SM DDP release notes/changelog files

doc/api/training/smd_data_parallel.rst

@@ -70,3 +70,12 @@ model.
 
    sdp_versions/smd_data_parallel_pytorch
    sdp_versions/smd_data_parallel_tensorflow
+
+Latest Updates
+==============
+
+New features, bug fixes, and improvements are regularly made to the SageMaker distributed data parallel library.
+
+To see the the latest changes made to the library, refer to the library
+`Release Notes
+<https://github.com/aws/sagemaker-python-sdk/blob/master/doc/api/training/smd_data_parallel_release_notes/>`_.

doc/api/training/smd_data_parallel_release_notes/smd_data_parallel_change_log.md

@@ -0,0 +1,18 @@
+# Sagemaker Distributed Data Parallel - Release Notes
+
+- First Release
+- Getting Started
+
+## First Release
+SageMaker's distributed data parallel library extends SageMaker’s training
+capabilities on deep learning models with near-linear scaling efficiency,
+achieving fast time-to-train with minimal code changes.
+SageMaker Distributed Data Parallel:
+
+- optimizes your training job for AWS network infrastructure and EC2 instance topology.
+- takes advantage of gradient update to communicate between nodes with a custom AllReduce algorithm.
+
+The library currently supports Tensorflow v2 and PyTorch via [AWS Deep Learning Containers](https://aws.amazon.com/machine-learning/containers/).  
+
+## Getting Started
+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).