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
Reissl S
(2020)
Synthetic observations of spiral arm tracers of a simulated Milky Way analog
in Astronomy & Astrophysics
Christiansen J
(2020)
Jet feedback and the photon underproduction crisis in simba
in Monthly Notices of the Royal Astronomical Society
Robertson A
(2020)
Mapping dark matter and finding filaments: calibration of lensing analysis techniques on simulated data
in Monthly Notices of the Royal Astronomical Society
Smith R
(2020)
The Cloud Factory I: Generating resolved filamentary molecular clouds from galactic-scale forces
in Monthly Notices of the Royal Astronomical Society
Hildebrandt H
(2020)
KiDS+VIKING-450: Cosmic shear tomography with optical and infrared data
in Astronomy & Astrophysics
Pagano P
(2020)
Hydrogen non-equilibrium ionisation effects in coronal mass ejections
in Astronomy & Astrophysics
Duguid C
(2020)
Convective turbulent viscosity acting on equilibrium tidal flows: new frequency scaling of the effective viscosity
in Monthly Notices of the Royal Astronomical Society
Joudaki S
(2020)
KiDS+VIKING-450 and DES-Y1 combined: Cosmology with cosmic shear
in Astronomy & Astrophysics
Witek H
(2020)
Towards numerical relativity in scalar Gauss-Bonnet gravity: 3 + 1 decomposition beyond the small-coupling limit
in Physical Review D
Ilee J
(2020)
Observing protoplanetary discs with the Square Kilometre Array - I. Characterizing pebble substructure caused by forming planets
in Monthly Notices of the Royal Astronomical Society
Falle S
(2020)
Thermal instability revisited
in Monthly Notices of the Royal Astronomical Society
Kordov Z
(2020)
Electromagnetic contribution to S - ? mixing using lattice QCD + QED
in Physical Review D
Boyle P
(2020)
Latest Results on Lattice Calculation Concerning K ? p l + l - Decays
in Journal of Physics: Conference Series
Van der Werf P
(2020)
An ALMA survey of the SCUBA-2 CLS UDS field: physical properties of 707 sub-millimetre galaxies
in Monthly Notices of the Royal Astronomical Society
Campargue A
(2020)
Detection of electric-quadrupole transitions in water vapour near 5.4 and 2.5 µm.
in Physical chemistry chemical physics : PCCP
Buie E
(2020)
Interpreting Observations of Absorption Lines in the Circumgalactic Medium with a Turbulent Medium
in The Astrophysical Journal
Sedda M
(2020)
The missing link in gravitational-wave astronomy: discoveries waiting in the decihertz range
in Classical and Quantum Gravity
Fumagalli M
(2020)
Detecting neutral hydrogen at z ? 3 in large spectroscopic surveys of quasars
in Monthly Notices of the Royal Astronomical Society
Keating L
(2020)
Constraining the second half of reionization with the Ly ß forest
in Monthly Notices of the Royal Astronomical Society
White S
(2020)
The globular cluster system of the Auriga simulations
in Monthly Notices of the Royal Astronomical Society
Threlfall J
(2020)
How Is Helicity (and Twist) Partitioned in Magnetohydrodynamic Simulations of Reconnecting Magnetic Flux Tubes?
in The Astrophysical Journal
Santos-Santos I
(2020)
Baryonic clues to the puzzling diversity of dwarf galaxy rotation curves
in Monthly Notices of the Royal Astronomical Society
Bantilan H
(2020)
Real-Time Dynamics of Plasma Balls from Holography
in Physical Review Letters
Clarke C
(2020)
Forbidden line diagnostics of photoevaporative disc winds
in Monthly Notices of the Royal Astronomical Society
Hughes M
(2020)
The [a/Fe]-[Fe/H] relation in the E-MOSAICS simulations: its connection to the birth place of globular clusters and the fraction of globular cluster field stars in the bulge
in Monthly Notices of the Royal Astronomical Society
Pedersen C
(2020)
Massive neutrinos and degeneracies in Lyman-alpha forest simulations
in Journal of Cosmology and Astroparticle Physics
Yip K
(2020)
On the Compatibility of Ground-based and Space-based Data: WASP-96 b, an Example*
in The Astronomical Journal
Kay S
(2020)
The intracluster light as a tracer of the total matter density distribution: a view from simulations
in Monthly Notices of the Royal Astronomical Society
Richings J
(2020)
Subhalo destruction in the Apostle and Auriga simulations
in Monthly Notices of the Royal Astronomical Society
Can K
(2020)
Lattice QCD evaluation of the Compton amplitude employing the Feynman-Hellmann theorem
in Physical Review D
Appleby S
(2020)
The impact of quenching on galaxy profiles in the simba simulation
in Monthly Notices of the Royal Astronomical Society
Ho S
(2020)
Morphological and Rotation Structures of Circumgalactic Mg ii Gas in the EAGLE Simulation and the Dependence on Galaxy Properties
in The Astrophysical Journal
Changeat Q
(2020)
TauREx3 PhaseCurve: A 1.5D Model for Phase-curve Description
in The Astrophysical Journal
Pagano P
(2020)
Effect of coronal loop structure on wave heating through phase mixing
in Astronomy & Astrophysics
Kirchschlager F
(2020)
Silicate Grain Growth due to Ion Trapping in Oxygen-rich Supernova Remnants like Cassiopeia A
in The Astrophysical Journal
Pakmor R
(2020)
The orbital phase space of contracted dark matter haloes
in Monthly Notices of the Royal Astronomical Society
Pettini M
(2020)
A bound on the 12C/13C ratio in near-pristine gas with ESPRESSO
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
Beraldo e Silva L
(2020)
Geometric properties of galactic discs with clumpy episodes
in Monthly Notices of the Royal Astronomical Society
Donevski D
(2020)
In pursuit of giants I. The evolution of the dust-to-stellar mass ratio in distant dusty galaxies
in Astronomy & Astrophysics
Guilluy G
(2020)
ARES IV: Probing the Atmospheres of the Two Warm Small Planets HD 106315c and HD 3167c with the HST/WFC3 Camera
in The Astronomical Journal
Rosca-Mead R
(2020)
Structure of Neutron Stars in Massive Scalar-Tensor Gravity
in Symmetry
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
McAlpine S
(2020)
Galaxy mergers in eagle do not induce a significant amount of black hole growth yet do increase the rate of luminous AGN
in Monthly Notices of the Royal Astronomical Society
Allanson O
(2020)
Particle-in-Cell Experiments Examine Electron Diffusion by Whistler-Mode Waves: 2. Quasi-Linear and Nonlinear Dynamics
in Journal of Geophysical Research: Space Physics
Edwards B
(2020)
ARES I: WASP-76 b, A Tale of Two HST Spectra*
in The Astronomical Journal
Igoshev A
(2020)
Strong toroidal magnetic fields required by quiescent X-ray emission of magnetars
in Nature Astronomy
Aviles A
(2020)
Marked correlation functions in perturbation theory
in Journal of Cosmology and Astroparticle Physics
Solar M
(2020)
Azimuthal variations of oxygen abundance profiles in star-forming regions of disc galaxies in EAGLE simulations
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. |