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Tue 6 Jul 2021
09:30 - 17:30

Venue: Bioinformatics Training Facility - Online LIVE Training

Provided by: Bioinformatics


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Mon 8 Jul 2024

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High Performance Computing: An Introduction (ONLINE LIVE TRAINING)

Tue 6 Jul 2021


PLEASE NOTE that until further notice, due to the evolving situation with Coronavirus no courses will be offered as classroom based at the Training Facility. The Bioinformatics Team will be teaching the course live online in conjunction with the presenters.

Have you heard about High Performance Computing, but are not sure what it is or whether it is relevant for your work? Would you like to use a HPC, but are not sure where to start? Are you using your personal computer to run computationally demanding tasks, which take long and slow down your work? Do you need to use software that runs on Linux, but don't have access to a Linux computer? If any of these questions apply to you, then this course might be for you!

Knowing how to work on a High Performance Computing system is an essential skill for applications such as bioinformatics, big-data analysis, image processing, machine learning, parallelising tasks, and other high-throughput applications.

In this course we will cover the basics of High Performance Computing, what it is and how you can use it in practice. This is a hands-on workshop, which should be accessible to researchers from a range of backgrounds and offering several opportunities to practice the skills we learn along the way.

As an optional session for those interested, we will also introduce the (free) HPC facilities available at Cambridge University (the course is not otherwise Cambridge-specific).

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Target audience
  • This course is aimed at students and researchers of any background.
  • We assume no prior knowledge of what a HPC is or how to use it.
  • It may be particularly useful for those who have attended other Facility Bioinformatics Training Courses and now need to process their data on a Linux server. It will also benefit those who find themselves using their personal computers to run computationally demanding analysis/simulations and would like to learn how to adapt these to run on a HPC.
  • Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
  • Please be aware that these courses are only free for registered University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here.
  • Further details regarding eligibility criteria are available here

Number of sessions: 1

# Date Time Venue Trainers
1 Tue 6 Jul 2021   09:30 - 17:30 09:30 - 17:30 Bioinformatics Training Facility - Online LIVE Training Hugo Tavares,  Lajos Kalmar,  Paul Judge,  Qi Wang
Topics covered

High Performance Computing (HPC), Working on remote servers, Shell scripting, SLURM job scheduler


During this course you will learn about:

  • What is a HPC and how does it differ from a regular computer?
  • What can a HPC be used for?
  • How do I access and work on a HPC?
  • How do I run jobs on a HPC?
  • How can I run many similar jobs in parallel?
  • How can I access, install and manage software on a HPC?

After this course you should be able to:

  • Describe what a HPC is and how it is generally organised.
  • Distinguish between a login and a compute node.
  • Connect to a HPC and navigate through its filesystem using the command-line.
  • Move files in/out of the HPC using Filezilla or alternative command-line tools.
  • Edit script files directly on a remote server using Visual Studio Code.
  • Describe the role of a Job Scheduler and what resources to consider when running jobs.
  • Use the SLURM job scheduler to run analysis on the HPC.
  • Customise the use of SLURM and take advantage of its inbuilt “job arrays” feature to parallelise similar jobs.
  • Obtain an account on the Cambridge University HPC server, and apply the knowledge learned here to use it effectively for your own work.

Presentations, demonstrations and practicals.

System requirements
  • We encourage you to use your own computer for this course. This is so you can leave the course prepared to work on a HPC that you may have access to in your institution.
  • Please install the necessary software following our setup instructions. If you have any issues installing the software, please get in touch with us some time before the course.
  • However, if you are unable to install the required software we will be able to give you access to the necessary tools through our training platform.

This is subject to change in line with the online training schedule.

Session 1 Welcome
Session 2 Introduction to HPC
Session 3 Working on a HPC cluster
Session 4 Using the SLURM job scheduler
Session 5 Using the SLURM job scheduler (cont.)
Session 6 Managing Software
Session 7 Parallelising Jobs
Session 8 HPC resources at University of Cambridge
Registration Fees
  • Free for registered University of Cambridge students
  • £ 50/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
  • It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
  • £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
  • £ 100/day for all Industry participants. These charges must be paid at registration
  • Further details regarding the charging policy are available here



A number of times per year

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