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
Offler S
(2019)
News from bottomonium spectral functions in thermal QCD
Norman S
(2021)
Stars Crushed by Black Holes. I. On the Energy Distribution of Stellar Debris in Tidal Disruption Events
in The Astrophysical Journal
Nobels F
(2022)
The interplay between AGN feedback and precipitation of the intracluster medium in simulations of galaxy groups and clusters
in Monthly Notices of the Royal Astronomical Society
Nixon C
(2021)
Partial, Zombie, and Full Tidal Disruption of Stars by Supermassive Black Holes
in The Astrophysical Journal
Nixon C
(2021)
Accretion discs with non-zero central torque
in New Astronomy
Nixon C
(2019)
What is wrong with steady accretion discs?
in Astronomy & Astrophysics
Nixon C
(2022)
Stellar Revival and Repeated Flares in Deeply Plunging Tidal Disruption Events
in The Astrophysical Journal Letters
Nixon C
(2022)
Stellar Revival and Repeated Flares in Deeply Plunging Tidal Disruption Events
in The Astrophysical Journal Letters
Nishimura (????) N
(2019)
Uncertainties in ?p-process nucleosynthesis from Monte Carlo variation of reaction rates
in Monthly Notices of the Royal Astronomical Society
Nikolaev A.
(2019)
Mesonic correlators at non-zero baryon chemical potential
in Proceedings of Science
Nikolaev A
(2020)
Mesonic correlators at non-zero baryon chemical potential
Nightingale J
(2021)
PyAutoFit: A Classy Probabilistic Programming Language for Model Composition and Fitting
in Journal of Open Source Software
Nightingale J
(2019)
Galaxy structure with strong gravitational lensing: decomposing the internal mass distribution of massive elliptical galaxies
in Monthly Notices of the Royal Astronomical Society
Nightingale J
(2023)
Abell 1201: detection of an ultramassive black hole in a strong gravitational lens
in Monthly Notices of the Royal Astronomical Society
Nightingale J
(2021)
PyAutoLens: Open-Source Strong Gravitational Lensing
in Journal of Open Source Software
Nelson R
(2023)
Gas accretion onto Jupiter mass planets in discs with laminar accretion flows
in Astronomy & Astrophysics
Nelson R
(2023)
Gas accretion onto Jupiter mass planets in discs with laminar accretion flows
in Astronomy & Astrophysics
Negri A
(2022)
The luminosity of cluster galaxies in the Cluster-EAGLE simulations
in Monthly Notices of the Royal Astronomical Society
Nealon R
(2019)
Flyby-induced misalignments in planet-hosting discs
in Monthly Notices of the Royal Astronomical Society
Nealon R
(2020)
Spirals, shadows & precession in HD 100453 - II. The hidden companion
in Monthly Notices of the Royal Astronomical Society
Nazari Z
(2021)
Oscillon collapse to black holes
in Journal of Cosmology and Astroparticle Physics
Navarro J
(2020)
The edge of the Galaxy
in Monthly Notices of the Royal Astronomical Society
Navarro J
(2019)
Baryon-induced dark matter cores in the eagle simulations
in Monthly Notices of the Royal Astronomical Society
Naik A
(2019)
Constraints on chameleon f(R)-gravity from galaxy rotation curves of the SPARC sample
in Monthly Notices of the Royal Astronomical Society
Murtas G
(2022)
Collisional ionization and recombination effects on coalescence instability in chromospheric partially ionized plasmas
in Physics of Plasmas
Murtas G
(2022)
Collisional ionization and recombination effects on coalescence instability in chromospheric partially ionized plasmas
in Physics of Plasmas
Mukherjee S
(2021)
SEAGLE - II. Constraints on feedback models in galaxy formation from massive early-type strong-lens galaxies
in Monthly Notices of the Royal Astronomical Society
Muia F
(2019)
The fate of dense scalar stars
in Journal of Cosmology and Astroparticle Physics
Mosbech M
(2023)
Gravitational-wave event rates as a new probe for dark matter microphysics
in Physical Review D
Morello G
(2023)
Spitzer thermal phase curve of WASP-121 b
in Astronomy & Astrophysics
Montargès M
(2023)
The VLT/SPHERE view of the ATOMIUM cool evolved star sample I. Overview: Sample characterization through polarization analysis
in Astronomy & Astrophysics
Monaco P
(2020)
The accuracy of weak lensing simulations
in Monthly Notices of the Royal Astronomical Society
Monachesi A
(2019)
The Auriga stellar haloes: connecting stellar population properties with accretion and merging history
in Monthly Notices of the Royal Astronomical Society
Moliné Á
(2019)
Properties of Subhalos in the Interacting Dark Matter Scenario
in Galaxies
Molaro M
(2022)
The effect of inhomogeneous reionization on the Lyman a forest power spectrum at redshift z > 4: implications for thermal parameter recovery
in Monthly Notices of the Royal Astronomical Society
Molaro M
(2023)
Possible evidence for a large-scale enhancement in the Lyman-a forest power spectrum at redshift z = 4
in Monthly Notices of the Royal Astronomical Society
Mocz P
(2023)
Cosmological structure formation and soliton phase transition in fuzzy dark matter with axion self-interactions
in Monthly Notices of the Royal Astronomical Society
Mitchell P
(2022)
How gas flows shape the stellar-halo mass relation in the eagle simulation
in Monthly Notices of the Royal Astronomical Society
Mitchell P
(2020)
Galactic inflow and wind recycling rates in the eagle simulations
in Monthly Notices of the Royal Astronomical Society
Mitchell P
(2020)
Galactic outflow rates in the EAGLE simulations
in Monthly Notices of the Royal Astronomical Society
Mitchell P
(2022)
Baryonic mass budgets for haloes in the eagle simulation, including ejected and prevented gas
in Monthly Notices of the Royal Astronomical Society
Mitchell P
(2022)
Baryonic mass budgets for haloes in the eagle simulation, including ejected and prevented gas
in Monthly Notices of the Royal Astronomical Society
Mitchell M
(2022)
A general framework to test gravity using galaxy clusters - VI. Realistic galaxy formation simulations to study clusters in modified gravity
in Monthly Notices of the Royal Astronomical Society
Mitchell M
(2021)
A general framework to test gravity using galaxy clusters IV: cluster and halo properties in DGP gravity
in Monthly Notices of the Royal Astronomical Society
Mitchell M
(2021)
A general framework to test gravity using galaxy clusters III: observable-mass scaling relations in f ( R ) gravity
in Monthly Notices of the Royal Astronomical Society
Mitchell M
(2021)
A general framework to test gravity using galaxy clusters - V. A self-consistent pipeline for unbiased constraints of f ( R ) gravity
in Monthly Notices of the Royal Astronomical Society
Miles P
(2020)
Fallback Rates from Partial Tidal Disruption Events
in The Astrophysical Journal
Mercer A
(2020)
Planet formation around M dwarfs via disc instability Fragmentation conditions and protoplanet properties
in Astronomy & Astrophysics
Mellor T
(2023)
MARVEL analysis of high-resolution spectra of thioformaldehyde (H 2 CS)
in Journal of Molecular Spectroscopy
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. |