We are steadily building a collection of research software profiling case studies. If youโ€™re looking for real world examples of optimisations you might find in research code, you should read these.

If you have had success profiling and optimising your own research software, we would welcome a case study written from your perspective. The more examples we can share, the more clearly we can demonstrate the impact that profiling can have on research code.

If you are interested in contributing, you can get in touch to discuss your experience with us, or submit an issue or a pull request directly.

Many of these simple optimisation patterns are incidental finds, uncovered whilst profiling code. If you discover anything missing from our database, please help by submitting it for inclusion via GitHub.

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Recent Case Studies

Case Study: FFEA

FFEA stands for Fluctuating Finite Element Analysis. It is a research software platform used to model biological molecules as they move and flex under thermal effects. The software itself was first released in 2018, building on methods that had been developed and published since 2010.

Since then, FFEA has seen steady adoption in the academic literature, with around 12 published studies using it, including work led by researchers who were not involved in its development. This level of continuity and uptake is relatively successful for specialised scientific software.