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2022

Modules Update December 2022

Since the last module update in December 2021, we have:

  • added/moved 84 modules to production
  • added 9 modules to the development environment
  • deprecated 5 modules
  • deleted 12 modules

Speeding Up Grep Searches

Sometimes you may find yourself needing to filter a large amount of output using the grep command. However, grep can sometimes struggle when you try to filter files with an incredibly large number of lines, as it loads each line into RAM line-by-line. This can mean you can quickly exhaust even large amounts of requested RAM. There are a few ways around this.

Migrating to a new research storage system

As the current 2 PetaByte Research Data Storage on Apocrita reaches end of life this summer, we have procured a new storage system, providing 5PB of capacity. This means faster, bigger and cheaper storage for you, the researcher! Read on to discover the benefits...but first, an important notice.

RSE team activities up to June 2022

The RSE team in ITS Research has had a busy few years since we started sharing our work in this blog. In this post we look at some highlights of recent activity and what we have to look forward to.

Using job statistics to increase job performance and reduce queueing time

You may wonder why some jobs start immediately but some wait in the queue for hours or days, even if your job is quite simple. If you notice your job has been queueing for a while, you may want to consider adjusting the requested resources to reduce queueing time and reduce any potential resource wastage as the job runs. Below, we outline two useful tools for you to check the resource usage of previous jobs.

Assessing code quality with the NAG Fortran compiler

The NAG Fortran compiler, like other compilers, has diagnostic capabilities which can help us write correct and portable Fortran programs. In this post we'll look at these, comparing with those of the GCC and Intel compilers, and see how the compiler can be a valuable tool when developing or maintaining Fortran code.

Introducing Sherman Lo, RSE

Hello! I am Sherman and I have just joined the RSE team at Queen Mary. Glad to meet you all!

My background is in computational statistics and machine learning. I have completed projects in rainfall prediction, defect detection for 3D printing and Markov chains using Monte Carlo. These projects involved collaboration with various scientists, such as meteorologists, engineers and statisticians.