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Details of Grant 

EPSRC Reference: EP/W007711/1
Title: Software Environment for Actionable & VVUQ-evaluated Exascale Applications (SEAVEA)
Principal Investigator: Coveney, Professor P
Other Investigators:
Guillas, Professor SE Luo, Professor KH Woodley, Professor SM
Researcher Co-Investigators:
Project Partners:
Argonne National Laboratory Centrum Wiskunde & Informatica Imperial College London
Max Planck Institutes Polish Academy of Sciences RIKEN
Rutgers State University of New Jersey Save the Children (UK) UK Atomic Energy Authority
University of Cambridge
Department: Chemistry
Organisation: UCL
Scheme: Standard Research
Starts: 02 August 2021 Ends: 31 March 2025 Value (£): 728,470
EPSRC Research Topic Classifications:
Fundamentals of Computing Software Engineering
EPSRC Industrial Sector Classifications:
R&D
Related Grants:
EP/W007762/1
Panel History:
Panel DatePanel NameOutcome
03 Jun 2021 SPF ExCALIBUR Cross-Cutting Research Expert Interview Panel A Announced
Summary on Grant Application Form
Uncertainty quantification, verification and validation are crucial to establish the reliability and reproducibility of all forms of computer-based simulation. We propose to establish an open source and open development VVUQ toolkit optimised for efficient execution at current pre- and emerging exascale, which will raise new challenges and new opportunities for simulations in fields as diverse as fusion and climate modelling.

Computer simulation results are validated compared with experiment in several ways, ranging from qualitative to quantitative measures which apply a validation metric. Likewise, verification is concerned with confirmation that the mathematical model and corresponding algorithm have been coded correctly. Uncertainty quantification (UQ) is concerned with understanding the origins of and assessing the magnitudes of the errors which accompany computer simulations, whether epistemic or aleatoric.



VVUQ is necessary for any simulation that makes predictions in advance of an event to become actionable - that is, for its output to be useful in any form of decision-making process, from government interventions in pandemics to the choice of materials to combine for aircraft wing production. Here, exascale computing offers more opportunities to make actionable predictions.

Moreover, because VVUQ is intrinsically compute intensive due to its ensemble-based execution pattern, it too requires exascale resources, as well as advanced resource management strategies to efficiently manage the large numbers of concurrent runs necessary.

We propose to establish an open source and open development VVUQ toolkit optimised for efficient execution at current pre- and emerging exascale. This will include advanced approaches for surrogate modelling in order to minimise the expense and time needed to perform the most compute-intensive calculations and will demonstrate its efficiency gains for a diverse array of VVUQ workflows within multiple scientific applications, and on architecturally and geographically diverse emerging exascale environments.

The software developed, implemented and benchmarked in this project will become an open and invaluable asset to the UK ExCALIBUR community but also much more widely within UK and internationally as high-performance computing enters the exascale era.

The proposed exascale toolkit will be built on a combination of widely used tools and services which will be evolved to handle systems of increasing levels of complexity. These include components from the VECMA project (EasyVVUQ, FabSim3, QCG-PJ and EasySurrogate), as well as the UCL-Alan Turing Institute Multi-Output Gaussian Process Emulator (MOGP). We will apply these capabilities to several applications, including: (i) the UKAEA's tokamak fusion modelling use case for which a working software environment will be produced; (ii) weather and climate forecasting for the Met Office; (iii) turbulent flow simulation for environmental science; (iv) prediction of advanced materials properties of graphene-polymer based nanocomposites for aerospace applications; (v) high-fidelity patient-specific virtual human blood flow system for medical research; (vi) drug discovery; and (vii) human migration.

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