sagemaker
v2.73.0
  • Using the SageMaker Python SDK
  • Use Version 2.x of the SageMaker Python SDK
  • APIs
    • Feature Store APIs
    • Training APIs
    • Distributed Training APIs
      • The SageMaker Distributed Data Parallel Library
      • The SageMaker Distributed Model Parallel Library
    • Inference APIs
    • Utility APIs
  • Frameworks
  • First-Party Algorithms
  • Workflows
  • Amazon SageMaker Debugger
  • Amazon SageMaker Feature Store
  • Amazon SageMaker Model Monitor
  • Amazon SageMaker Processing
sagemaker
  • »
  • APIs »
  • Distributed Training APIs
  • Edit on GitHub

Distributed Training APIs¶

SageMaker distributed training libraries offer both data parallel and model parallel training strategies. They combine software and hardware technologies to improve inter-GPU and inter-node communications. They extend SageMaker’s training capabilities with built-in options that require only small code changes to your training scripts.

  • The SageMaker Distributed Data Parallel Library
    • Use with the SageMaker Python SDK
    • API Documentation
      • Version 1.2.x (Latest)
      • Version 1.1.x
      • Version 1.0.0
    • Release Notes
      • SageMaker Distributed Data Parallel 1.2.2 Release Notes
      • Release History
  • The SageMaker Distributed Model Parallel Library
    • Use the Library’s API to Adapt Training Scripts
      • Version 1.6.0 (Latest)
      • Documentation Archive
    • Use with the SageMaker Python SDK
      • Configuration Parameters for distribution
      • Ranking Basics without Tensor Parallelism
      • Placement Strategy with Tensor Parallelism
      • Prescaled Batch
    • Release Notes
      • Sagemaker Distributed Model Parallel 1.6.0 Release Notes
      • Release History
Next Previous

© Copyright 2022, Amazon Revision 4f66d51a.

Built with Sphinx using a theme provided by Read the Docs.