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
> No previous knowledge of CUDA programming is assumed

Technologies: NVIDIA® Nsight™, nsys

Certificate: Upon successful completion of the assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

Hardware Requirements: Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.

Languages: English