neonΒΆ

Release:2.2.0+5843e71
Date:Sep 27, 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:

  • Update MKLML version 20170908 that fixes a bug related to data conversions)
  • Add SSD example for bounding box object detection that works for both GPU and MKL backend
  • Add DeepSpeech2 MKL backend optimization that features ~3X improvement
  • Update aeon to 1.0.0 including new version of manifest (doc/source/loading_data.rst#aeon-dataloader)
  • See more in the change log.

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