8-bit Deep Learning

Motivations

In this repository, we train an MLP with 8-bit multiplications (but 32-bit accumulations). Our method could take advantage of a Pascal (the latest Nvidia GPU architecture) instruction which performs 4 x 8-bit multiplications 32-bit accumulation per clock cycle. Basically, we could train neural networks about 4 times faster than float32 with no loss in accuracy.

Requirements

Python 2.7, Numpy, Scipy
Theano
A fast Nvidia GPU (or a large amount of patience)
Setting your Theano flags to use the GPU
Lasagne

MNIST MLP

Firstly, download the MNIST dataset:

wget http://deeplearning.net/data/mnist/mnist.pkl.gz

Then, simply run the training script:

python mnist_mlp.py

It should run for about 15 minutes on a Titan X GPU. The final test error should be around 0.87%.

CIFAR-10 ConvNet

TODO

ImageNet ConvNet