This two-part workshop teaches the fundamental tools and techniques for accelerating C/C++ applications to run on massively parallel GPUs with CUDA®.

Participants will learn how to write code, configure code parallelization with CUDA, optimize memory migration between the CPU and GPU accelerator, and implement the workflow learned on a new task—accelerating a fully functional, but CPU-only, particle simulator for observable massive performance gains. At the end of the workshop, you'll have access to additional resources to create new GPU-accelerated applications on your own. Each session is roughly divided into 3 hours of active teaching and 1 hour of extra Q&A.

• This first session focuses on accelerating applications with CUDA C/C++ and managing accelerated application memory with CUDA C/C++.
• The second session will focus on asynchronous streaming and visual profiling for accelerated applications with CUDA C/C++.

Upon successful completion of the assessment, you’ll receive an NVIDIA certificate.

Important

This is a two-part course. Make sure you can attend both sessions before you register. 
A laptop is required to participate. Students can borrow a laptop through the library’s Tech Lending program.

Prerequisites:

• Basic C/C++ competency, including familiarity with variable types, loops, conditional statements, functions, and array manipulations

Complete An Even Easier Introduction to CUDA, 1-hour online course (free with NVIDIA account