The generated code is highly optimized and benchmarks will be presented that show that deep learning inference performance of the auto-generated CUDA code is ~2.5x faster for MXNet, ~5x faster for Caffe2 and ~7x faster for TensorFlow.
Date & Time: Wednesday, Oct 4, 2017 from 10:00am – 11:00am PT
By attending this webinar, you’ll learn how to
- Access and manage large image sets
- Visualize networks and gain insight into the training process
- Import reference networks such as AlexNet and GoogLeNet
- Automatically generate portable and optimized CUDA code from the MATLAB algorithm