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817 B
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23 lines
817 B
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RaySGD: Distributed Deep Learning
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=================================
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.. image:: raysgdlogo.png
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:scale: 20%
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:align: center
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RaySGD is a lightweight library for distributed deep learning, providing thin wrappers around framework-native modules for data parallel training.
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The main features are:
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- Ease of use: Scale Pytorch's native ``DistributedDataParallel`` and TensorFlow's ``tf.distribute.MirroredStrategy`` without needing to monitor individual nodes.
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- Composibility: RaySGD is built on top of the Ray Actor API, enabling seamless integration with existing Ray applications such as RLlib, Tune, and Ray.Serve.
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- Scale up and down: Start on single CPU. Scale up to multi-node, multi-gpu by changing 2 lines of code.
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.. toctree::
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raysgd_pytorch.rst
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raysgd_tensorflow.rst
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raysgd_ft.rst
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