scholarly journals Lattice QCD Application Development within the US DOE Exascale Computing Project

2018 ◽  
Vol 175 ◽  
pp. 09010 ◽  
Author(s):  
Richard Brower ◽  
Norman Christ ◽  
Carleton DeTar ◽  
Robert Edwards ◽  
Paul Mackenzie
Keyword(s):  
Lattice Qcd ◽  
Lattice Gauge Theory ◽  
Short Description ◽  
Department Of Energy ◽  
Application Development ◽  
Science And Engineering ◽  
Software Developers ◽  
Exascale Computing ◽  
Lattice Gauge ◽  
The Us

In October, 2016, the US Department of Energy launched the Exascale Computing Project, which aims to deploy exascale computing resources for science and engineering in the early 2020’s. The project brings together application teams, software developers, and hardware vendors in order to realize this goal. Lattice QCD is one of the applications. Members of the US lattice gauge theory community with significant collaborators abroad are developing algorithms and software for exascale lattice QCD calculations. We give a short description of the project, our activities, and our plans.

scholarly journals Performance Portability Strategies for Grid C++ Expression Templates

2018 ◽  
Vol 175 ◽  
pp. 09006 ◽  
Author(s):  
Peter A. Boyle ◽  
M.A. Clark ◽  
Carleton DeTar ◽  
Meifeng Lin ◽  
Verinder Rana ◽  
...  
Keyword(s):  
Lattice Qcd ◽  
Just In Time ◽  
Application Development ◽  
Performance Portability ◽  
Exascale Computing ◽  
Starting Point ◽  
The Us ◽  
And Performance ◽  
Expression Templates ◽  
Expression Template

One of the key requirements for the Lattice QCD Application Development as part of the US Exascale Computing Project is performance portability across multiple architectures. Using the Grid C++ expression template as a starting point, we report on the progress made with regards to the Grid GPU offloading strategies. We present both the successes and issues encountered in using CUDA, OpenACC and Just-In-Time compilation. Experimentation and performance on GPUs with a SU(3)×SU(3) streaming test will be reported. We will also report on the challenges of using current OpenMP 4.x for GPU offloading in the same code.

scholarly journals Preparing sparse solvers for exascale computing

2020 ◽  
Vol 378 (2166) ◽  
pp. 20190053
Author(s):  
Hartwig Anzt ◽  
Erik Boman ◽  
Rob Falgout ◽  
Pieter Ghysels ◽  
Michael Heroux ◽  
...  
Keyword(s):  
High Performance ◽  
Numerical Algorithms ◽  
Computational Science ◽  
Department Of Energy ◽  
High Fidelity ◽  
Scientific Applications ◽  
Exascale Computing ◽  
Multi Scale ◽  
The Us ◽  
Computing Platforms

Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly parallel sparse solvers are essential for continuing advances in high-fidelity, multi-physics and multi-scale simulations, especially as we target exascale platforms. This paper describes the challenges, strategies and progress of the US Department of Energy Exascale Computing project towards providing sparse solvers for exascale computing platforms. We address the demands of systems with thousands of high-performance node devices where exposing concurrency, hiding latency and creating alternative algorithms become essential. The efforts described here are works in progress, highlighting current success and upcoming challenges. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

Multiphysics coupling in the Exascale computing project

2021 ◽  
pp. 109434202110289
Author(s):  
Thomas M Evans ◽  
Julia C White
Keyword(s):  
High Performance ◽  
Computational Science ◽  
Department Of Energy ◽  
Special Issue ◽  
Computational Accuracy ◽  
Exascale Computing ◽  
The Us ◽  
Multiphysics Coupling ◽  
And Performance ◽  
Performance Computing

Multiphysics coupling presents a significant challenge in terms of both computational accuracy and performance. Achieving high performance on coupled simulations can be particularly challenging in a high-performance computing context. The US Department of Energy Exascale Computing Project has the mission to prepare mission-relevant applications for the delivery of the exascale computers starting in 2023. Many of these applications require multiphysics coupling, and the implementations must be performant on exascale hardware. In this special issue we feature six articles performing advanced multiphysics coupling that span the computational science domains in the Exascale Computing Project.

scholarly journals Fast algorithms for chiral fermions in 2 dimensions

2018 ◽  
Vol 175 ◽  
pp. 14005
Author(s):  
Dafina Hyka (Xhako) ◽  
Rudina Osmanaj (Zeqirllari)
Keyword(s):  
Domain Wall ◽  
Lattice Qcd ◽  
Promising Result ◽  
Lattice Gauge Theory ◽  
Computational Cost ◽  
The Other ◽  
Coupling Constant ◽  
Domain Wall Fermions ◽  
Lattice Gauge ◽  
High Computational Cost

In lattice QCD simulations the formulation of the theory in lattice should be chiral in order that symmetry breaking happens dynamically from interactions. In order to guarantee this symmetry on the lattice one uses overlap and domain wall fermions. On the other hand high computational cost of lattice QCD simulations with overlap or domain wall fermions remains a major obstacle of research in the field of elementary particles. We have developed the preconditioned GMRESR algorithm as fast inverting algorithm for chiral fermions in U(1) lattice gauge theory. In this algorithm we used the geometric multigrid idea along the extra dimension.The main result of this work is that the preconditioned GMRESR is capable to accelerate the convergence 2 to 12 times faster than the other optimal algorithms (SHUMR) for different coupling constant and lattice 32x32. Also, in this paper we tested it for larger lattice size 64x64. From the results of simulations we can see that our algorithm is faster than SHUMR. This is a very promising result that this algorithm can be adapted also in 4 dimension.

Interpolation and extrapolation

2018 ◽  
Author(s):  
Joseph F. Boudreau ◽  
Eric S. Swanson
Keyword(s):  
Public Transportation ◽  
Spline Interpolation ◽  
Lattice Gauge Theory ◽  
Human Vision ◽  
Physical Sciences ◽  
One Dimensional ◽  
Lattice Gauge ◽  
Multidimensional Problems ◽  
Data Points ◽  
Lagrange Interpolating Polynomial

This chapter deals with two related problems occurring frequently in the physical sciences: first, the problem of estimating the value of a function from a limited number of data points; and second, the problem of calculating its value from a series approximation. Numerical methods for interpolating and extrapolating data are presented. The famous Lagrange interpolating polynomial is introduced and applied to one-dimensional and multidimensional problems. Cubic spline interpolation is introduced and an implementation in terms of Eigen classes is given. Several techniques for improving the convergence of Taylor series are discussed, including Shank’s transformation, Richardson extrapolation, and the use of Padé approximants. Conversion between representations with the quotient-difference algorithm is discussed. The exercises explore public transportation, human vision, the wine market, and SU(2) lattice gauge theory, among other topics.

A sketch of the education landscape in biomimetic and biohybrid systems

2018 ◽  
Author(s):  
Anna Mura ◽  
Tony J. Prescott
Keyword(s):  
Social Sciences ◽  
Course Development ◽  
Science And Engineering ◽  
Arts And Humanities ◽  
Research And Innovation ◽  
Innovation Activities ◽  
The Social ◽  
The Us ◽  
Societal Context ◽  
Discipline Programs

The Living Machines approach, which can be seen as an exemplar methodology for a wider initiative towards “convergent science,” implies and requires a transdisciplinary understanding that bridges from between science and engineering and to the social sciences, arts, and humanities. In addition, it emphasizes a mix of basic and applied approaches whilst also requiring an awareness of the societal context in which modern research and innovation activities are conducted. This chapter explores the education landscape for postgraduate programs related to the concept of Living Machines, highlighting some challenges that should be addressed and providing suggestions for future course development and policy making. The chapter also reviews some of the within-discipline and across-discipline programs that currently exist, particularly within Europe and the US, and outlines an exemplar degree program that could provide the multi-faceted training needed to pursue research and innovation in Living Machines.

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