PRISM: Platform for Research In Simulation Methods

Lead Research Organisation: Imperial College London
Department Name: Dept of Aeronautics

Abstract

Computational science is a multidisciplinary research endeavour spanning applied mathematics, computer science and engineering together with input from application areas across science, technology and medicine. Advanced simulation methods have the potential to revolutionise not only scientific research but also to transform the industrial economy, offering companies a competitive advantage in their products, better productivity, and an environment for creative exploration and innovation.

The huge range of topics that computational science encapsulates means that the field is vast and new methods are constantly being published. These methods relate not only to the core simulation techniques but also to problems which rely on simulation. These problems include quantifying uncertainty (i.e. asking for error bars), blending models with data to make better predictions, solving inverse problems (if the output is Y, what is the input X?), and optimising designs (e.g. finding a vehicle shape that is the most aerodynamic). Unfortunately, the process through which advanced new methods find their way into applications and industrial practice is very slow.

One of the reasons for this is that applying mathematical algorithms to complex simulation models is very intrusive; mostly they cannot treat the simulation code as a "black box". They often require rewriting of the software, which is very time consuming and expensive. In our research we address this problem by using automating the generation of computer code for simulation. The key idea is that the simulation algorithm is described in some abstract way (which looks as much like the underlying mathematics as possible, after thinking carefully about what the key aspects are), and specialised software tools are used to automatically build the computer code. When some aspect of the implementation needs to change (for example a new type of computer is being used) then these tools can be used to rebuild the code from the abstract description. This flexibility dramatically accelerates the application of advanced algorithms to real-world problems.

Consider the example of optimising the shape of a Formula 1 car to minimise its drag. The optimisation process is highly invasive: it must solve auxiliary problems to learn how to improve the design, and it be able to modify the shape used in the simulation at each iteration. Typically this invasiveness would require extensive modifications to the simulation software. But by storing a symbolic representation of the aerodynamic equations, all operations necessary for the optimisation can be generated in our system, without needing to rewrite or modify the aerodynamics code at all.

The research goal of our platform is to investigate and promote this methodology, and to produce publicly available, sustainable open-source software that ensures its uptake. The platform will allow us to make advances in our software approach that enables us to continue to secure industrial and government funding in the broad range of application areas we work in, including aerospace and automotive sectors, renewable energy, medicine and surgery, the environment, and manufacturing.

Planned Impact

Academic and industrial users of computational modelling software will benefit from this research since the outputs of the platform will give them access to robust performance-portable implementations of advanced simulation methods, including the composition of models with mathematical algorithms that can solve optimisation problems, quantify uncertainty, assimilate data, etc. This includes our own industrial collaborators from BAE Systems, Airbus, McLaren Racing, Rolls Royce, Arup Consulting, Meygen, EDF, AMEC, Shell, BP, Intel and NVIDIA. Computational modelling is becoming a greater part of the digital economy as a replacement for physical prototyping for many of these industries. Advanced computational modelling can be used to allow high-tech companies to obtain an edge over competitors, to improve productivity in their processes and products, and to provide a environment for creativity and innovation. We also collaborate with public sector research centres such as the UK Met Office, the National Oceanographic Centre in Southampton and Liverpool, and the British Antarctic Survey, for whom the improved modelling capability will enable them to better inform government policy on energy and the environment.

The platform team have an exceptional track record of delivering professionally engineered software tools which, in contrast to much academic software, are well designed, robustly tested, comprehensively documented and ready for translation into production use. This key distinguishing point is critical in guaranteeing that effective wider impact is actually achieved. The institutionalization of best practice in scientific software development also creates maintainable software with an effective and usable life far beyond that of the platform.

There is a continuing need for multidisciplinary researchers with skills in computer science, computational mathematics and numerical modelling. Our Platform grant will enable training in multiple disciplines to address this demand from both industry and academia. Our Platform directly targets the barriers to impact that prevent sophisticated modelling techniques from finding widespread application in industry and science. Further, software tools developed in the platform will support systematic, flexible mapping from the science and engineering "business requirements" of a numerical modelling project right down to the gates and wires of a computational simulation.

We will ensure the impact is maximized by holding regular events where we showcase our work and share ideas with industrial collaborators, and give our researchers the opportunity to network, including a stakeholder input workshop upon renewal. We will fund projects that bring our researchers into direct contact with industrial partners, building proof-of- concept products and interacting on benchmarks and challenges; thus disseminating our ideas and software and collecting industrial user needs. Further, we will aim to influence and keep up with the latest innovations from hardware vendors. The type of multidisciplinary experience that we provide to researchers on this project will make them experts in both numerical modelling and the necessary computer science and software engineering foundations, ensuring they become very employable within both academia and industry.

Publications

10 25 50

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Farrell P (2020) A local Fourier analysis of additive Vanka relaxation for the Stokes equations in Numerical Linear Algebra with Applications

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Melvin T (2019) A mixed finite-element, finite-volume, semi-implicit discretization for atmospheric dynamics: Cartesian geometry in Quarterly Journal of the Royal Meteorological Society

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Van-Brunt A (2020) A Numerical Framework for Concentrated-Solution Theory in ECS Meeting Abstracts

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Luporini F (2020) Architecture and Performance of Devito, a System for Automated Stencil Computation in ACM Transactions on Mathematical Software

 
Description The PI was invited to participate in a Blackett Review on modelling due to his role in this Platform grant and its predecessor.
Sector Aerospace, Defence and Marine,Environment,Transport
Impact Types Policy & public services

 
Description Research Software Engineering and PRISM
Geographic Reach Local/Municipal/Regional 
Policy Influence Type Influenced training of practitioners or researchers
URL https://prism.ac.uk/2020/08/research-software-engineering-and-prism/
 
Description Application Customisation: Enhancing Design Quality and Developer Productivity
Amount £1,263,356 (GBP)
Funding ID EP/P010040/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 03/2017 
End 02/2022
 
Description COMAC Centre
Amount £3,000,000 (GBP)
Funding ID Beijing Aeronautical Science& Technology Research Institute (BASTRI) of Commercial Aircraft Corporation of China (COMAC) 
Organisation Commercial Aircraft Corporation of China 
Sector Private
Country China
Start 07/2019 
End 07/2024
 
Description ELEMENT - Exascale Mesh Network
Amount £245,611 (GBP)
Funding ID EP/V001345/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 04/2020 
End 06/2021
 
Description EPSRC CENTRE FOR DOCTORAL TRAINING IN THE MATHEMATICS OF PLANET EARTH AT IMPERIAL COLLEGE LONDON AND THE UNIVERSITY OF READING
Amount £5,463,490 (GBP)
Funding ID EP/L016613/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 03/2014 
End 09/2022
 
Description EPSRC Centre for Doctoral Training in High Performance Embedded and Distributed Systems
Amount £4,081,693 (GBP)
Funding ID EP/L016796/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 03/2014 
End 09/2022
 
Description EPSRC Impact Acceleration award "Multi-scale adjoint-enabled modelling to improve operational storm surge forecasting at the Flood Forecasting Centre (FFC) and support the wider modelling community" (PI - Matt Piggott)
Amount £66,000 (GBP)
Funding ID EPSRC Impact Acceleration award "Multi-scale adjoint-enabled modelling to improve operational storm surge forecasting at the Flood Forecasting Centre (FFC) and support the wider modelling community" 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2019 
End 09/2021
 
Description EPSRC Impact Acceleration award (Co-I Colin Cotter)
Amount £25,349 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2019 
End 03/2020
 
Description EPSRC iCASE PhD project with Shell "Computational / data science techniques to improve and integrate weather forecasting in business decision-making" (Matt Piggott)
Amount £100,000 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2019 
End 09/2023
 
Description Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation.
Amount £159,456 (GBP)
Funding ID EP/V001493/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 04/2020 
End 06/2021
 
Description Health assessment across biological length scales for personal pollution exposure and its mitigation (INHALE)
Amount £2,793,915 (GBP)
Funding ID EP/T003189/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 04/2019 
End 03/2022
 
Description JUNO: A Network for Japan - UK Nuclear Opportunities
Amount £488,145 (GBP)
Funding ID EP/P013600/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 11/2016 
End 11/2021
 
Description Managing Air for Green Inner Cities
Amount £4,173,134 (GBP)
Funding ID EP/N010221/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 12/2015 
End 12/2020
 
Description NSFPLR-NERC: Melting at Thwaites grounding zone and its control on sea level (THWAITES-MELT)
Amount £206,031 (GBP)
Funding ID NE/S006427/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 09/2018 
End 08/2023
 
Description On the way to the asymptotic limit: mathematics of slow-fast coupling in PDEs
Amount £849,609 (GBP)
Funding ID EP/R029628/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 08/2018 
End 07/2022
 
Description On the way to the asymptotic limit: mathematics of slow-fast coupling in PDEs
Amount £849,609 (GBP)
Funding ID EP/R029628/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 08/2018 
End 07/2022
 
Description PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems (PREMIERE)
Amount £6,560,538 (GBP)
Funding ID EP/T000414/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2019 
End 09/2024
 
Description PhD studentship from the EPSRC Centre for Doctoral Training in Partial Differential Equations
Amount £58,000 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2018 
End 10/2021
 
Description PhD studentship from the EPSRC Centre for Doctoral Training in Partial Differential Equations
Amount £58,000 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2018 
End 10/2021
 
Description Three dimensionality and Instabilities of Leading-Edge Vortices
Amount £449,805 (GBP)
Funding ID EP/S029389/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 09/2019 
End 09/2022
 
Description UK Turbulence Consortium
Amount £693,229 (GBP)
Funding ID EP/R029326/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2018 
End 09/2022
 
Title Research Software Engineering and PRISM 
Description The PRISM platform is characterised by its group of advanced scientific research software and the teams that build and maintain this software. Software engineering expertise is therefore a significant part of PRISM. The term Research Software Engineering or RSE is becoming increasingly common within the research community. Indeed, the acronym "RSE" may be something that you are already familiar with or have encountered as it becomes more widely used. The RSE movement, which has developed over recent years, goes beyond purely considering expertise in building research software to include aspects such as best practices, careers, training, policy development and various other areas. 
Type Of Material Improvements to research infrastructure 
Year Produced 2020 
Provided To Others? Yes  
Impact Within the teams that are part of PRISM, there are many researchers and academics who spend much of their time writing code. In some cases, these individuals may identify themselves as Research Software Engineers while in other cases they may simply consider themselves as researchers who spend a lot of their time coding. Either way, there is lots that an active research software community can offer these people, from events at which to present their work and network with others developing software in different research fields through to offering training and offering opportunities to get involved with providing training to others. Imperial College London has a Research Software Community in which there are members of PRISM who are active participants. This includes helping to run the community as part of its organisational committee and attending events and activities provided by the community. PRISM also has links with the wider London and South East of England regional research software community RSLondon. One of UK Engineering and Physical Sciences Research Council (EPSRC)'s 11 Research Software Engineering Fellows is directly linked with PRISM through a work programme that includes continuation of a previous collaboration with the Nektar++ team. This work is developing tools and services to support bridging the gap between the code and growing user communities. These user communities include individuals who have limited technical computing knowledge but advanced scientific and mathematical knowledge to support their use of the code and its outputs. 
URL https://prism.ac.uk/2020/08/research-software-engineering-and-prism/
 
Description Hewlett Packard: Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation Hewlett Packard Ltd
Country United Kingdom 
Sector Private 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact multi-disciplinary
Start Year 2020
 
Description IBM: Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation IBM
Country United States 
Sector Private 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact multi-disciplinary
Start Year 2020
 
Description McLaren Racing 
Organisation McLaren Racing
Country United Kingdom 
Sector Private 
PI Contribution We have transferred fundamental ideas behind vortex stability and identification to their design practice. More recently we are been applying computational modelling tools developed in an academic setting to example flow problems of direct interest to McLaren.
Collaborator Contribution Data and motivation on how to focus our research direction
Impact .
Start Year 2007
 
Description Met Office 
Organisation Meteorological Office UK
Country United Kingdom 
Sector Academic/University 
PI Contribution GungHo - a next generation atmospheric dynamical core for weather and climate modelling Some of the key aspects The grid that the model is discretized on. Removal of the singularity in the current latitude-longitude grid is considered essential to achieving good scalability. Although no alternative grid is without its own issues, the cubed-sphere grid has a number of advantages over other choices and is currently the preferred option. Highly scalable implicit solvers. There are significant advantages to retaining a two-time-level implicit temporal discretization, but this is only viable if the resulting implicit system, with its global connectivity, can be efficiently solved on hundreds of thousands of processors. Inherently conservative advection schemes. Only dry mass is inherently conserved by the current dynamical core, yet there is a growing need to exactly conserve a number of tracer fields, as well as possibly such quantities as energy and angular momentum. This requires replacement of the current pointwise semi-Lagrangian scheme with a flux-form conserving advection scheme, be that a semi-Lagrangian one or an Eulerian one, while preserving the good phase properties of the current scheme. The spatial discretization. A mixed finite-element spatial discretization, as distinct from the current finite-difference/finite-volume approach, permits the use of alternative grid structures without some of the disadvantages that those grids incur with a finite-difference discretization. A new modelling infrastructure has been designed to permit the efficient implementation of these changes. This is called LFRic after Lewis Fry Richardson (see Related pages). A further important element is how each of the above interacts with, and depends upon, each other. Key aims To design and develop a dynamical core that scales well on hundreds of thousands of processors while maintaining at least the accuracy and robustness of its contemporary dynamical core. To improve the conservation properties of the dynamical core.
Collaborator Contribution Some of the key aspects The grid that the model is discretized on. Removal of the singularity in the current latitude-longitude grid is considered essential to achieving good scalability. Although no alternative grid is without its own issues, the cubed-sphere grid has a number of advantages over other choices and is currently the preferred option. Highly scalable implicit solvers. There are significant advantages to retaining a two-time-level implicit temporal discretization, but this is only viable if the resulting implicit system, with its global connectivity, can be efficiently solved on hundreds of thousands of processors. Inherently conservative advection schemes. Only dry mass is inherently conserved by the current dynamical core, yet there is a growing need to exactly conserve a number of tracer fields, as well as possibly such quantities as energy and angular momentum. This requires replacement of the current pointwise semi-Lagrangian scheme with a flux-form conserving advection scheme, be that a semi-Lagrangian one or an Eulerian one, while preserving the good phase properties of the current scheme. The spatial discretization. A mixed finite-element spatial discretization, as distinct from the current finite-difference/finite-volume approach, permits the use of alternative grid structures without some of the disadvantages that those grids incur with a finite-difference discretization. A new modelling infrastructure has been designed to permit the efficient implementation of these changes. This is called LFRic after Lewis Fry Richardson (see Related pages). A further important element is how each of the above interacts with, and depends upon, each other. Key aims To design and develop a dynamical core that scales well on hundreds of thousands of processors while maintaining at least the accuracy and robustness of its contemporary dynamical core. To improve the conservation properties of the dynamical core.
Impact multi-disciplinary
Start Year 2010
 
Description Naval Postgraduate School 
Organisation Naval Postgraduate School, Monterrey CA
Country United States 
Sector Academic/University 
PI Contribution Collaboration with DR THOMAS GIBSON (NRC fellow at the Naval Postgraduate School) who actively develops for the Firedrake Project: an open-source software package for automating the solution of PDEs using the finite element method.
Collaborator Contribution Collaboration with DR THOMAS GIBSON (NRC fellow at the Naval Postgraduate School) who actively develops for the Firedrake Project: an open-source software package for automating the solution of PDEs using the finite element method.
Impact Collaboration with DR THOMAS GIBSON (NRC fellow at the Naval Postgraduate School) who actively develops for the Firedrake Project: an open-source software package for automating the solution of PDEs using the finite element method.
Start Year 2019
 
Description Rolls Royce 
Organisation Rolls Royce Group Plc
Country United Kingdom 
Sector Private 
PI Contribution We have been exploring the application of the Nektar++ software to turbo-machinery problem.
Collaborator Contribution Access to data and expert knowledge of the field as well as exposure to other researcher supported by Rolls Royce
Impact Presentations of methods at international conferences and internal workshops
Start Year 2017
 
Description Schlumberger: Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation Schumberger
Country United Kingdom 
Sector Private 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact multi-disciplinary
Start Year 2020
 
Description Scientists in the dynamics research group at the Met Office are using Firedrake to develop new numerics and solvers for weather and climate simulation. 
Organisation Meteorological Office UK
Country United Kingdom 
Sector Academic/University 
PI Contribution Scientists in the dynamics research group at the Met Office are using Firedrake to develop new numerics and solvers for weather and climate simulation.
Collaborator Contribution Scientists in the dynamics research group at the Met Office are using Firedrake to develop new numerics and solvers for weather and climate simulation.
Impact Scientists in the dynamics research group at the Met Office are using Firedrake to develop new numerics and solvers for weather and climate simulation.
Start Year 2019
 
Description Technical University of Munich: Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation Technical University of Munich
Country Germany 
Sector Academic/University 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact multi-disciplinary
Start Year 2020
 
Description Technical University of Munich: Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation Technical University of Munich
Country Germany 
Sector Academic/University 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact multi-disciplinary
Start Year 2020
 
Description UCL: Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact multi-disciplinary
Start Year 2020
 
Description University at Buffalo (SUNY): Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation University at Buffalo
Country United States 
Sector Academic/University 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact multi-disciplinary
Start Year 2020
 
Description University of Bath: Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation University of Bath
Country United Kingdom 
Sector Academic/University 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact multi-disciplinary
Start Year 2020
 
Description University of Durham 
Organisation Durham University
Country United Kingdom 
Sector Academic/University 
PI Contribution Collaboration with Dr Lawrence Mitchell (Assistant Professor in the Department of Computer Science) who develops compilers and software abstractions for the development of numerical models implemented using the finite element method. This research is concretely realised in the open source Firedrake project.
Collaborator Contribution Collaboration with Dr Lawrence Mitchell (Assistant Professor in the Department of Computer Science) who develops compilers and software abstractions for the development of numerical models implemented using the finite element method. This research is concretely realised in the open source Firedrake project.
Impact Collaboration with Dr Lawrence Mitchell (Assistant Professor in the Department of Computer Science) who develops compilers and software abstractions for the development of numerical models implemented using the finite element method. This research is concretely realised in the open source Firedrake project.
Start Year 2019
 
Description University of Leeds: Gen X: ExCALIBUR working group on Exascale continuum mechanics through code generation 
Organisation University of Leeds
Country United Kingdom 
Sector Academic/University 
PI Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Collaborator Contribution Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Impact Continuous physical processes pervade every aspect of our society, industry and the natural world. From the flow of air over an aircraft to the propagation of mobile phone signals, to the behaviour of chemical components at every point of the manufacturing processes, continuum mechanics is at the heart of our industrial processes. In medicine, the electrical behaviour of the heart and brain, the flow of blood and other fluids through the body, and the detection of disorders using all manner of scanners and detectors are all continuum mechanics processes. In the natural world, detecting and understanding the movement and composition of the Earth enable us to understand earthquakes and to hunt for valuable minerals, while advanced understanding of the complex interaction of fluids and electromagnetic fields allows us to understand stars, the cosmos and our place in it. In all of these cases and many more beside, the mathematical equations describing phenomena are known, but solutions very rarely exist. Science and engineering are essentially dependent on computer simulation to understand any of these systems, and to design the devices and processes which use them. Many of these phenomena are so complex or have such a range of spatial scales that existing petascale computer systems are a limit on scientific advance. In addition, there is a need to go beyond mere simulation to simulate the uncertainty in processes, find the optimal solution, or discover the multiple possible outcomes of a system. The advent of exascale computing presents the opportunity to address these limitations. However, increasing computational scale, increasingly complex simulation algorithms, and the vast quantities of data produced by exascale computing will defeat not just existing simulation software, but also existing ways of writing simulation software. Gen X is a project to establish the requirements for exascale simulation software for continuum mechanics, and to provide a concrete way of achieving this capability within the next five years. The Gen X approach is to move beyond just writing code to a system of specialist simulation languages which enable scientists and engineers to specify the problem they want to solve and the algorithms they want by writing mathematics, the language of science. The actual code will be automatically generated by specialist compilers rather than hand-written. Rather than an algorithm developer writing a paper about their new development and hoping that simulation scientists will find the time to code it up for their specific problem, the algorithm will be encoded in a domain specific language and implemented in its compiler. The simulation scientist will then be able to access the algorithm directly without recoding. At exascale, writing all the simulation outputs to disk for later analysis is impossible. Instead, simulation data must be processed, analysed and visualised as the simulation is conducted, and only the results stored for later use. Gen X will provide mathematical languages for this process which will enable the scientist or engineer to concisely specify the analysis to be performed, and to have confidence that the resulting calculations will be both efficient and correct. By enabling scientists and engineers to work at a higher mathematical level while also accessing more sophisticated algorithms and hardware-specific implementations than previously possible, Gen X will make simulation science both more capable and more productive. In this manner, Gen X is essential to realising the potential of exascale computing while also making the most efficient use of research resources.
Start Year 2020
 
Description University of São Paulo 
Organisation Federal University of São Paulo
Country Brazil 
Sector Academic/University 
PI Contribution Researchers at the university of Sao Paulo are using Firedrake for a variety of challenges related to seismic inversion. Dr Ham visited in November 2019 and gave a Firedrake tutorial.
Collaborator Contribution Researchers at the university of Sao Paulo are using Firedrake for a variety of challenges related to seismic inversion. Dr Ham visited in November 2019 and gave a Firedrake tutorial.
Impact Researchers at the university of Sao Paulo are using Firedrake for a variety of challenges related to seismic inversion. Dr Ham visited in November 2019 and gave a Firedrake tutorial.
Start Year 2019
 
Title DEVITO V4.0 
Description Devito is a Domain-specific Language (DSL) and code generation framework for the design of highly optimised finite difference kernels for use in inversion methods. 
Type Of Technology Software 
Year Produced 2019 
Open Source License? Yes  
Impact Devito is a Domain-specific Language (DSL) and code generation framework for the design of highly optimised finite difference kernels for use in inversion methods. 
 
Title Devito v4.2 
Description A Domain-specific Language (DSL) and code generation framework for the design of highly optimised finite difference kernels for use in inversion methods. 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
Impact Devito v4.2 now supports multi-node-multi-GPU domain-decomposition parallelization and has become a NumFOCUS affiliated project 
 
Title NEKTAR++V5.0.0 
Description Nektar++ is a tensor product based finite element package designed to allow one to construct efficient classical low polynomial order h-type solvers (where h is the size of the finite element) as well as higher p-order piecewise polynomial order solvers. 
Type Of Technology Software 
Year Produced 2019 
Open Source License? Yes  
Impact The latest version of Nektar++, v5.0.0, was released on the 9th December 2019. It can be downloaded from the downloads page.This release includes a wide range of new library features as well as many other improvements and bug fixes. Many of the solvers and utilities have also received major improvements. 
 
Title Nekmesh: an open-source high-order mesh generator 
Description High-order curvilinear meshes are both an enabler and a bottleneck towards achieving high-resolution flow simulations about complex geometries. The open-source code Nekmesh is the Imperial College London contribution towards improving the high-order mesh generation process, an area where both commercial and academic codes are scarce. Nekmesh has been specifically designed to tackle the significant challenge of automatically generating valid, high-quality curvilinear meshes for complex three-dimensional geometries with a particular emphasis on simulating high-Reynolds number aeronautical and fluid dynamics flows. 
Type Of Technology Software 
Year Produced 2018 
Open Source License? Yes  
Impact One of the very few codes either commercial or academic able to generate high-order meshes from CAD. Unique in allowing generation of meshes with polynomial orders P>4. 
 
Title Nektar++ Version 4.2.0 
Description Nektar++ is a tensor product based finite element package designed to allow one to construct efficient classical low polynomial order h-type solvers (where h is the size of the finite element) as well as higher p-order piecewise polynomial order solvers. 
Type Of Technology Software 
Year Produced 2015 
Open Source License? Yes  
Impact The Nektar++ framework has been an underpinning framework for a range of solver technologies which at Imperial includes: 1) Incompressible flow simulation and stability analysis related to car aerodynamics with McLaren Racing and offshore engineering 2) Biomedical modelling in atrial arrthymia in collaboration Hammersmith Hospital and Cardiovascular modelling in collaboration with Bioengineering 3) Compressible flow modelling with collaboration with Airbus and more recent interest form Rolls Royce. The wider community of Nektar++ usage can be captured in the following: - It has an active user list currently with 76 registered from Europe, USA, South America, Australia and China - It has an active code development community: Over the past 3.5 years we have had over 4500 commits and had 500 merge requests completed in our Gitlab repository. - Over the past five months, the most recent version of the code (v4.2.0) has been downloaded 2473 times with increasing usage of Debian and Fedora packages. - Our overview paper (doi:10.1016/j.cpc.2015.02.008) was published in Computer Physics Communications in July 2015 and has been either 1st or 2nd on the most downloaded list since this time. - Our inaugural Nektar++ workshop in 2015 had 30 participants from the UK, Europe and Australia. (http://www.nektar.info/community/workshops/nektar-2015/) - The package is supported on a number of HPC facilities e.g. ARCHER, Argonne/ORNL, INRIA, Imperial HPC cluster (Cx1,Helen) External to imperial our closest development activities are currently with the Universities of Utah and Brown in USA, University of Madrid (Spain), University of Darmstadt (Germany) and the University of Sao Paolo (Brazil). We have also had recent interest from UK users at Cambridge, Nottingham and Loughborogh Universities as well as notable users acvitity from Warsaw University, Harbin Institute of Technology in China, Beihang University, Middle East Technical University, Monash University and the University of Western Australia. 
URL http://www.nektar.info/downloads/file/nektar-4-2-0-tar-gz/
 
Title Nektar++ v5.0.1 
Description A tensor product based finite element package designed to allow one to construct efficient classical low polynomial order h-type solvers (where h is the size of the finite element) as well as higher p-order piecewise polynomial order solvers. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact The latest version of Nektar++, v5.0.1, was released on the 21st January 2021. It can be downloaded from the downloads page. 
 
Title PYFR 1.9.0 
Description PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures using the Flux Reconstruction approach of Huynh. The framework is designed to solve a range of governing systems on mixed unstructured grids containing various element types. It is also designed to target a range of hardware platforms via use of an in-built domain specific language derived from the Mako templating engine. 
Type Of Technology Software 
Year Produced 2019 
Open Source License? Yes  
Impact Latest release of PyFR 1.9.0 includes: • Improved strong scaling. • Added support for Gmsh v4.1. • Fixed performance issue with OpenCL backend. 
 
Title THETIS 
Description Unstructured mesh coastal ocean model in 2D and 3D, built using Firdrake and including adaptive mesh and adjoint capabilities. 
Type Of Technology Software 
Year Produced 2019 
Open Source License? Yes  
Impact A new (coastal) ocean model, in 2D and 3D, using finite element methods, and implemented via the Firedrake framework. Includes an adjoint capability for sensitivity analyses and optimisation. Also includes a preliminary mesh adaptivity capability. 
 
Title Thetis 
Description A new (coastal) ocean model, in 2D and 3D, using finite element methods, and implemented via the Firedrake framework. Includes an adjoint capability for sensitivity analyses and optimisation. Also includes a preliminary mesh adaptivity capability. 
Type Of Technology Software 
Year Produced 2016 
Open Source License? Yes  
Impact Basis for ongoing collaboration with the wider ocean model development community. 
URL http://thetisproject.org/
 
Description 2020 RICE OIL & GAS HPC CONFERENCE, Workshop: From Zero-to-Devito 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The Devito workshop participants learnt how to implement finite difference and inverse solvers using Devito.

https://www.devitoproject.org/
Year(s) Of Engagement Activity 2020
 
Description 2ND FIREDRAKE WORKSHOP 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact The second workshop provided the opportunity for Firedrake users and developers to engage with each other to communicate the ways that Firedrake can be used in simulation science, the latest developments in the project, and the future developments anticipated.
Year(s) Of Engagement Activity 2018
 
Description 2nd PRISM workshop on applications: Beyond CFD 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Beyond CFD: In this workshop experiences on application of PDE solvers which go beyond CFD tools, for example composable solvers, stability analysis, inverse problems, data assimilation and uncertainty quantification were shared. The format of the on-line workshop involved a series of 3 short 10-minutes talks followed by small group discussions/panel meeting and a summary session.

The event's programme included:

2.00pm-2.15pm Matt Knepley (University at Buffalo) on "Building Complex Solvers in PETSc"
2.15pm-2.30pm Patrick Farrell (University of Oxford) on "Computing multiple solutions of PDEs"
2.30pm-2.45pm Koki Sagiyama (Imperial College London) on "Firedrake: Solving equations on subspaces "
2.45pm-3.30pm Small group discussions/Panel meeting
3.30pm-3.45pm Summary session
Year(s) Of Engagement Activity 2020
URL https://prism.ac.uk/2020/09/2nd-prism-workshop-on-applications-beyond-cfd/
 
Description 3RD FIREDRAKE WORKSHOP 2019 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact The workshop began with a half day Firedrake tutorial for interested new users. See the programme for detailed timings: https://firedrakeproject.org/firedrake_19.html.
Year(s) Of Engagement Activity 2019
 
Description 4TH FIREDRAKE WORKSHOP 2020 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact This was a first workshop in North America at the University of Washington
Year(s) Of Engagement Activity 2020
 
Description 4th NEKTAR++ WORKSHOP 2019 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact The 4th annual Nektar++ Workshop brought together developers and users of all experiences to hear about new and future developments in Nektar++ and the exciting science and engineering being undertaken with the code. The first two days included a comprehensive programme of talks, which were followed by a number of parallel informal group sessions allowing developers and users to discuss and work on specific aspects of the code.
Year(s) Of Engagement Activity 2019
 
Description Automating forward and adjoint coupling in finite element geoscience simulations 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact In this project we are enabling 'coupling' in the Firedrake stack, for the purpose of simulation, optimisation and uncertainty quantification. We are particularly interested in the type of coupling in which two or more domains of possibly distinct physical natures interact with each other via interfaces.

One characteristic example of such coupling is 'ocean-atmosphere coupling' that aims to explain global climate taking into account the interaction between the ocean currents and the atmospheric circulation via, e.g., heat exchange on the ocean surface. Another is 'domain-decomposition' often employed in wave propagation problems; an originally monolithic domain is artificially decomposed into smaller subdomains of appropriate size for computation, and solutions in the subdomains interact with each other via the artificial interface to finally form a global solution. A third example is fluid-structure interaction, where the fluid and solid satisfy different equations that need to be coupled at the boundary. This has important applications e.g. in designing wave/wind/tidal turbines etc.

Our current development in Firedrake is to facilitate numerical simulations and model development in these fields.
Year(s) Of Engagement Activity 2020
URL https://prism.ac.uk/2020/04/blog-entry-automating-forward-and-adjoint-coupling-in-finite-element-geo...
 
Description Devito Book Summer Project with Imperial College London 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Undergraduate students
Results and Impact Rini Banerjee, a student of Joint Mathematics and Computer Science at Imperial College London who spent summer 2020 doing a remote research internship on the Devito Project, under the supervision of Prof Paul Kelly and Dr Gerard Gorman. Rini has been working on the Devito Book: a set of Jupyter Notebook tutorials that teach the finite difference method for solving partial differential equations using Devito, based on the textbook "Finite Difference Computing with PDEs - A Modern Software Approach" by H. P. Langtangen and S. Linge.
Year(s) Of Engagement Activity 2020
URL https://techcommunity.microsoft.com/t5/educator-developer-blog/devito-book-summer-project-with-imper...
 
Description FIREDRAKE TUTORIAL - GERMANY 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact There was a hands-on Firedrake tutorial at the Aachen Institute for Advanced Study in Computational Engineering Science (AICES).
Year(s) Of Engagement Activity 2019
 
Description FIREDRAKE TUTORIAL - UK 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact The Firedrake team once again offered a half day Firedrake tutorial aimed at new Firedrake users. The tutorial was an introduction to solving PDEs using the finite element method with Firedrake. The lecture was pitched at new MRes and PhD students just starting to use or develop Firedrake
Year(s) Of Engagement Activity 2019
 
Description FIREDRAKE TUTORIAL - USA 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact The Firedrake team presented a live cloud tutorial at the SIAM Conference on Computational Science and Engineering in Spokane Washington.
Year(s) Of Engagement Activity 2019
 
Description Great Exhibition Festival 2019 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact The Great Exhibition Road Festival is a free three-day celebration of curiosity, discovery and exploration in South Kensington. Over the summer, Imperial partnered with 20 neighbours across Exhibition Road and South Kensington, including some of the world's most iconic museums, to create a unique new festival. Over 60,000 people attended the first ever Great Exhibition Road Festival at the end of June to enjoy a mixture of art and science, culture and local history, technology and curiosity.
Year(s) Of Engagement Activity 2019
 
Description HIFICOMA 2019: WORKSHOP ON SPECTRAL/HP ELEMENT METHOD USING NEKTAR++ 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact We are delighted to report that the following members of the PRISM team: Chris Cantwell, Dave Moxey, Joaquim Peiro, Spencer Sherwin were invited to organise workshop on Spectral/hp element method using Nektar++ during the symposium International Symposium on High-Fidelity Computational Methods & Applications 2019, HiFiCoMa 2019, which was held in Shanghai. The objective of this symposium was to bring together experts in computational science and experts in engineering application to exchange new ideas and discuss development perspectives of high-fidelity methods. It also offered a platform to show the exciting scientific and engineering study undertaken in this area. The symposium ended with a Nektar++ workshop to provide a more opportunity to understand how to apply high order spectral/hp element software. More information on the event is available here: https://www.ishfcma.org/
Year(s) Of Engagement Activity 2019
 
Description INTERNATIONAL CONFERENCE ON SPECTRAL AND HIGH ORDER METHODS (ICOSAHOM) 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Scientific scope: The purpose of this conference series was to bring together researchers and practitioners with an interest in the theoretical, computational and applied aspects of high-order and spectral methods for the solution of differential equations.
Subjects included, but were not limited to: spectral methods, high-order finite difference methods, p and hp finite element methods, discontinuous Galerkin methods, ENO/WENO methods, high order methods for integral equations, wavelet-based methods, stochastic methods, efficient solvers and preconditioners for high order methods, efficient time-stepping methods, parallel and computational aspects, flux reconstruction.
Outcomes:
• The Christine Bernardi Award was given for her outstanding contributions in the area of "high-order approximations for the solution of PDE's". The 2018 Christine Bernardi Award was presented with a €1,000 cash prize during the celebration of the 50th anniversary of the Laboratoire Jacques Louis Lions where she was working. The Laureate was invited to give a talk at this occasion. The award was presented to honor Christine Bernardi, CNRS senior researcher at Laboratoire Jacques-Louis Lions at Sorbonne University (formerly known as Université Pierre et Marie Curie) in numerical analysis, who prematurely passed away on March 10, 2018. She was a leading figure in the domain of finite element and spectral methods and had contributions both in delicate a priori and posteriori estimates and in new numerical approaches in fluid flows and electromagnetism.
• The live streams of all the conference plenary talks can be found on the plenary speakers' page. http://icosahom2018.org/programme/plenaryspeakers/
• WINASc reception for female participants: there was a special drinks reception for women participants on Tuesday evening, 18:30-19:45, at 170 Queens Gate in the Drawing Room. This reception was hosted by Fengyan Li, Jennifer Ryan, and Beth Wingate, in conjunction with WINASc (Women in Numerical Analysis and Scientific Computing) and was made possible through the ICOSAHOM organization and their sponsors (EPSRC, Rolls-Royce, PRISM, AFOSR, and Imperial College London).
Year(s) Of Engagement Activity 2018
 
Description Improving the performance of Nektar++ with SIMD 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact In modern computer architectures, the gap between processor clock speed and memory bandwidth is constantly increasing, meaning that to attain optimal performance, algorithms with a high degree of arithmetic intensity - i.e the ratio between computations performed and the amount of data transferred from the memory (DRAM) - are required. In this context, high-order finite element methods are particularly attractive due to their high (and tunable) arithmetic intensity. Nektar++ is a finite element package designed to allow one to construct efficient classical low polynomial order h-type solvers (where h is the size of the finite element) as well as higher p-order piecewise polynomial solvers. The Nektar++ library comes with a number of solvers and also allows one to construct a variety of new ones. The main solvers provided are a continuous Galerkin incompressible Navier-Stokes solver and a discontinuous Galerkin compressible Navier-Stokes solver. These solvers are routinely applied to industrially relevant simulations; typical applications encompass external aerodynamics (for instance the flow around cars) as well as internal aerodynamics (for instance the flow in aircraft engines). The use single-instruction multiple-data (SIMD) vectorization, that is prevalent on modern hardware, is a well-studied solution for the efficient implementation of high-order operators. We are in the process of integrating within the Nektar++ library some operators (which are based on the work of Moxey et al., 2020) that take advantage SIMD hardware. The intent is to improve the efficiency of the Nektar++ library with the specific end goal of accelerating the compressible flow solver. Figure Caption: Roofline analysis for the vectorized Helmholtz operator (Moxey et al., 2020) on Broadwell CPU using deformed hexadral (triangle) and undeformed hexahedral (squares) elements with varying polynomial order (1-20).
Year(s) Of Engagement Activity 2020
URL https://prism.ac.uk/2020/04/blog-entry-improving-the-performance-of-nektar-with-simd/
 
Description Organisation of 3rd PRISM Workshop on Application of Time-Stepping Techniques 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact In this workshop we wish to shared experiences on application of time-stepping techniques, for example parallel time integration, encapsulation of time integration and implicit time integration. As before the format of the on-line workshop involved a series of 3 short 15-minutes talks followed by a group discussions and a summary session.

The event's programme included:

3.00pm-3.15pm Scott MacLachlan (Memorial University of Newfoundland) on Parallel time integration

3.20pm-3.35pm Rob Kirby (Baylor University) on Encapsulation of time integration

3.40pm-3.55pm Zhenguo Yan  (Imperial College London) on Implicit time integration

4.00pm-4.30pm Group discussions

4.30pm-4.45pm Summary
Year(s) Of Engagement Activity 2021
URL https://prism.ac.uk/2021/01/3rd-prism-workshop-on-application-of-time-stepping-techniques/
 
Description PRISM workshop on best practices for software training and workshops 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact PRISM workshop on best practices for software training and workshops: Exploring online teaching in a post-pandemic era!
Date: 21st May 2020
Location: on-line
Summary: In this workshop we shared experiences and best practices on the use of workshops and tutorials for the PRISM related software. In light of the currently changes due to the Covid-19 pandemic it was also interesting to ask how our training experiences are likely to change at a broader level including all forms of remote teaching. The format of the on-line workshop involved a series of 3 or 4 short 10-minutes talks followed by small group discussions and a summary session.
The programme included presentations by:

2.00pm-2.15pm David Ham on Firedrake
2.15pm-2.30pm Spencer Sherwin / David Moxey on Nektar ++
2.30pm-2.45pm Matt Piggott / Gerard Gorman on Jupiter notebook
2.45pm-3pm Katerina Michalickova on Software Carpentry
3pm-4pm Brainstorming session on establishing best practices.
Year(s) Of Engagement Activity 2020
URL https://prism.ac.uk/2020/05/prism-workshop-on-best-practices-for-software-training-and-workshops/
 
Description Participation in the first global, virtual TRANSFORM 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The first global, virtual TRANSFORM took place in September 2020 (TRANSFORM 2020: Schedule). The Software Underground brought lots of interesting and useful sessions on the digital subsurface. This event was a bit different from most conferences: the sessions were fully participatory and interactive.

Rhodri Nelson from Imperial College London gave a tutorial on "Geophysical Modeling with Devito" which can be seen in full here: Tutorial: Geophysical Modeling with Devito - YouTube
Year(s) Of Engagement Activity 2020
URL https://transform2020.sched.com/
 
Description RSE HACK EVENT WITH MICROSOFT AND THE ALAN TURING INSTITUTE 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact This event focused on the theory and practise of automated testing and verification of research software and is critical reproducible research.
Year(s) Of Engagement Activity 2020
 
Description THE IUTAM SYMPOSIUM ON LAMINAR-TURBULENT TRANSITION 2019 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The scientific programme covered a range of fundamental topic areas, including: Global analysis of instabilities and receptivities for complex configurations; Nonlinear dynamical-systems approaches to minimal seeds and transition to turbulence; Influence of multi-physics phenomena on transition: reactive flows, non-Newtonian material behaviour, interfacial flows, flows with interacting structures; Novel experimental measurement and evaluation techniques for transition in complex flows; Roughness-induced transition; transition from steps, gaps, junctions and other geometric imperfections; Transition in hypersonic flows; prediction of thermal loads; Active and passive control of flows undergoing transition; transition delay; Transition mechanisms in natural and controlled environments; receptivity techniques and studies; Late stages of transition and the breakdown to fully developed turbulence; Transient growth problems and bypass mechanisms and their role in the transition process.

Outcomes:
• We received very positive feedback from attendees on the well organised and attended meeting.
• Symposium was well attended by early-career academics, post-graduate students, industry representatives, senior members of the community and invited guests.
• 175 registered delegates of which 40% are PhDs
• Evening reception (Monday, 2nd September) and conferenced dinner (on the 5th September) provided networking opportunities for attendees to discuss future collaborations.
Year(s) Of Engagement Activity 2019
 
Description The wake passing effect in LPTs with Nektar++ 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact In a gas turbine engine, the pressure expansion through the high- and low-pressure turbines (LPT) is achieved in a number of subsequent stages. The interaction of multiple stages of rotors and stators is a crucial source of deterministic unsteadiness which has repercussions on the loss production mechanisms, and it is thus of great importance to designers.

To model the bar passing effect, the Smoothed Profile Method (SPM) approach was adopted and incorporated in the Nektar++ framework. Extensive preliminary validation was carried out to ensure the generation of a realistic cylinder wake. As part of the SPM formulation, an interface thickness parameter must be selected to represent the rigid particles. The interface thickness was selected to ensure accurate representation of the SPM boundaries (thus driven by resolution requirements). An auxiliary study focused on varying the diameter of the cylinders at fixed interface thickness. A smaller bar diameter of 60% the width of the nominal diameter produced wake profiles and spectral characteristics that very closely match those of a corresponding DNS simulation over the entire range of Reynolds numbers analysed.
Year(s) Of Engagement Activity 2020
URL https://prism.ac.uk/2020/11/blog-the-wake-passing-effect-in-lpts-with-nektar/
 
Description Thetis workshop at the Korean Institute of Ocean Science and Technology 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact 5-day finite element training
Year(s) Of Engagement Activity 2019
 
Description Thetis workshop at the Maldives National University 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Thetis is an unstructured grid coastal ocean model built using the Firedrake finite element framework. Currently Thetis consists of 2D depth averaged and full 3D baroclinic models.
Year(s) Of Engagement Activity 2019
 
Description Virtual Symposium and Tutorial Day held for CFD solver PyFR 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact A symposium and tutorial day for the CFD solver PyFR have been held virtually.

PyFR is a high-order accurate CFD solver designed for solving unsteady turbulent flow problems in the vicinity of complex geometries. It has application in a range of engineering sectors, including commercial and military aviation, wind engineering and submarine design. The project is jointly led by Dr Peter Vincent in the Department of Aeronautics and Prof Freddie Witherden in the Department of Ocean Engineering at Texas A&M University.

The PyFR Symposium 2020 consisted of talks from both industry and the PyFR team. The event covered a range of topics related to the theory of high-order Flux Reconstruction schemes, their implementation in PyFR, and their application to industrially relevant flow problems.

An additional event, the PyFR Tutorial Day 2020, provided step-by-step guidance on running scale-resolving CFD simulations with PyFR in parallel on multiple GPUs, as well as an overview of the PyFR codebase, and deep-dive sessions into specific topics of interest. Access to computing resources were provided by Amazon via their cloud platform.

Dr Peter Vincent hailed both events as "a great success". He added that "the overarching objective of the symposium was to help bridge the gap between industrial requirements and academic research activities, and I think we achieved that - the talks have led to a lot of offline discussions, and opportunities for collaboration."

The symposium also saw talks from the likes of MBDA, Zenotech and Pointwise as well as from the PyFR team, who described recent developments in numerics/software, and application of PyFR to a range of test cases.

Recordings and slide decks taken from all the talks given at the PyFR Symposium are now available on the PyFR website: http://pyfr.org/events.php
Year(s) Of Engagement Activity 2020
URL https://www.imperial.ac.uk/news/199255/virtual-symposium-tutorial-day-held-cfd/