Using multiple GPUs is one option to speed up your code. On Apocrita, we have V100, A100 and H100 GPUs available, with up to 4 GPUs per node. On other compute clusters, JADE2 has 8 V100 GPUs per node and Sulis has 3 A100 GPUs per node. If your problem is pleasingly parallel, you can distribute identical or similar tasks to each GPU on a node, or even on multiple nodes.
We held a 2-hour HPC workshop last Friday, December 15th. We arranged an agenda in coordination with the research student at QMUL, Peter Alexander Lock. It covered the generalities of Linux, accessing Apocrita, submitting jobs, and HPC commands.
Since the last module update in December 2022, we have:
On November 15th, our HPC team organised an event called “Let’s talk about Linux and HPC”, which focused on giving an overview of HPC at QMUL. The conference was open to the public and published on Eventbrite.
Approximately 30 people were in attendance between organisers and online or onsite attendees that came to our 2-hour event in the Engineering building at the Mile End campus. During the conference, attendees shared opinions, thoughts and suggestions for future workshops dealing with Linux, Ubuntu and setting up scripts in more detail. They were able to express themselves with the help of mentimeter.
The High Performance Computing (HPC) team is keen to spread Linux and HPC knowledge at Queen Mary University of London. Keeping in mind our vision to support excellence in research, our valuable efforts have been fruitful this year. Our achievements include:
We have deployed the latest version of Environment Modules (5.3.0) across the cluster on all frontend and compute nodes.
Nowadays, there seems to be an R package for anything and everything. While this makes starting a project in R seem quick and easy, there are considerations to take into account that will make your life easier in the long run.
Files quickly proliferate and need to be kept tidy. It is important that the correct people can access the files, and file systems are well-structured for easy navigation.
Living with Machines is a funded project at The Alan Turing Institute (aka the Turing), bringing together academics from different disciplines, to answer research questions such as how did historical newspapers tell the political landscape, how were accidents in factories reported, how did road and settlement names change, how did people change occupations during the industrial revolution...
Installing packages into a personal R library can sometimes take quite a long time, but it doesn't always have to be this way.