neon

Release:1.7.0+d8ae0ee
Date:Nov 21, 2016

neon is Nervana ’s Python-based deep learning library. It provides ease of use while delivering the highest performance.

Features include:

  • Support for commonly used models including convnets, RNNs, LSTMs, and autoencoders. You can find many pre-trained implementations of these in our model zoo
  • Tight integration with our state-of-the-art GPU kernel library
  • 3s/macrobatch (3072 images) on AlexNet on Titan X (Full run on 1 GPU ~ 32 hrs)
  • Basic automatic differentiation support
  • Framework for visualization
  • Swappable hardware backends: write code once and deploy on CPUs, GPUs, or Nervana hardware

New features in this release:

  • Update Data Loader to aeon https://github.com/NervanaSystems/aeon
  • Add Neural Machine Translation model
  • Remove Fast RCNN model (use Faster RCNN model instead)
  • Remove music_genres example
  • Fix super blocking for small N with 1D conv
  • Fix update-direct conv kernel for small N
  • Add gradient clipping to Adam optimizer
  • Documentation updates and bug fixes
  • See change log.

We use neon internally at Nervana to solve our customers’ problems in many domains. Consider joining us. We are hiring across several roles. Apply here!