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
Bantilan H
(2021)
Cauchy evolution of asymptotically global AdS spacetimes with no symmetries
in Physical Review D
Young A
(2022)
Characteristics of small protoplanetary disc warps in kinematic observations
in Monthly Notices of the Royal Astronomical Society
Young A
(2022)
Characteristics of small protoplanetary disc warps in kinematic observations
in Monthly Notices of the Royal Astronomical Society
Edwards B
(2023)
Characterizing a World Within the Hot-Neptune Desert: Transit Observations of LTT 9779 b with the Hubble Space Telescope/WFC3
in The Astronomical Journal
Ruiz-Macias O
(2021)
Characterizing the target selection pipeline for the Dark Energy Spectroscopic Instrument Bright Galaxy Survey
in Monthly Notices of the Royal Astronomical Society
Beane S
(2021)
Charged multihadron systems in lattice QCD + QED
in Physical Review D
Bignell R
(2023)
Charm baryons at finite temperature on anisotropic lattices
Bignell R
(2022)
Charm baryons at finite temperature on anisotropic lattices
Bignell R
(2023)
Charm baryons at finite temperature on anisotropic lattices
Hatton D
(2020)
Charmonium properties from lattice QCD + QED : Hyperfine splitting, J / ? leptonic width, charm quark mass, and a µ c
in Physical Review D
Zhu Y
(2021)
Chasing the Tail of Cosmic Reionization with Dark Gap Statistics in the Lya Forest over 5 < z < 6
in The Astrophysical Journal
Varghese A
(2023)
Chemical Mixing Induced by Internal Gravity Waves in Intermediate-mass Stars
in The Astrophysical Journal
Young A
(2021)
Chemical signatures of a warped protoplanetary disc
in Monthly Notices of the Royal Astronomical Society
Ragusa E
(2021)
Circumbinary and circumstellar discs around the eccentric binary IRAS 04158+2805 - a testbed for binary-disc interaction
in Monthly Notices of the Royal Astronomical Society
Vandenbroucke B
(2020)
CMACIONIZE 2.0: a novel task-based approach to Monte Carlo radiation transfer
in Astronomy & Astrophysics
Rosenberg E
(2022)
CMB power spectra and cosmological parameters from Planck PR4 with CamSpec
in Monthly Notices of the Royal Astronomical Society
Rosenberg E
(2022)
CMB power spectra and cosmological parameters from Planck PR4 with CamSpec
in Monthly Notices of the Royal Astronomical Society
Sohn W
(2019)
CMB-S4 forecast on the primordial non-Gaussianity parameter of feature models
in Physical Review D
Beraldo e Silva L
(2021)
Co-formation of the thin and thick discs revealed by APOGEE-DR16 and Gaia -DR2
in Monthly Notices of the Royal Astronomical Society
Aurrekoetxea J
(2020)
Coherent gravitational waveforms and memory from cosmic string loops
in Classical and Quantum Gravity
Ananyev V
(2023)
Collider constraints on electroweakinos in the presence of a light gravitino
in The European Physical Journal C
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
Bennett E
(2020)
Color dependence of tensor and scalar glueball masses in Yang-Mills theories
in Physical Review D
Igoshev A
(2021)
Combined analysis of neutron star natal kicks using proper motions and parallax measurements for radio pulsars and Be X-ray binaries
in Monthly Notices of the Royal Astronomical Society
Dobbs C
(2019)
Comparing the properties of GMCs in M33 from simulations and observations
in Monthly Notices of the Royal Astronomical Society
Pratt J
(2020)
Comparison of 2D and 3D compressible convection in a pre-main sequence star
in Astronomy & Astrophysics
Bolton JS
(2022)
Comparison of Low-Redshift Lyman-a Forest Observations to Hydrodynamical Simulations with Dark Photon Dark Matter.
in Physical review letters
Bolton JS
(2022)
Comparison of Low-Redshift Lyman-a Forest Observations to Hydrodynamical Simulations with Dark Photon Dark Matter.
in Physical review letters
Pariat E
(2023)
Comparison of magnetic energy and helicity in coronal jet simulations
in Astronomy & Astrophysics
Pariat E
(2023)
Comparison of magnetic energy and helicity in coronal jet simulations
in Astronomy & Astrophysics
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
Attanasio F
(2020)
Complex Langevin simulations and the QCD phase diagram: recent developments
in The European Physical Journal A
Drach V
(2020)
Composite electroweak sectors on the lattice
Ripley J
(2022)
Computing the quasinormal modes and eigenfunctions for the Teukolsky equation using horizon penetrating, hyperboloidally compactified coordinates
in Classical and Quantum Gravity
Ripley J
(2022)
Computing the quasinormal modes and eigenfunctions for the Teukolsky equation using horizon penetrating, hyperboloidally compactified coordinates
in Classical and Quantum Gravity
Theuns T
(2021)
Connecting cosmological accretion to strong Ly a absorbers
in Monthly Notices of the Royal Astronomical Society
Brown S
(2020)
Connecting the structure of dark matter haloes to the primordial power spectrum
in Monthly Notices of the Royal Astronomical Society
Smail R
(2023)
Constraining beyond the standard model nucleon isovector charges
in Physical Review D
Lamberts A
(2022)
Constraining blazar heating with the 2 ? z ? 3 Lyman-a forest
in Monthly Notices of the Royal Astronomical Society
Lamberts A
(2022)
Constraining blazar heating with the 2 ? z ? 3 Lyman-a forest
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
Reeves A
(2023)
Constraining quenching time-scales in galaxy clusters by forward-modelling stellar ages and quiescent fractions in projected phase space
in Monthly Notices of the Royal Astronomical Society
Leo M
(2020)
Constraining structure formation using EDGES
in Journal of Cosmology and Astroparticle Physics
Humphries J
(2019)
Constraining the initial planetary population in the gravitational instability model
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
Keating L
(2020)
Constraining the second half of reionization with the Ly ß forest
in Monthly Notices of the Royal Astronomical Society
Reina-Campos M
(2023)
Constraining the shape of dark matter haloes with globular clusters and diffuse stellar light in the E-MOSAICS 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. |