Parallel Computing with GPUs

7 February 2022 - Spring Semester Week 1-Week 12
In Person
Paul Richmond

All of our events may be recorded and shared via the University of Sheffield Kaltura platform so those who cannot attend may still benefit. We will consider your attendance implict consent to this.

12 Week Parallel Computing with GPUs course

Starting this term (Feb) is a 12 week course on “Parallel Computing with GPUs”. The course has been designed as an undergraduate 4th year (and MSc) module for Computer Science but is available to staff and PhD Students (as part of the DDP program) and regularly has staff and PhD student enrolment.

The first 3 weeks are focused on teaching C and OpenMP followed by GPU programming with CUDA C. Lectures are provided as pre-recorded mini lectures and there are 2 hours of scheduled support per week to undertake practical lab classes. Assessment is not required for DDP or staff participants. You can attend all or just parts of the course.

If you are interested in enrolling as staff or a PhD student then please express you interest on the following google form:

If you are interested in joining after the start of week one then please contact Paul Richmond directly.

Prerequisite skills: Some programming experience.

Learning Objectives

  • Compare and contrast parallel computing architectures
  • Implement programs for GPUs and multicore architectures
  • Apply benchmarking and profiling to GPU programs to understand performance
  • Identify and address limiting factors and apply optimisation to improve code performance

This course will be run in person but recordings of lectures will be availble for self paced learning.

Contact Us

For queries relating to collaborating with the RSE team on projects:

Information and access to JADE II and Bede.

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Queries regarding free research computing support/guidance should be raised via our Code clinic or directed to the University IT helpdesk.