SEARCH SESSIONS

Search All
 
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC ON-DEMAND

AI Application, Deployment & Inference
Presentation
Media
Deploying AI on Jetson Xavier/DRIVE Xavier with TensorRT and MATLAB
Abstract:
Learn how GPU Coder produces high-performance CUDA code automatically from a high-level algorithm description in MATLAB. Write your deep learning application with the expressive power of MATLAB, which allows you to describe not just the use of your trained deep learning model in inference mode, but also perform data-augmentation and post-processing of the results to create a complete deployment-ready application. With MATLAB running on your host machine, communicate and control peripheral devices on your Jetson Xavier and DRIVE Xavier platforms to bring in live data from sensors for visualization and analysis. GPU Coder can then generate optimized inference code for the whole application. The deep learning inference model is compiled down to TensorRT's inference engine, while the rest of the application logic is parallelized through creation of CUDA kernels and integrated with other CUDA optimized libraries like cuBLAS, cuFFT, etc. GPU Coder provides a clean, elegant solution to go from algorithm to application deployment, unleashing the performance of CUDA, TensorRT, and the Xavier device architecture.
 
Topics:
AI Application, Deployment & Inference, Deep Learning & AI Frameworks, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9281
Streaming:
Download:
Share: