Upcoming dates:

• February 9, 2023, 9:00 AM-5:00 PM CET (Central European Time)

• February 23, 2023. Time: 9:00 AM-5:00 PM (Pacific Time)

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. At the end of the workshop, you’ll have access to additional resources to create new GPU-accelerated applications on your own. 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