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Last pushed: a year ago
Short Description
Keras with CUDA enabled via NVIDIA docker wrapper
Full Description


keras-cuda

nvidia-docker + Ubuntu 14.04 + CUDA 7.5.18 + cuDNN v4 + Keras.

Requirements

  • Host with recent drivers and the NVIDIA Docker wrapper
  • NVidia GPU with Fermi, Kepler or later architecture

Usage

# 10s per epoch (GPU) vs 100s per epoch (CPU)
nvidia-docker run --rm brianlow/keras-cuda python examples/imdb_cnn.py

# or run an interactive shell
nvidia-docker run -i -t brianlow/keras-cuda /bin/bash

Notes

  • Some tricks to get the NVIDIA Docker wrapper working:
    • To enable the NVIDIA driver on Ubuntu 16.04: Software & Updates -> Additional Drivers -> Use later NVIDIA binary driver (proprietary)
    • Ensure nvidia-docker-plugin is running, either by rebooting or running sudo nvidia-docker-plugin
    • Test with nvidia-docker run --rm nvidia/cuda nvidia-smi.
    • Your card may still work if it is identified correctly but Processes show "Not Supported".
  • Tested with Ubuntu 16.04 host with GeForce GTX 760 (Kepler) and NVIDIA driver 361.42

Alternatives

The NVIDIA Docker wrapper decouples the OS and driver versions between host and container. If you can control both, see
Kaixhin/dockerfiles for a huge variety of CUDA-enabled machine learning docker images using vanilla docker.

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Owner
brianlow
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