A Graphics Processing Unit (GPU) provides much higher instruction throughput and memory bandwidth than the CPU within a similar price and power envelope. Many applications leverage these higher capabilities to run faster on the GPU than on the CPU

CUDA® is a general purpose parallel computing platform and programming model that leverages the parallel compute engine in NVIDIA GPUs
to solve many complex computational problems in a more efficient way than on a CPU.

The NVIDIA CUDA Programming on NVIDIA GPUs is a 5-day hands-on course for students, postdocs, academics and others who want to learn how to develop applications to run on NVIDIA GPUs using the CUDA programming environment. All that will be assumed is some proficiency with C and basic C++ programming.

The course consists of approximately 3 hours of lectures and 4 hours of practicals each day. The aim is that by the end of the course you will be able to write relatively simple programs and will be confident and able to continue learning through studying the examples provided by NVIDIA as part of their SDK (software development kit).

When future editions of the course are announced, we will add these to our events page.

Find out more

Syllabus for a previous edition of the course