Benchmarks based on neural networks libraries to compare the performance between different GPUs

Question

I am looking for benchmarks based on neural networks libraries (Theano/TensorFlow/Torch/Caffe/…) to compare the performance between different GPUs.

I am aware of:

• https://github.com/jcjohnson/cnn-benchmarks (CNN in Torch)
• https://github.com/jcjohnson/neural-style#speed (CNN in Torch)
• https://github.com/glample/rnn-benchmarks (vanilla RNNs and LSTM in Theano, TensorFlow, and Torch)

What are some other benchmark codes?

Answer 1

Here is my list with collection of benchmarks: https://github.com/mrgloom/Deep-Benchmark-List

https://github.com/dividiti/ck-caffe looks more promissing, but complicated.

Answer 2

I found a few more benchmarks with the help of reddit:

• https://github.com/soumith/convnet-benchmarks: feedforward and convolution layers in many different libraries. (overview)
• https://github.com/DeepMark/deepmark : LSTM and CNN, torch only so far.
• https://github.com/baidu-research/DeepBench : "DeepBench attempts to answer the question, "Which hardware provides the best performance on the basic operations used for training deep neural networks?" (another page on it: https://svail.github.io/DeepBench)