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
Baugh C
(2019)
Galaxy formation in the Planck Millennium: the atomic hydrogen content of dark matter haloes
in Monthly Notices of the Royal Astronomical Society
Haynes C
(2019)
Galactic simulations of r-process elemental abundances
in Monthly Notices of the Royal Astronomical Society
Vincenzo F
(2019)
He abundances in disc galaxies I. Predictions from cosmological chemodynamical simulations
in Astronomy & Astrophysics
Stevenson P
(2019)
Low-energy heavy-ion reactions and the Skyrme effective interaction
in Progress in Particle and Nuclear Physics
Debras F
(2019)
Eigenvectors, Circulation, and Linear Instabilities for Planetary Science in 3 Dimensions (ECLIPS3D)
in Astronomy & Astrophysics
Arnett W
(2019)
3D Simulations and MLT. I. Renzini's Critique
in The Astrophysical Journal
Mahler G
(2019)
RELICS: Strong Lensing Analysis of MACS J0417.5-1154 and Predictions for Observing the Magnified High-redshift Universe with JWST
in The Astrophysical Journal
Rhodin N
(2019)
The nature of strong H i absorbers probed by cosmological simulations: satellite accretion and outflows
in Monthly Notices of the Royal Astronomical Society
Amarantidis S
(2019)
The first supermassive black holes: indications from models for future observations
in Monthly Notices of the Royal Astronomical Society
Hori K
(2019)
Anelastic torsional oscillations in Jupiter's metallic hydrogen region
in Earth and Planetary Science Letters
Offler S.
(2019)
News from bottomonium spectral functions in thermal QCD
in Proceedings of Science
Nixon C
(2019)
What is wrong with steady accretion discs?
in Astronomy & Astrophysics
Pittard J
(2019)
Momentum and energy injection by a supernova remnant into an inhomogeneous medium
in Monthly Notices of the Royal Astronomical Society
Green S
(2019)
Thermal emission from bow shocks I. 2D hydrodynamic models of the Bubble Nebula
in Astronomy & Astrophysics
Dobbs C
(2019)
Comparing the properties of GMCs in M33 from simulations and observations
in Monthly Notices of the Royal Astronomical Society
Bennett E
(2019)
Sp (4) gauge theories on the lattice: Nf = 2 dynamical fundamental fermions
in Journal of High Energy Physics
Digby R
(2019)
The star formation histories of dwarf galaxies in Local Group cosmological simulations
in Monthly Notices of the Royal Astronomical Society
Callingham T
(2019)
The mass of the Milky Way from satellite dynamics
in Monthly Notices of the Royal Astronomical Society
Bijnens J
(2019)
Electromagnetic finite-size effects to the hadronic vacuum polarization
in Physical Review D
Duguid C
(2019)
Tidal flows with convection: frequency-dependence of the effective viscosity and evidence for anti-dissipation
in Monthly Notices of the Royal Astronomical Society
Mahmoud R
(2019)
Reverberation reveals the truncated disc in the hard state of GX 339-4
in Monthly Notices of the Royal Astronomical Society
Davies C
(2019)
Meson electromagnetic form factors from lattice QCD
Cautun M
(2019)
The aftermath of the Great Collision between our Galaxy and the Large Magellanic Cloud
in Monthly Notices of the Royal Astronomical Society
Raimondi F
(2019)
Core-polarization effects and effective charges in O and Ni isotopes from chiral interactions
in Physical Review C
Shanahan R
(2019)
Strong Excess Faraday Rotation on the Inside of the Sagittarius Spiral Arm
in The Astrophysical Journal Letters
Achúcarro A
(2019)
Cosmological evolution of semilocal string networks.
in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Haworth T
(2019)
The first multidimensional view of mass loss from externally FUV irradiated protoplanetary discs
in Monthly Notices of the Royal Astronomical Society
Witzke V
(2019)
Evolution and characteristics of forced shear flows in polytropic atmospheres: large and small Péclet number regimes
in Monthly Notices of the Royal Astronomical Society
Trayford J
(2019)
Resolved galaxy scaling relations in the eagle simulation: star formation, metallicity, and stellar mass on kpc scales
in Monthly Notices of the Royal Astronomical Society
Eilers A
(2019)
Anomaly in the Opacity of the Post-reionization Intergalactic Medium in the Ly a and Ly ß Forest
in The Astrophysical Journal
Davies C
(2019)
Improving the kinetic couplings in lattice nonrelativistic QCD
in Physical Review D
Bantilan H
(2019)
End point of nonaxisymmetric black hole instabilities in higher dimensions
in Physical Review D
Hillier A
(2019)
Ion-neutral decoupling in the nonlinear Kelvin-Helmholtz instability: Case of field-aligned flow
in Physics of Plasmas
Allanson O
(2019)
Particle-in-cell Experiments Examine Electron Diffusion by Whistler-mode Waves: 1. Benchmarking With a Cold Plasma
in Journal of Geophysical Research: Space Physics
Edelmann P
(2019)
Three-dimensional Simulations of Massive Stars. I. Wave Generation and Propagation
in The Astrophysical Journal
Comerford T
(2019)
Bondi-Hoyle-Lyttleton accretion by binary stars
in Monthly Notices of the Royal Astronomical Society
Guervilly C
(2019)
Turbulent convective length scale in planetary cores.
in Nature
Pagano P
(2019)
A Prospective New Diagnostic Technique for Distinguishing Eruptive and Noneruptive Active Regions
in The Astrophysical Journal
Rosito M
(2019)
Assembly of spheroid-dominated galaxies in the EAGLE simulation
in Astronomy & Astrophysics
Hatton D
(2019)
Renormalizing vector currents in lattice QCD using momentum-subtraction schemes
in Physical Review D
Jackson R
(2019)
Massive spheroids can form in single minor mergers
in Monthly Notices of the Royal Astronomical Society
Golightly E
(2019)
Tidal Disruption Events: The Role of Stellar Spin
in The Astrophysical Journal
Offler S
(2019)
News from bottomonium spectral functions in thermal QCD
Hall C
(2019)
The Temporal Requirements of Directly Observing Self-gravitating Spiral Waves in Protoplanetary Disks with ALMA
in The Astrophysical Journal
Garzilli A
(2019)
The Lyman-a forest as a diagnostic of the nature of the dark matter
in Monthly Notices of the Royal Astronomical Society
Nikolaev A.
(2019)
Mesonic correlators at non-zero baryon chemical potential
in Proceedings of Science
Idini A
(2019)
Ab Initio Optical Potentials and Nucleon Scattering on Medium Mass Nuclei.
in Physical review letters
Riley A
(2019)
The velocity anisotropy of the Milky Way satellite system
in Monthly Notices of the Royal Astronomical Society
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. |