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Part 4: Automatic CUDA Code Generation and Deployment on Embedded Platforms

Overview

NVIDIA GPUs are the hardware of choice for many applications, such as autonomous systems, deep learning, signal and image processing. MATLAB is the ideal environment for exploring, developing and prototyping algorithms. In this seminar, we will learn how to generate CUDA code directly from MATLAB to run on NVIDIA GPUs using GPU Coder.

Highlights

  • GPU Coder converts your MATLAB algorithms to CUDA without being a CUDA expert
  • GPU Coder optimizes instructions and memory operations to generate efficient code

About the Presenter

Rishu Gupta is a senior application engineer at MathWorks India. He primarily focuses on image processing, computer vision, and deep learning applications. Rishu has over nine years of experience working on applications related to visual contents. He previously worked as a scientist at LG Soft India in the Research and Development unit. He has published and reviewed papers in multiple peer-reviewed conferences and journals. Rishu holds a bachelor’s degree in electronics and communication engineering from BIET Jhansi, a master’s in visual contents from Dongseo University, South Korea, working on the application of computer vision, and a Ph.D. in electrical engineering from University Technology Petronas, Malaysia with a focus on biomedical image processing for ultrasound images.

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