The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. Experience C/C++ application acceleration 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, you’ll be able to accelerate and optimize existing C/C++ CPU-only applications using the most essential CUDA tools and techniques. You’ll understand an iterative style of CUDA development that will allow you to ship accelerated applications fast.

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.

Suggested Resources to Satisfy Prerequisites

The learn-c.org interactive tutorial.

Tools, Libraries, and Frameworks Used

• CUDA C++
• nvcc
• Nsight Systems

Related Training

• Accelerating CUDA C++ Applications with Concurrent Streams

A self-paced course to learn more intermediate CUDA C++ concurrency techniques after completing this course.

• Scaling Workloads Across Multiple GPUs with CUDA C++

A self-paced course to learn more intermediate CUDA C++ multi-GPU techniques after completing this course.

For additional hands-on training through the NVIDIA Deep Learning Institute, visit www.nvidia.com/dli.

Registering Your Interest

There are a limited number of places available for this course. Your application will be treated as an expression of interest and you are not guaranteed a place at the workshop.

As part of the application process, you will be asked to provide a brief explanation of how attending this workshop will benefit your work. You may find it useful to write this piece before attempting to register for the event.

After the application deadline has passed, submissions will be considered, and successful applicants will be offered a place by 16 March.

This event is only open to those working or studying at one of the N8 Research Partnership universities. Please register using your academic (.ac.uk) e-mail address to help verify your eligibility for this course.