EPSRC Reference: |
EP/W035782/1 |
Title: |
RSE training in algorithms for exascale simulations |
Principal Investigator: |
Shipton, Dr J |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Mathematics |
Organisation: |
University of Exeter |
Scheme: |
Standard Research - NR1 |
Starts: |
01 April 2022 |
Ends: |
31 March 2025 |
Value (£): |
35,066
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EPSRC Research Topic Classifications: |
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EPSRC Industrial Sector Classifications: |
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Related Grants: |
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Panel History: |
Panel Date | Panel Name | Outcome |
16 Feb 2022
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SPF EXCALIBUR RSE KI Phase Two Panel
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Announced
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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.
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Key Findings |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.ex.ac.uk |