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https://github.com/vale981/ray
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48 lines
1.3 KiB
ReStructuredText
48 lines
1.3 KiB
ReStructuredText
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.. _sgd-arch:
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Architecture
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============
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A diagram of the RaySGD architecture is provided below.
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.. image:: sgd-arch.svg
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:width: 70%
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:align: center
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Trainer
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-------
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The Trainer is the main class that is exposed in the RaySGD API that users will interact with.
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* The user will pass in a *function* which defines the training logic.
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* The Trainer will create an :ref:`Executor <sgd-arch-executor>` to run the distributed training.
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* The Trainer will handle callbacks based on the results from the BackendExecutor.
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.. _sgd-arch-executor:
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Executor
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--------
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The executor is an interface which handles execution of distributed training.
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* The executor will handle the creation of an actor group and will be initialized in conjunction with a backend.
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* Worker resources, number of workers, and placement strategy will be passed to the Worker Group.
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Backend
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-------
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A backend is used in conjunction with the executor to initialize and manage framework-specific communication protocols.
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Each communication library (Torch, Horovod, TensorFlow, etc.) will have a separate backend and will take a specific configuration value.
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WorkerGroup
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-----------
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The WorkerGroup is a generic utility class for managing a group of Ray Actors.
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* This is similar in concept to Fiber's `Ring <https://uber.github.io/fiber/experimental/ring/>`_.
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