neonΒΆ

Release:1.8.2+0d643dd
Date:Feb 23, 2017

neon is Intel Nervana ‘s reference deep learning framework committed to best performance on all hardware. Designed for ease-of-use and extensibility.

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:

  • Make the whale calls example stable and shuffle dataset before splitting into subsets
  • Reduce default depth in cifar_msra example to 2
  • Fix the formatting of the conv layer description
  • Fix documentation error in the video-c3d example
  • Support greyscale videos
  • See more in the 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!