Getting Started with Accelerated Computing in CUDA C/C++ | NVIDIA

About 2 min

Getting Started with Accelerated Computing in CUDA C/C++ | NVIDIA 관련

Learn how to accelerate and optimize existing C/C++ CPU-only applications using the most essential CUDA tools and techniques. You’ll also learn an iterative style of CUDA development that will allow you to ship accelerated applications fast.

About This Course

CUDA is used to accelerate CPU-only applications by making them run on GPUs . These CUDA applications are massively parallel and way faster than their CPU-only counterparts. Experience C/C++ application acceleration by:

Parallelizing applications to run on GPUs
Optimizing applications by using CUDA techniques like memory - management
Learning techniques like concurrency and CUDA streams
Learning tools like Nsight Systems to profile and identify bottlenecks

Upon completion, you’ll be able to accelerate and optimize existing C/C++ CPU-only applications using the most essential CUDA techniques and Nsight Systems. You’ll understand an iterative style of CUDA development that will allow you to ship accelerated applications quickly.

Prerequisities

Basic C/C++ competency including familiarity with variable types, loops, conditional statements, functions, and array manipulations. No previous knowledge of CUDA programming is assumed.