Fundamentals of Accelerated Computing with CUDA C/C++
Offered By: Nvidia via Independent
Course Description
Overview
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.
Syllabus
- 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++
- Next Steps
- Course Survey
- Environment Quick Start
Tags
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