Learn how you can use MATLAB to build your computer vision and deep learning applications and deploy them on NVIDIA Jetson
MATLAB auto-generates portable CUDA code that leverages CUDA libraries like cuBLAS and cuDNN from the MATLAB algorithm, which is then cross-compiled and deployed to Jetson.
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.
By watching this webinar replay, 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