For getting started, refer to [SageMaker Distributed Data Parallel Python SDK Guide](https://docs.aws.amazon.com/sagemaker/latest/dg/data-parallel-use-api.html#data-parallel-use-python-skd-api).

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