Dirac 2.5 Operations
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of 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.
DiRAC-2.5 will provide maintain the existing DiRAC-2 services from April 2017, and also provide and increase in computational
resources at Durham, Cambridge and Leicester.
This grant will support the operation of the Edinburgh DiRAC services, which presently comprise
98384 operational computing cores serving around 80% of DiRAC computing cycles. The system is made up
from both the original 1.26PFlop/s DiRAC BlueGene/Q system and, following a recent transfer
to Edinburgh by STFC, six racks of the Hartree BlueJoule supercomputer.
The DiRAC project also will offer a team of three research software engineers who will help DiRAC researchers to ensure their scientific codes to extract
the best possible performance from the hardware components of the DiRAC clusters. These highly skilled programmers will
increase the effective computational power of the DiRAC facility during 2017.
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.
DiRAC-2.5 will provide maintain the existing DiRAC-2 services from April 2017, and also provide and increase in computational
resources at Durham, Cambridge and Leicester.
This grant will support the operation of the Edinburgh DiRAC services, which presently comprise
98384 operational computing cores serving around 80% of DiRAC computing cycles. The system is made up
from both the original 1.26PFlop/s DiRAC BlueGene/Q system and, following a recent transfer
to Edinburgh by STFC, six racks of the Hartree BlueJoule supercomputer.
The DiRAC project also will offer a team of three research software engineers who will help DiRAC researchers to ensure their scientific codes to extract
the best possible performance from the hardware components of the DiRAC clusters. These highly skilled programmers will
increase the effective computational power of the DiRAC facility during 2017.
Planned Impact
The expected impact of the DiRAC 2.5 HPC facility is fully described in the attached pathways to impact document 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
Coughlin E
(2020)
Variability in Short Gamma-Ray Bursts: Gravitationally Unstable Tidal Tails
in The Astrophysical Journal
Coulton W
(2020)
Weak lensing minima and peaks: Cosmological constraints and the impact of baryons
in Monthly Notices of the Royal Astronomical Society
Creci G
(2020)
Evolution of black hole shadows from superradiance
in Physical Review D
Croft R
(2023)
The gravitational afterglow of boson stars
in Classical and Quantum Gravity
Croft R
(2023)
The gravitational afterglow of boson stars
in Classical and Quantum Gravity
Cuesta-Lazaro C
(2020)
Towards a non-Gaussian model of redshift space distortions
in Monthly Notices of the Royal Astronomical Society
Cuesta-Lazaro C
(2023)
Galaxy clustering from the bottom up: a streaming model emulator I
in Monthly Notices of the Royal Astronomical Society
Cufari M
(2023)
Tidal capture of stars by supermassive black holes: implications for periodic nuclear transients and quasi-periodic eruptions
in Monthly Notices of the Royal Astronomical Society: Letters
Cui W
(2021)
The origin of galaxy colour bimodality in the scatter of the stellar-to-halo mass relation
in Nature Astronomy
Cummins D
(2022)
Extreme pebble accretion in ringed protoplanetary discs
in Monthly Notices of the Royal Astronomical Society
Cummins D
(2022)
Extreme pebble accretion in ringed protoplanetary discs
in Monthly Notices of the Royal Astronomical Society
Cuomo V
(2023)
Testing for relics of past strong buckling events in edge-on galaxies: simulation predictions and data from S4G
in Monthly Notices of the Royal Astronomical Society
Cuomo V
(2023)
Testing for relics of past strong buckling events in edge-on galaxies: simulation predictions and data from S4G
in Monthly Notices of the Royal Astronomical Society
Currie L
(2020)
Generation of shear flows and vortices in rotating anelastic convection
in Physical Review Fluids
Currie L
(2020)
Convection with misaligned gravity and rotation: simulations and rotating mixing length theory
in Monthly Notices of the Royal Astronomical Society
Curtis-Lake E
(2023)
The epoch of galaxy quenching
in Nature Astronomy
Czakon M
(2021)
Next-to-Next-to-Leading Order Study of Three-Jet Production at the LHC.
in Physical review letters
Czakon M
(2021)
NNLO QCD corrections to leptonic observables in top-quark pair production and decay
in Journal of High Energy Physics
Czakon M
(2021)
NNLO QCD predictions for W+c-jet production at the LHC
in Journal of High Energy Physics
Czakon M
(2023)
NNLO B-fragmentation fits and their application to $$ t\overline{t} $$ production and decay at the LHC
in Journal of High Energy Physics
Czakon M
(2023)
A detailed investigation of W+c-jet at the LHC
in Journal of High Energy Physics
Czakon M
(2023)
Infrared-safe flavoured anti-kT jets
in Journal of High Energy Physics
Czakon M
(2021)
B-hadron production in NNLO QCD: application to LHC t$$ \overline{t} $$ events with leptonic decays
in Journal of High Energy Physics
Daisy Leung T
(2020)
Predictions of the L [C ii] -SFR and [Cii] Luminosity Function at the Epoch of Reionization
in The Astrophysical Journal
Daley-Yates S
(2023)
Heating and cooling in stellar coronae: coronal rain on a young Sun
in Monthly Notices of the Royal Astronomical Society
Dalla Vecchia C
(2020)
Constraining the inner density slope of massive galaxy clusters
in Monthly Notices of the Royal Astronomical Society
Daly R
(2023)
Successful kinetic impact into an asteroid for planetary defence
in Nature
Davies C
(2022)
Cosmological forecasts with the clustering of weak lensing peaks
in Monthly Notices of the Royal Astronomical Society
Davies C
(2021)
Optimal void finders in weak lensing maps
in Monthly Notices of the Royal Astronomical Society
Davies C
(2021)
Constraining cosmology with weak lensing voids
in Monthly Notices of the Royal Astronomical Society
Davies C
(2022)
Windows on the hadronic vacuum polarization contribution to the muon anomalous magnetic moment
in Physical Review D
Davies C
(2019)
Determination of the quark condensate from heavy-light current-current correlators in full lattice QCD
in Physical Review D
Davies C
(2019)
Meson electromagnetic form factors from lattice QCD
Davies C
(2019)
Improving the kinetic couplings in lattice nonrelativistic QCD
in Physical Review D
Davies C
(2022)
Windows on the hadronic vacuum polarization contribution to the muon anomalous magnetic moment
in Physical Review D
Davies C
(2022)
Cosmological forecasts with the clustering of weak lensing peaks
in Monthly Notices of the Royal Astronomical Society
Davies C.T.H.
(2018)
Meson electromagnetic form factors from lattice QCD
in Proceedings of Science
Davies CTH
(2020)
Lattice QCD Matrix Elements for the B_{s}^{0}-B[over ¯]_{s}^{0} Width Difference beyond Leading Order.
in Physical review letters
Davies J
(2020)
The quenching and morphological evolution of central galaxies is facilitated by the feedback-driven expulsion of circumgalactic gas
in Monthly Notices of the Royal Astronomical Society
Davison T
(2022)
Complex Crater Formation by Oblique Impacts on the Earth and Moon
in Geophysical Research Letters
Davison T
(2022)
Complex Crater Formation by Oblique Impacts on the Earth and Moon
in Geophysical Research Letters
Davoudi Z
(2019)
Theoretical aspects of quantum electrodynamics in a finite volume with periodic boundary conditions
in Physical Review D
Davé R
(2020)
Galaxy cold gas contents in modern cosmological hydrodynamic simulations
in Monthly Notices of the Royal Astronomical Society
De Jong E
(2022)
Primordial black hole formation with full numerical relativity
in Journal of Cosmology and Astroparticle Physics
De Jong E
(2022)
Primordial black hole formation with full numerical relativity
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
De Vries N
(2023)
The interactions of the elliptical instability and convection
in Physics of Fluids
De Vries N
(2023)
The interactions of the elliptical instability and convection
in Physics of Fluids
Description | DiRAC 2.5 is a facility to support leading-edge computational astronomy and particle physics in the UK. This has resulted in over 500 peer-reviewed publications. |
Exploitation Route | Build on the scientific knowledge and computational techniques developed. |
Sectors | Digital/Communication/Information Technologies (including Software),Education |
Description | Intel IPAG QCD codesign project |
Organisation | Intel Corporation |
Department | Intel Corporation (Jones Farm) |
Country | United States |
Sector | Private |
PI Contribution | We have collaborated with Intel corporation since 2014 with $720k of total direct funding, starting initially as an Intel parallel computing centre, and expanding to direct close collaboration with Intel Pathfinding and Architecture Group. |
Collaborator Contribution | We have performed detailed optimisation of QCD codes (Wilson, Domain Wall, Staggered) on Intel many core architectures. We have investigated the memory system and interconnect performance, particularly on Intel's latest interconnect hardware called Omnipath. We found serious performance issues and worked with Intel to plan a solution and this has been verified and is available as beta software. It will reach general availability in the Intel MPI 2019 release, and allow threaded concurrent communications in MPI for the first time. A joint paper on the resolution to this was written with the Intel MPI team, and the application of the same QCD programming techniques to machine learning gradient reduction was applied in the paper to the Baidu Research all reduce library, demonstrating a 10x gain for this critical step in machine learning in clustered environments. We are also working with Intel verifying future architectures that will deliver the exascale performance in 2021. |
Impact | We have performed detailed optimisation of QCD codes (Wilson, Domain Wall, Staggered) on Intel many core architectures. We have investigated the memory system and interconnect performance, particularly on Intel's latest interconnect hardware called Omnipath. We found serious performance issues and worked with Intel to plan a solution and this has been verified and is available as beta software. It will reach general availability in the Intel MPI 2019 release, and allow threaded concurrent communications in MPI for the first time. A joint paper on the resolution to this was written with the Intel MPI team, and the application of the same QCD programming techniques to machine learning gradient reduction was applied in the paper to the Baidu Research all reduce library, demonstrating a 10x gain for this critical step in machine learning in clustered environments. This collaboration has been renewed annually in 2018, 2019, 2020. Two DiRAC RSE's were hired by Intel to work on the Turing collaboration. |
Start Year | 2016 |
Title | FP16-S7E8 MIXED PRECISION FOR DEEP LEARNING AND OTHER ALGORITHMS |
Description | We demonstrated that a new non-IEEE 16 bit floating point format is the optimal choice for machine learning training and proposed instructions. |
IP Reference | US20190042544 |
Protection | Patent application published |
Year Protection Granted | 2019 |
Licensed | Yes |
Impact | We demonstrated that a new non-IEEE 16 bit floating point format is the optimal choice for machine learning training and proposed instructions. Intel filed this with US patent office. This IP is owned by Intel under the terms of the Intel Turing strategic partnership contract. As a co-inventor I have been named on the patent application. The proposed format has been announced as planned for use in future Intel architectures. This collaboration with Turing emerged out of an investment in Edinburgh by Intel Pathfinding and Architecture Group in codesign with lattice gauge theory simulations. Intel hired DiRAC RSE's Kashyap and Lepper and placed them in Edinburgh to work with me on Machine Learning codesign through the Turing programme. |