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Details of Grant 

EPSRC Reference: EP/W035782/1
Title: RSE training in algorithms for exascale simulations
Principal Investigator: Jamil, Dr O
Other Investigators:
Shipton, Dr J
Researcher Co-Investigators:
Project Partners:
Department: Mathematics
Organisation: University of Exeter
Scheme: Standard Research - NR1
Starts: 01 April 2022 Ends: 31 March 2025 Value (£): 35,066
EPSRC Research Topic Classifications:
Software Engineering
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
16 Feb 2022 SPF EXCALIBUR RSE KI Phase Two Panel Announced
Summary on Grant Application Form
The exascale computing landscape in the UK is at an exciting stage,

with funding being allocated to novel architectures, new software

frameworks and innovative algorithms. Through training RSEs we have an

opportunity to embed the progress made in these areas into the core of

academic research and industrial applications, positioning the UK as

an international leader in exascale simulations. To grasp this

opportunity is essential that RSEs are trained in algorithms so

that they can take an active part in research in this area. In order

to make informed and creative design choices when writing and

optimising software, RSEs need to have core knowledge of algorithms so

that they can confidently innovate and avoid the common pitfalls that

academics and industrial partners are already aware of through their

research and experience. If this core knowledge is not passed on to

RSEs and shared throughout the RSE community, advances made through

the ExCALIBUR programme research projects risk failing to achieve

crucial impact in academic and industrial applications.

As described in section 7.3 of the RSE Knowledge Integration Landscape

Review, it is crucial that RSEs have the potential to be actively

involved in research. This is one of the key attractions of the job

for skilled postgraduate students and is essential for retaining

skilled RSEs in the role. The Landscape Review acknowledges that

design of new algorithms is a research field in itself and requires

`strong domain specific knowledge'. We propose to provide training in

this area, alongside opportunities for knowledge exchange and

networking between academic researchers, postgraduate students, RSEs

and industrial partners.

We propose to run two three-day workshops and a Summer School to

provide training in state of the art algorithms and core knowledge of

the underlying foundational mathematical and numerical analysis on

which they are based. The materials developed in advance of, and

during, these events will be curated and shared online to either be

used as stand alone material for individual training or to form the

basis of future summer schools.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.ex.ac.uk