ISC19

We are investigating how SX-Aurora works on variouse ML applications. In this post, we would like to share the result of performance evaluation of three ML workloads using TensorFlow. The graphs show relative performance of training on CPU, GPU and VE in SX-Aurora. The left graph is simple CNN for image classification based on the example in Keras. We have used mnist dataset. As you know, GPU’s high peak computational performance works well for convolution layers, then V100 is the best. [Read More]