Abstract

This workshop teaches the fundamental tools and techniques for accelerating C/C++ applications to run on massively parallel GPUs with CUDA®. You’ll learn how to write code, configure code parallelization with CUDA, optimize memory migration between the CPU and GPU accelerator, and implement the workflow that you’ve learned on a new task—accelerating a fully functional, but CPU-only, particle simulator for observable massive performance gains. 

The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. Experience C/C++ application acceleration by:

• Accelerating CPU-only applications to run their latent parallelism on GPUs
• Utilizing essential CUDA memory management techniques to optimize accelerated applications
• Exposing accelerated application potential for concurrency and exploiting it with CUDA streams
• Leveraging command line and visual profiling to guide and check your work

Find more information on this workshop here

Learning Objectives

At the conclusion of the workshop, you’ll have an understanding of the fundamental tools and techniques for GPU-accelerating C/C++ applications with CUDA and be able to:

• Write code to be executed by a GPU accelerator
• Expose and express data and instruction-level parallelism in C/C++ applications using CUDA
• Utilize CUDA-managed memory and optimize memory migration using asynchronous prefetching
• Leverage command line and visual profilers to guide your work
• Utilize concurrent streams for instruction-level parallelism
• Write GPU-accelerated CUDA C/C++ applications, or refactor existing CPU-only applications, using a profile-driven approach 

Prerequisites

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

Please note that pictures and videos might be taken during the event. The pictures and videos might be used for communication about the event. By joining the lecture, you are agreeing to being featured in these communication actions.