DiRAC 2.5 - the pathway to DiRAC Phase 3
Lead Research Organisation:
University of Leicester
Department Name: Physics and Astronomy
Abstract
Physicists across the astronomy, nuclear and particle physics communities are focussed
on understanding how the Universe works at a very fundamental level. The distance scales
with which they work vary by 50 orders of magnitude from the smallest distances probed
by experiments at the Large Hadron Collider, deep within the atomic
nucleus, to the largest scale galaxy clusters discovered out in space. The Science challenges,
however, are linked through questions such as: How did the Universe begin and how is it evolving?
and What are the fundamental constituents and fabric of the Universe and how do they interact?
Progress requires new astronomical observations and experimental data but also
new theoretical insights. Theoretical understanding comes increasingly from large-scale
computations that allow us to confront the consequences of our theories very accurately
with the data or allow us to interrogate the data in detail to extract information that has
impact on our theories. These computations test the fastest computers that we have and
push the boundaries of technology in this sector. They also provide an excellent
environment for training students in state-of-the-art techniques for code optimisation and
data mining and visualisation.
The DiRAC-2.5 project builds on the success of the DiRAC HPC facility and will provide the resources needed
to support cutting edge research during 2017 in all areas of science supported by STFC.
In particular, DiRAC-2.5 will provide:
1) A factor 2 increase in the computational power of the DiRAC supercomputer at the University of Durham, which is designed for simulations requiring large amounts of computer memory. The enhanced system will be used to:
(i) simulate the merger of pairs of black holes which generate gravitational waves such as those recently discovered by the LIGO consortium;
(ii) perform the most realistic simulations to date of the formation and evolution of galaxies in the Universe
(iii) carry out detailed simulations of the interior of the sun and of planetary interiors.
2) A new High Performance Computer whose particular architecture is well suited to the theoretical
problems that we want to tackle that utilise large amounts of data, either as input or
being generated at intermediate stages of our calculations. Two key challenges
that we will tackle are those of
(i) improving our understanding of the Milky Way through analysis of new data from the European
Space Agency's GAIA satellite and
(ii) improving the potential of experiments at CERN's Large Hadron Collider for discovery
of new physics by increasing the accuracy of theoretical predictions for rare processes involving the
fundamental constituents of matter known as quarks.
on understanding how the Universe works at a very fundamental level. The distance scales
with which they work vary by 50 orders of magnitude from the smallest distances probed
by experiments at the Large Hadron Collider, deep within the atomic
nucleus, to the largest scale galaxy clusters discovered out in space. The Science challenges,
however, are linked through questions such as: How did the Universe begin and how is it evolving?
and What are the fundamental constituents and fabric of the Universe and how do they interact?
Progress requires new astronomical observations and experimental data but also
new theoretical insights. Theoretical understanding comes increasingly from large-scale
computations that allow us to confront the consequences of our theories very accurately
with the data or allow us to interrogate the data in detail to extract information that has
impact on our theories. These computations test the fastest computers that we have and
push the boundaries of technology in this sector. They also provide an excellent
environment for training students in state-of-the-art techniques for code optimisation and
data mining and visualisation.
The DiRAC-2.5 project builds on the success of the DiRAC HPC facility and will provide the resources needed
to support cutting edge research during 2017 in all areas of science supported by STFC.
In particular, DiRAC-2.5 will provide:
1) A factor 2 increase in the computational power of the DiRAC supercomputer at the University of Durham, which is designed for simulations requiring large amounts of computer memory. The enhanced system will be used to:
(i) simulate the merger of pairs of black holes which generate gravitational waves such as those recently discovered by the LIGO consortium;
(ii) perform the most realistic simulations to date of the formation and evolution of galaxies in the Universe
(iii) carry out detailed simulations of the interior of the sun and of planetary interiors.
2) A new High Performance Computer whose particular architecture is well suited to the theoretical
problems that we want to tackle that utilise large amounts of data, either as input or
being generated at intermediate stages of our calculations. Two key challenges
that we will tackle are those of
(i) improving our understanding of the Milky Way through analysis of new data from the European
Space Agency's GAIA satellite and
(ii) improving the potential of experiments at CERN's Large Hadron Collider for discovery
of new physics by increasing the accuracy of theoretical predictions for rare processes involving the
fundamental constituents of matter known as quarks.
Planned Impact
The expected impact of DiRAC-2.5 is fully described in the pathways to impact section of the case for support and includes:
1) Disseminating best practice in High Performance Computing software engineering throughout the theoretical Particle Physics, Astronomy and Nuclear physics communities in the UK as well as to industry partners.
2) Working on co-design projects with industry partners to improve future generations of hardware and software.
3) Development of new techniques in the area of High Performance Data Analytics which will benefit industry partners and researchers in other fields such as biomedicine, biology, engineering, economics and social science, and the natural environment who can use this new technology to improve research outcomes in their areas.
4) Share best practice on the design and operation of distributed HPC facilities with UK National e-Infrastructure partners.
5) Training of the next generation of research scientists of physical scientists to tackle problems effectively on state-of-the-art of High Performance Computing facilities. Such skills are much in demand from high-tech industry.
6) Engagement with the general public to promote interest in science, and to explain how our ability to solve complex problems using the latest computer technology leads to new scientific capabilities/insights. Engagement of this kind also naturally encourages the uptake of STEM subjects in schools.
1) Disseminating best practice in High Performance Computing software engineering throughout the theoretical Particle Physics, Astronomy and Nuclear physics communities in the UK as well as to industry partners.
2) Working on co-design projects with industry partners to improve future generations of hardware and software.
3) Development of new techniques in the area of High Performance Data Analytics which will benefit industry partners and researchers in other fields such as biomedicine, biology, engineering, economics and social science, and the natural environment who can use this new technology to improve research outcomes in their areas.
4) Share best practice on the design and operation of distributed HPC facilities with UK National e-Infrastructure partners.
5) Training of the next generation of research scientists of physical scientists to tackle problems effectively on state-of-the-art of High Performance Computing facilities. Such skills are much in demand from high-tech industry.
6) Engagement with the general public to promote interest in science, and to explain how our ability to solve complex problems using the latest computer technology leads to new scientific capabilities/insights. Engagement of this kind also naturally encourages the uptake of STEM subjects in schools.
Publications
Cooper L
(2022)
Form factors for the processes B c + ? D 0 l + ? l and B c + ? D s + l + l - ( ? ? ¯ ) from lattice QCD
in Physical Review D
Al-Refaie A
(2022)
FRECKLL: Full and Reduced Exoplanet Chemical Kinetics distiLLed
Goyal J
(2019)
Fully scalable forward model grid of exoplanet transmission spectra
in Monthly Notices of the Royal Astronomical Society
Fiacconi D
(2018)
Galactic nuclei evolution with spinning black holes: method and implementation
in Monthly Notices of the Royal Astronomical Society
Fiacconi Davide
(2017)
Galaxy formation simulations with spinning black holes: method and implementation
in ArXiv e-prints
Dipierro G
(2018)
Gas and multispecies dust dynamics in viscous protoplanetary discs: the importance of the dust back-reaction
in Monthly Notices of the Royal Astronomical Society
Meiksin A
(2017)
Gas around galaxy haloes - III: hydrogen absorption signatures around galaxies and QSOs in the Sherwood simulation suite
in Monthly Notices of the Royal Astronomical Society
Clough K
(2022)
Ghost Instabilities in Self-Interacting Vector Fields: The Problem with Proca Fields.
in Physical review letters
Huang J
(2023)
Global 3D Radiation Magnetohydrodynamic Simulations of Accretion onto a Stellar-mass Black Hole at Sub- and Near-critical Accretion Rates
in The Astrophysical Journal
Chang C
(2023)
Global fits of simplified models for dark matter with GAMBIT
Chang C
(2023)
Global fits of simplified models for dark matter with GAMBIT I. Scalar and fermionic models with s-channel vector mediators
in The European Physical Journal C
Chang C
(2023)
Global fits of simplified models for dark matter with GAMBIT II. Vector dark matter with an s-channel vector mediator
in The European Physical Journal C
Bennett E
(2021)
Glueballs and strings in S p ( 2 N ) Yang-Mills theories
in Physical Review D
Figueras P
(2020)
Gravitational collapse in cubic Horndeski theories
in Classical and Quantum Gravity
Figueras P
(2020)
Gravitational Collapse in Cubic Horndeski Theories
Khan S
(2021)
Gravitational-wave surrogate models powered by artificial neural networks
in Physical Review D
Bamber J
(2021)
Growth of accretion driven scalar hair around Kerr black holes
in Physical Review D
Bamber J
(2020)
Growth of accretion driven scalar hair around Kerr black holes
Clough K
(2019)
Growth of massive scalar hair around a Schwarzschild black hole
in Physical Review D
Wurster J
(2018)
Hall effect-driven formation of gravitationally unstable discs in magnetized molecular cloud cores
in Monthly Notices of the Royal Astronomical Society
Jennings F
(2023)
Halo scaling relations and hydrostatic mass bias in the simba simulation from realistic mock X-ray catalogues
in Monthly Notices of the Royal Astronomical Society
Collins C
(2023)
Helium as a signature of the double detonation in Type Ia supernovae
in Monthly Notices of the Royal Astronomical Society
Collins C
(2023)
Helium as a signature of the double detonation in Type Ia supernovae
Sperhake U
(2019)
High-energy collision of black holes in higher dimensions
in Physical Review D
Martin G
(2018)
Identifying the progenitors of present-day early-type galaxies in observational surveys: correcting 'progenitor bias' using the Horizon-AGN simulation
in Monthly Notices of the Royal Astronomical Society
Hu Shaoran
(2017)
Impact of Cosmological Satellites on Stellar Discs: Dissecting One Satellite at a Time
in ArXiv e-prints
Hu S
(2018)
Impact of cosmological satellites on stellar discs: dissecting one satelliteat a time
in Monthly Notices of the Royal Astronomical Society
Kimm T
(2018)
Impact of Lyman alpha pressure on metal-poor dwarf galaxies
in Monthly Notices of the Royal Astronomical Society
Rocco N
(2018)
Inclusive electron-nucleus cross section within the self-consistent Green's function approach
in Physical Review C
De Belsunce R
(2021)
Inference of the optical depth to reionization from low multipole temperature and polarization Planck data
in Monthly Notices of the Royal Astronomical Society
Katz Harley
(2016)
Interpreting ALMA Observations of the ISM During the Epoch of Reionisation
in ArXiv e-prints
Rosca-Mead R
(2019)
Inverse-chirp signals and spontaneous scalarisation with self-interacting potentials in stellar collapse
in Classical and Quantum Gravity
Linh B
(2021)
Investigation of the ground-state spin inversion in the neutron-rich Cl 47 , 49 isotopes
in Physical Review C
Scardoni C
(2022)
Inward and outward migration of massive planets: moving towards a stalling radius
in Monthly Notices of the Royal Astronomical Society
Hellinger P
(2022)
Ion-scale Transition of Plasma Turbulence: Pressure-Strain Effect
in The Astrophysical Journal
Hellinger P
(2022)
Ion-scale transition of plasma turbulence: Pressure-strain effect
Hellinger P
(2022)
Ion-scale transition of plasma turbulence: Pressure-strain effect
Description | Many new discoveries about the formation and evolution of galaxies, star formation, planet formation have been made possible by the award. |
Exploitation Route | Many international collaborative projects are supported by the HPC resources provided by DiRAC. |
Sectors | Digital/Communication/Information Technologies (including Software),Education |
URL | http://www.dirac.ac.uk |
Description | Major co-design project with Hewlett Packard Enterprise, including partnership in the HPE/Arm/Suse Catalyst UK programme. |
First Year Of Impact | 2017 |
Sector | Digital/Communication/Information Technologies (including Software) |
Impact Types | Societal |
Description | DiRAC 2.5x Project Office 2017-2020 |
Amount | £300,000 (GBP) |
Organisation | Science and Technologies Facilities Council (STFC) |
Sector | Public |
Country | United Kingdom |
Start | 02/2018 |
End | 03/2020 |
Title | Citation analysys and Impact |
Description | Use of IT to determineacademic impact of eInfrastructure |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | Understood emerging trends in DiRAC Science and helped decide the scale and type of IT investments and direct us to develop new technologies |
URL | http://www.dirac.ac.uk |
Description | Co-design project with Hewlett Packard Enterprise |
Organisation | Hewlett Packard Enterprise (HPE) |
Country | United Kingdom |
Sector | Private |
PI Contribution | Technical support and operations costs for running the hardware. Research workflows to test the system performance, and investment of academic time and software engineering time to optimise code for new hardware. Project will explore suitability of hardware for DiRAC workflows and provide feedback to HPE. |
Collaborator Contribution | In-kind provision of research computing hardware. Value is commercially confidential. |
Impact | As this collaboration is about to commence, there are no outcomes to report at this point. |
Start Year | 2018 |
Description | Nuclei from Lattice QCD |
Organisation | RIKEN |
Department | RIKEN-Nishina Center for Accelerator-Based Science |
Country | Japan |
Sector | Public |
PI Contribution | Surrey performed ab initio studies of LQCD-derived nuclear forces |
Collaborator Contribution | Work by Prof. Hatsuda and collaborators at the iTHEMS and Quantum Hadron Physics Laboratory to provide nuclear forces derived from LQCD |
Impact | Phys. Rev. C 97, 021303(R) |
Start Year | 2015 |
Description | STFC Centres for Doctoral Training in Data Intensive Science |
Organisation | University of Leicester |
Department | STFC DiRAC Complexity Cluster (HPC Facility Leicester) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Support for STFC Centres for Doctoral Training (CDT) in Data Intensive Science - DiRAC is a partner in five of the eight of the newly established STFC CDTs, and is actively engaged with them in developing industrial partnerships. DiRAC is also offering placements to CDT students interested in Research Software Engineering roles. |
Collaborator Contribution | Students to work on interesting technical problems for DiRAC |
Impact | This is the first year |
Start Year | 2017 |
Description | Surrey-Saclay |
Organisation | Saclay Nuclear Research Centre |
Country | France |
Sector | Public |
PI Contribution | Provided codes and know-how to develop GF Gorkov formalism and implementation. |
Collaborator Contribution | Help spreading and advertise my research |
Impact | Presentation of preliminary results at conference. Grant still ongoing. Results being written up. Output will be first ab-initio calculation of fully open shells. |
Start Year | 2010 |