Overview
In this session we will learn how to generate CUDA code automatically from MATLAB to run on NVIDIA desktop and embedded GPUs. MATLAB is the ideal environment for exploring, developing and prototyping algorithms. GPUs are the hardware of choice for many applications, such as signal, image processing and deep learning, that benefit from the massive parallel processing they offer. GPU Coder offers a direct route to transition from MATLAB development to deployment on GPUs via the generation of CUDA code.
Highlights
- Prototype and accelerate implementations with automatic CUDA code generation
- Enhance performance through code refactoring and design pattern pragmas
- Scale MATLAB algorithms on multiple GPUs for processing data
- Deploy generated code to desktop and embedded GPUs
About the Presenter
Oscar Molina holds master's and PhD degrees both in Petroleum Engineering and a bachelor's degree in Mechanical Engineering. Prior to joining the MathWorks, Oscar worked in the oil and gas industry for about 8 years in different areas, including production operations and reservoir engineering. During his last two years in the industry, Oscar focused on the creation of digital twins aimed at optimizing oil and gas production as well as understanding short and long-term reservoir potential. Furthermore, he worked on modeling CO2 injection in deep saline aquifers. Oscar currently helps our customers to accelerate MATLAB code with MATLAB Coder and GPU Coder.
