Learn to use CUDA C/C++ tools and techniques to accelerate CPU-only applications to run on massively parallel GPUs.
What You'll Learn
How to GPU-accelerate CPU-only applications with CUDA C/C++
An iterative, profiler driven approach to accelerating applications
About This Course
The CUDA computing platform enables the acceleration of CPU-only applications to run on the world's fastest massively parallel GPUs. Experience accelerating C/C++ applications 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
Upon completion of this workshop, you'll be able to accelerate and optimize existing C/C++ CPU-only applications using a number of the most essential CUDA tools and techniques. You will have a keen sense for an iterative style of CUDA development that will allow you to ship accelerated applications fast. Prerequisites
To successfully complete this course, you should have some basic C/C++ competency.
Accelerating Applications with CUDA C/C++
Managing Accelerated Application Memory with CUDA C/C++ Unified Memory and nvprof
Asynchronous Streaming, and Visual Profiling for Accelerated Applications with CUDA C/C++