DSSTNE (pronounced "Destiny") is an open source software library for training and deploying deep neural networks using GPUs. Amazon engineers built DSSTNE to solve deep learning problems at Amazon's scale. DSSTNE is built for production deployment of real-world deep learning applications, emphasizing speed and scale over experimental flexibility.
DSSTNE was built with a number of features for production 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. Custom GPU kernels perform sparse computation on the GPU, without filling in lots of zeroes.
- scottlegrand@ reported a 14.8x speed up vs Tensorflow
- Directions on how to run a benchmark can be found in here
- Follow Setup for step by step instructions on installing and setting up DSSTNE
- Check User Guide for detailed information about the features in DSSTNE
- Check Examples to start trying your first Neural Network Modeling using DSSTNE