DiRAC-3 Operations 2019-2022 - Edinburgh
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Physics and Astronomy
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Planned Impact
The DiRAC-3 Facility strategy for impact and innovation delivery is well-aligned with the UK government Industrial Strategy. As such, much of our societal and economic impact will continue to be driven by our engagements with industry. Each DiRAC-3 service provider has a local industrial strategy to deliver continued high levels of industrial engagement and to explore avenues to increase innovation and industrial returns over the next three years. Progress towards the industrial strategy goals will be monitored by the Service Management Boards and the DiRAC Technical Manager and reported to STFC via the DiRAC Oversight Committee.
The "Pathways to Impact" document attached to the lead JeS form for this proposal describes the overall DiRAC-3 industrial strategy, including our strategic goals and key performance indicators.
Examples of the expected impact of DiRAC-3 include:
Dissemination of 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.
Training of the next generation of research 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 and the cadre of highly-skilled, computationally literate individuals nurtured by DiRAC-3 will have influence beyond academia and will help to maintain the UK's scientific and economic leadership.
Development and delivery of co-design projects with industry partners to improve future generations of hardware and software.
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 these developments to improve research outcomes in their areas.
Sharing of best practice on the design and operation of distributed HPC facilities with UK National e-Infrastructure partners and providing leadership towards an integrated UKRI National e-Infrastructure. By supporting the uptake of emerging technologies by the DiRAC research communities, we will enable other research communities, both in academia and industry, to explore the value of using leading-edge technology to support their research workflows.
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.
The "Pathways to Impact" document attached to the lead JeS form for this proposal describes the overall DiRAC-3 industrial strategy, including our strategic goals and key performance indicators.
Examples of the expected impact of DiRAC-3 include:
Dissemination of 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.
Training of the next generation of research 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 and the cadre of highly-skilled, computationally literate individuals nurtured by DiRAC-3 will have influence beyond academia and will help to maintain the UK's scientific and economic leadership.
Development and delivery of co-design projects with industry partners to improve future generations of hardware and software.
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 these developments to improve research outcomes in their areas.
Sharing of best practice on the design and operation of distributed HPC facilities with UK National e-Infrastructure partners and providing leadership towards an integrated UKRI National e-Infrastructure. By supporting the uptake of emerging technologies by the DiRAC research communities, we will enable other research communities, both in academia and industry, to explore the value of using leading-edge technology to support their research workflows.
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.
Organisations
Publications
Tsang Y
(2024)
Scaling of the geomagnetic secular variation timescale
in Geophysical Journal International
Davison T
(2022)
Complex Crater Formation by Oblique Impacts on the Earth and Moon
in Geophysical Research Letters
Read P
(2020)
The turbulent dynamics of Jupiter's and Saturn's weather layers: order out of chaos?
in Geoscience Letters
Sergeev D
(2023)
Simulations of idealised 3D atmospheric flows on terrestrial planets using LFRic-Atmosphere
in Geoscientific Model Development
Halim S
(2021)
Assessing the survivability of biomarkers within terrestrial material impacting the lunar surface
in Icarus
Raducan S
(2022)
Ejecta distribution and momentum transfer from oblique impacts on asteroid surfaces
in Icarus
Young R
(2019)
Simulating Jupiter's weather layer. Part II: Passive ammonia and water cycles
in Icarus
Bartlett D
(2024)
Exhaustive Symbolic Regression
in IEEE Transactions on Evolutionary Computation
Hardy F
(2023)
Estimating nosocomial infection and its outcomes in hospital patients in England with a diagnosis of COVID-19 using machine learning
in International Journal of Data Science and Analytics
Heyl J
(2023)
Data quality and autism: Issues and potential impacts.
in International journal of medical informatics
Worthy J
(2024)
Evaluation of the bilinear condensate of the planar Thirring model in the strongly coupled region
in International Journal of Modern Physics C
Stevenson P
(2020)
Internuclear potentials from the Sky3D code
in IOP SciNotes
Brady R
(2024)
Numerical Equivalence of Diabatic and Adiabatic Representations in Diatomic Molecules
in Journal of Chemical Theory and Computation
Pedersen C
(2020)
Massive neutrinos and degeneracies in Lyman-alpha forest simulations
in Journal of Cosmology and Astroparticle Physics
Widdicombe J
(2020)
Black hole formation in relativistic Oscillaton collisions
in Journal of Cosmology and Astroparticle Physics
Leo M
(2020)
Constraining structure formation using EDGES
in Journal of Cosmology and Astroparticle Physics
Elley M
(2025)
Robustness of inflation to kinetic inhomogeneities
in Journal of Cosmology and Astroparticle Physics
Aviles A
(2020)
Marked correlation functions in perturbation theory
in Journal of Cosmology and Astroparticle Physics
Srinivasan S
(2021)
Cosmological gravity on all scales. Part II. Model independent modified gravity N-body simulations
in Journal of Cosmology and Astroparticle Physics
Nazari Z
(2021)
Oscillon collapse to black holes
in Journal of Cosmology and Astroparticle Physics
Barrera-Hinojosa C
(2020)
GRAMSES: a new route to general relativistic N -body simulations in cosmology. Part II. Initial conditions
in Journal of Cosmology and Astroparticle Physics
Givans J
(2022)
Non-linearities in the Lyman-a forest and in its cross-correlation with dark matter halos
in Journal of Cosmology and Astroparticle Physics
De Jong E
(2023)
Spinning primordial black holes formed during a matter-dominated era
in Journal of Cosmology and Astroparticle Physics
Arvizu A
(2024)
Modeling the 3-point correlation function of projected scalar fields on the sphere
in Journal of Cosmology and Astroparticle Physics
Pedersen C
(2021)
An emulator for the Lyman-a forest in beyond-?CDM cosmologies
in Journal of Cosmology and Astroparticle Physics
| Title | Supplemental data for the report "Optimisation of lattice simulations energy efficiency" |
| Description | Supplemental data for the report "Optimisation of lattice simulations energy efficiency". Also available as a git repository. It contains: Full copy of benchmark run directories Power monitoring scripts Power monitoring raw measurements Power monitoring data analysis and results used in the report For a more complete description, please see the README.md file. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| URL | https://zenodo.org/record/7057644 |
| Title | Supplemental data for the report "Optimisation of lattice simulations energy efficiency" |
| Description | Supplemental data for the report "Optimisation of lattice simulations energy efficiency". Also available as a git repository. It contains: Full copy of benchmark run directories Power monitoring scripts Power monitoring raw measurements Power monitoring data analysis and results used in the report For a more complete description, please see the README.md file. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| URL | https://zenodo.org/record/7057645 |
