amazon dsstne

Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models

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Amazon DSSTNE: Deep Scalable Sparse Tensor Network Engine

DSSTNE (pronounced “Destiny”) is an open source software library for training and deploying recommendation
models with sparse inputs, fully connected hidden layers, and sparse outputs. Models with weight matrices
that are too large for a single GPU can still be trained on a single host. DSSTNE has been used at Amazon
to generate personalized product recommendations for our customers at Amazon’s scale. It is designed for
production deployment of real-world applications which need to emphasize speed and scale over experimental
flexibility.

DSSTNE was built with a number of features for production recommendation workloads:

  • Multi-GPU Scale: Training and prediction
    both scale out to use multiple GPUs, spreading out computation
    and storage in a model-parallel fashion for each layer.
  • Large Layers: Model-parallel scaling enables larger networks than
    are possible with a single GPU.
  • Sparse Data: DSSTNE is optimized for fast performance on sparse datasets, common in recommendation
    problems. Custom GPU kernels perform sparse computation on the GPU, without filling in lots of zeroes.

Benchmarks

Scaling up

License

License

Setup

  • Follow Setup for step by step instructions on installing and setting up DSSTNE

User Guide

  • Check User Guide for detailed information about the features in DSSTNE

Examples

  • Check Examples to start trying your first Neural Network Modeling using DSSTNE

Q&A

FAQ