Distributed Training with Amazon SageMaker RL
Amazon SageMaker RL supports multi-core and multi-instance distributed training. Depending on your use case, training and/or environment rollout can be distributed. For example, SageMaker RL works for the following distributed scenarios:
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Single training instance and multiple rollout instances of the same instance type. For an example, see the Neural Network Compression example in the SageMaker examples repository
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Single trainer instance and multiple rollout instances, where different instance types for training and rollouts. For an example, see the AWS DeepRacer / AWS RoboMaker example in the SageMaker examples repository
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Single trainer instance that uses multiple cores for rollout. For an example, see the Roboschool example in the SageMaker examples repository
. This is useful if the simulation environment is light-weight and can run on a single thread. -
Multiple instances for training and rollouts. For an example, see the Roboschool example in the SageMaker examples repository
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