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Computing Patterns for High Performance Multiscale Computing

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Objective

Multiscale phenomena are ubiquitous and they are the key to understanding the complexity of our world. Despite the significant progress achieved through computer simulations over the last decades, we are still limited in our capability to accurately and reliably simulate hierarchies of interacting multiscale physical processes that span a wide range of time and length scales, thus quickly reaching the limits of contemporary high performance computing at the tera- and petascale. Exascale supercomputers promise to lift this limitation, and in this project we will develop multiscale computing algorithms capable of producing high-fidelity scientific results and scalable to exascale computing systems. Our main objective is to develop generic and reusable High Performance Multiscale Computing algorithms that will address the exascale challenges posed by heterogeneous architectures and will enable us to run multiscale applications with extreme data requirements while achieving scalability, robustness, resiliency, and energy efficiency. Our approach is based on generic multiscale computing patterns that allow us to implement customized algorithms to optimise load balancing, data handling, fault tolerance and energy consumption under generic exascale application scenarios. We will realise an experimental execution environment on our pan-European facility, which will be used to measure performance characteristics and develop models that can provide reliable performance predictions for emerging and future exascale architectures. The viability of our approach will be demonstrated by implementing nine grand challenge applications which are exascale-ready and pave the road to unprecedented scientific discoveries. Our ambition is to establish new standards for multiscale computing at exascale, and provision a robust and reliable software technology stack that empowers multiscale modellers to transform computer simulations into predictive science.

Programme(s)

H2020-EU.1.2.2. - FET Proactive

Topic(s)

FETHPC-1-2014 - HPC Core Technologies, Programming Environments and Algorithms for Extreme Parallelism and Extreme Data Applications

Call for proposal

H2020-FETHPC-2014

See other projects for this call

Funding Scheme

RIA - Research and Innovation action

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Coordinator

UNIVERSITEIT VAN AMSTERDAM

Address

Spui 21
1012wx Amsterdam

Netherlands

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 754 000

Website

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Participants (12)

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UNIVERSITY COLLEGE LONDON

United Kingdom

EU Contribution

€ 603 125

INSTYTUT CHEMII BIOORGANICZNEJ POLSKIEJ AKADEMII NAUK

Poland

EU Contribution

€ 435 375

BAYERISCHE AKADEMIE DER WISSENSCHAFTEN

Germany

EU Contribution

€ 423 375

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV

Germany

EU Contribution

€ 413 625

UNIVERSITEIT LEIDEN

Netherlands

EU Contribution

€ 370 710

SCIENCE AND TECHNOLOGY FACILITIES COUNCIL

United Kingdom

UNITED KINGDOM RESEARCH AND INNOVATION

United Kingdom

EU Contribution

€ 346 750

ALLINEA SOFTWARE LIMITED

United Kingdom

EU Contribution

€ 110 156,91

CBK SCI CON LIMITED

United Kingdom

EU Contribution

€ 128 125

SAINT PETERSBURG NATIONAL RESEARCH UNIVERSITY OF INFORMATION TECHNOLOGIES, MECHANICS AND OPTICS

Russia

BRUNEL UNIVERSITY LONDON

United Kingdom

ARM LIMITED

United Kingdom

EU Contribution

€ 357 643,09

Project information

ComPat

Grant agreement ID: 671564

Project website

Start date

1 October 2015
End date

30 September 2018

Funded under:

H2020-EU.1.2.2.

Overall budget:

€ 4 122 864,36
EU contribution

€ 3 942 885

Coordinated by:

UNIVERSITEIT VAN AMSTERDAM

Netherlands

Periodic Reporting for period 2 - ComPat (Computing Patterns for High Performance Multiscale Computing)

Reporting period: 2017-04-01 to 2018-09-30

Summary of the context and overall objectives of the project

Our Objectives:
Our main objective is to develop generic and reusable High Performance Multiscale Computing algorithms that will enable us to tackle scientific grand challenges at the exascale. The algorithms will provide scalability, robustness, resiliency, and efficiency of multiscale applications with extreme data requirements. We will formalise three multiscale computing patterns, all of them incorporating customized algorithms for load balancing, data handling, fault tolerance and energy consumption under generic exascale application scenarios, as well as performance prediction models. We will develop and implement all algorithms required by the three multiscale computing patterns, co- designing with the anticipated characteristics of exascale machines and providing strategies for optimisation with respect to such characteristics. We will develop an application toolkit needed to instantiate the computing patterns which in turn will allow multiscale simulations to reach exascale performance. Adopting selected middleware, we will realise an Experimental Execution Environment on HPC resources available to the project. We will implement nine grand challenge applications as instantiations of the multiscale computing patterns. Their scalability and performance will be measured on available high performance computing systems and will be predicted for future exascale systems. The added value of our approach for software engineering for extreme parallelism will be demonstrated.

Main Results of ComPat:
ComPat has delivered a design of three Multiscale Computing Patterns (MCP), implemented MCP algorithms and software, and tested this software on a Pan-European Experimental Execution Environment operated by the project. ComPat delivered an integrated software stack, relying on QCG, to execute a range of multiscale applications on the EEE, using the MCP algorithms and software. This resulted both in a proof of concept of the vision of MCPs, as well as detailed performance measurement of multiscale applications executed with the MCP algorithms and software. ComPat has strongly disseminated these results in papers, conferences, workshops, schools, and a webinar, as well as by creating a set of videos to explain the major developments in ComPat.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

ComPat logo

ComPat architecture

Project information

ComPat

Grant agreement ID: 671564

Project website

Start date

1 October 2015
End date

30 September 2018

Funded under:

H2020-EU.1.2.2.

Overall budget:

€ 4 122 864,36
EU contribution

€ 3 942 885

Coordinated by:

UNIVERSITEIT VAN AMSTERDAM

Deliverables

Documents, reports (21)

Interim Report on Instantiating Computing Patterns for HPMC Applications

Interim report about our progress in employing multiscale computing patterns in actual scientific applications. It will contain an assessment of the efficacy of the patterns as well as recommendations and best practices for their instantiation.

Report on Application Software Readiness

Report the specific requirements of the applications as identified during Task 3.1.

Quality Assurance Plan

To manage and support the project Quality Control, a documented Quality Assurance Plan will be set up and maintained to monitor all deliverables before finalising them. The deliverable also contains a detailed risk analysis and contingency planning.

First Dissemination Report

Review events and dissemination results of past year and proposes actions for the coming one, including update of dissemination action plan.

First progress report on the Experimental Execution Environment

This deliverable will present the progress in the installation, configuration, and usage of the Experimental Execution Environment. This deliverable will also include the first version of the ComPat Experimental Execution Environment user guide.

Report on integration of ComPat services with multiscale coupling libraries and patterns

A document describing the final integration of ComPat services with multiscale coupling libraries and patterns including references to ComPat applications executed on the ComPat Pan-European Experimental Execution Environment.

Report and software on design of tools and required actions to support performance tools for multiscale

Report on an analyses of the requirements for the tools (debug, profile and analyse performance) and design and architecture of a solution appropriate to support the multiscale patterns.

Architecture of the ComPat system

A document describing the overall architecture of the ComPat system including relationships between developed in the project toolkits and services.

Report on Existing Software Suitability and Adaptation

Report on what software will be used in the project, how it compares to other software packages, and outline a detailed plan for their adaptation and integration, as well as report on MML implementation and status report on implementation of the multiscale computing patterns.

Final report on the Experimental Execution Environment

An update of deliverable D6.3.

Final report on high level tools, including performance profiling and modelling

Report on the status of the tools, and on the validation of the impact of measurement and analysis on the applications – and on the accuracy of the modelling tools as applied to simulations at the scales of machines available during the latter months of the project.

Report on the assessment of operational procedures and definition of the ComPat operational model

Report on Instantiating Computing Patterns and performance measurements and prediction of HPMC Application

Report on the performance of all selected multiscale applications as measured on the Experimental Execution Environment and other available resources. It will give a detailed account of various metrics of resource usage, including wall clock time, data throughput, scalability and energy consumption. It will furnish detailed performance predictions for all selected multiscale applications on future exascale systems. This report will, as a major outcome of this project, present a forecast of the actual impact that exascale resources may have on future science applications by leveraging extreme parallelism.

Final Report on Multiscale Computing Patterns, including their Performance

Final report on the performance of all selected multiscale applications as measured on the Experimental Execution Environment and selected production environments. It will give a detailed account of various metrics of resource usage, including wall clock time, data throughput, scalability and energy consumption. It will also provide a detailed account on the performance prediction models.

First Report on Multiscale Computing Patterns and Algorithms

First report on the algorithms and components used to construct the Multiscale Computing Patterns, details of the actual implementation, and preliminary results on performance measurements.

First Report on status of performance profiling of multiscale simulations

First report on an analysis of the changes and impact on the initial simulations using the initial tools, including any architectural changes required since D4.1.

First Report on ComPat middleware services

A document summarizing the status of development of services offering a set of key capabilities for toolkits and patterns from WP2, including QoS on computational Tier-0/1 resources, dynamic multi-cluster co-allocation of resources, energy optimization and multi-cluster deployment and execution of ComPat multiscale simulations consisting of cooperating sub-models.

Third Dissemination Report

Review events and dissemination results of second project period.

Second Dissemination Report

Review events and dissemination results and propose actions for the coming one, including update of dissemination action plan.

Detailed Dissemination Action plan

Project Handbook

To ensure a consistent implementation of the management of the project, UvA will produce a project procedure handbook that will be easily accessible to all Partners.

Publications

Peer reviewed articles (26)

Numerical verification of the microscopic time reversibility of Newton’s equations of motion: Fighting exponential divergence

Author(s): Simon F. Portegies Zwart, Tjarda C.N. Boekholt

Published in: Communications in Nonlinear Science and Numerical Simulation, Issue 61, 2018, Page(s) 160-166, ISSN 1007-5704

DOI: 10.1016/j.cnsns.2018.02.002

The Oceanographic Multipurpose Software Environment (OMUSE v1.0)

Author(s): Inti Pelupessy, Ben van Werkhoven, Arjen van Elteren, Jan Viebahn, Adam Candy, Simon Portegies Zwart, Henk Dijkstra

Published in: Geoscientific Model Development, Issue 10/8, 2017, Page(s) 3167-3187, ISSN 1991-9603

DOI: 10.5194/gmd-10-3167-2017

The dynamics of stellar discs in live dark-matter haloes

Author(s): M S Fujii, J Bédorf, J Baba, S Portegies Zwart

Published in: Monthly Notices of the Royal Astronomical Society, Issue 477/2, 2018, Page(s) 1451-1471, ISSN 0035-8711

DOI: 10.1093/mnras/sty711

Stability of exomoons around the Kepler transiting circumbinary planets

Author(s): Adrian S Hamers, Maxwell X Cai, Javier Roa, Nathan Leigh

Published in: Monthly Notices of the Royal Astronomical Society, Issue 480/3, 2018, Page(s) 3800-3811, ISSN 0035-8711

DOI: 10.1093/mnras/sty2117

Cellular Level In-silico Modeling of Blood Rheology with An Improved Material Model for Red Blood Cells

Author(s): Gábor Závodszky, Britt van Rooij, Victor Azizi, Alfons Hoekstra

Published in: Frontiers in Physiology, Issue 8, 2017, Page(s) 563, ISSN 1664-042X

DOI: 10.3389/fphys.2017.00563

A Comparison of Fully-Coupled 3D In-Stent Restenosis Simulations to In-vivo Data

Author(s): Pavel S. Zun, Tatiana Anikina, Andrew Svitenkov, Alfons G. Hoekstra

Published in: Frontiers in Physiology, Issue 8, 2017, ISSN 1664-042X

DOI: 10.3389/fphys.2017.00284

Validation of Patient-Specific Cerebral Blood Flow Simulation Using Transcranial Doppler Measurements

Author(s): Derek Groen, Robin A. Richardson, Rachel Coy, Ulf D. Schiller, Hoskote Chandrashekar, Fergus Robertson, Peter V. Coveney

Published in: Frontiers in Physiology, Issue 9, 2018, ISSN 1664-042X

DOI: 10.3389/fphys.2018.00721

Chemically Specific Multiscale Modeling of the Shear-Induced Exfoliation of Clay–Polymer Nanocomposites

Author(s): James L. Suter, Peter V. Coveney

Published in: ACS Omega, Issue 3/6, 2018, Page(s) 6439-6445, ISSN 2470-1343

DOI: 10.1021/acsomega.8b00542

The Oceanographic Multipurpose SoftwareEnvironment

Author(s): Inti Pelupessy, Ben van Werkhoven, Arjen van Elteren, Jan Viebahn, Adam Candy, Simon Portegies Zwart, Henk Dijkstra

Published in: Geoscientific Model Development Discussions, 2016, Page(s) 1-36, ISSN 1991-962X

DOI: 10.5194/gmd-2016-178

The signatures of the parental cluster on field planetary systems

Author(s): Maxwell Xu Cai, Simon Portegies Zwart, Arjen van Elteren

Published in: Monthly Notices of the Royal Astronomical Society, Issue 474/4, 2017, Page(s) 5114-5121, ISSN 0035-8711

DOI: 10.1093/mnras/stx3064

The origin of interstellar asteroidal objects like 1I/2017 U1 ‘Oumuamua

Author(s): Simon Portegies Zwart, Santiago Torres, Inti Pelupessy, Jeroen Bédorf, Maxwell X Cai

Published in: Monthly Notices of the Royal Astronomical Society: Letters, Issue 479/1, 2018, Page(s) L17-L22, ISSN 1745-3933

DOI: 10.1093/mnrasl/sly088

Multiscale modeling: recent progress and open questions

Author(s): Bastien Chopard, Jean-Luc Falcone, Pierre Kunzli, Lourens Veen, Alfons Hoekstra

Published in: Multiscale and Multidisciplinary Modeling, Experiments and Design, Issue 1/1, 2018, Page(s) 57-68, ISSN 2520-8160

DOI: 10.1007/s41939-017-0006-4

Stability of multiplanetary systems in star clusters

Author(s): Maxwell Xu Cai (蔡栩), M. B. N. Kouwenhoven, Simon F. Portegies Zwart, Rainer Spurzem

Published in: Monthly Notices of the Royal Astronomical Society, Issue 470/4, 2017, Page(s) 4337-4353, ISSN 0035-8711

DOI: 10.1093/mnras/stx1464

Uncertainty Quantification of a Multiscale Model for In-Stent Restenosis

Author(s): Anna Nikishova, Lourens Veen, Pavel Zun, Alfons G. Hoekstra

Published in: Cardiovascular Engineering and Technology, 2018, ISSN 1869-408X

DOI: 10.1007/s13239-018-00372-4

Multiscale computing in the exascale era

Author(s): Saad Alowayyed, Derek Groen, Peter V. Coveney, Alfons G. Hoekstra

Published in: Journal of Computational Science, Issue 22, 2017, Page(s) 15-25, ISSN 1877-7503

DOI: 10.1016/j.jocs.2017.07.004

On the calculation of equilibrium thermodynamic properties from molecular dynamics

Author(s): Peter V. Coveney, Shunzhou Wan

Published in: Physical Chemistry Chemical Physics, Issue 18/44, 2016, Page(s) 30236-30240, ISSN 1463-9076

DOI: 10.1039/c6cp02349e

Load balancing of parallel cell-based blood flow simulations

Author(s): S. Alowayyed, G. Závodszky, V. Azizi, A.G. Hoekstra

Published in: Journal of Computational Science, Issue 24, 2018, Page(s) 1-7, ISSN 1877-7503

DOI: 10.1016/j.jocs.2017.11.008

The evolution of hierarchical triple star-systems

Author(s): Silvia Toonen, Adrian Hamers, Simon Portegies Zwart

Published in: Computational Astrophysics and Cosmology, Issue 3/1, 2016, ISSN 2197-7909

DOI: 10.1186/s40668-016-0019-0

Hemocell: a high-performance microscopic cellular library

Author(s): Gábor Zavodszky, Britt van Rooij, Victor Azizi, Saad Alowayyed, Alfons Hoekstra

Published in: Procedia Computer Science, Issue 108, 2017, Page(s) 159-165, ISSN 1877-0509

DOI: 10.1016/j.procs.2017.05.084

Patterns for High Performance Multiscale Computing

Author(s): S. Alowayyed, T. Piontek, J.L. Suter, O. Hoenen, D. Groen, O. Luk, B. Bosak, P. Kopta, K. Kurowski, O. Perks, K. Brabazon, V. Jancauskas, D. Coster, P.V. Coveney, A.G. Hoekstra

Published in: Future Generation Computer Systems, Issue 91, 2019, Page(s) 335-346, ISSN 0167-739X

DOI: 10.1016/j.future.2018.08.045

Simulations of stripped core-collapse supernovae in close binaries

Author(s): Alex Rimoldi, Simon Portegies Zwart, Elena Maria Rossi

Published in: Computational Astrophysics and Cosmology, Issue 3/1, 2016, ISSN 2197-7909

DOI: 10.1186/s40668-016-0015-4

Uncertainty Quantification in Alchemical Free Energy Methods

Author(s): Agastya P. Bhati, Shunzhou Wan, Yuan Hu, Brad Sherborne, Peter V. Coveney

Published in: Journal of Chemical Theory and Computation, Issue 14/6, 2018, Page(s) 2867-2880, ISSN 1549-9618

DOI: 10.1021/acs.jctc.7b01143

PolNet: A Tool to Quantify Network-Level Cell Polarity and Blood Flow in Vascular Remodeling

Author(s): Miguel O. Bernabeu, Martin L. Jones, Rupert W. Nash, Anna Pezzarossa, Peter V. Coveney, Holger Gerhardt, Claudio A. Franco

Published in: Biophysical Journal, Issue 114/9, 2018, Page(s) 2052-2058, ISSN 0006-3495

DOI: 10.1016/j.bpj.2018.03.032

The Role of Multiscale Protein Dynamics in Antigen Presentation and T Lymphocyte Recognition

Author(s): R. Charlotte Eccleston, Shunzhou Wan, Neil Dalchau, Peter V. Coveney

Published in: Frontiers in Immunology, Issue 8, 2017, ISSN 1664-3224

DOI: 10.3389/fimmu.2017.00797

Graphene-Graphene Interactions: Friction, Superlubricity, and Exfoliation

Author(s): Robert C. Sinclair, James L. Suter, Peter V. Coveney

Published in: Advanced Materials, Issue 30/13, 2018, Page(s) 1705791, ISSN 0935-9648

DOI: 10.1002/adma.201705791

SiMon: Simulation Monitor for Computational Astrophysics

Author(s): Penny Xuran Qian, Maxwell Xu Cai, Simon Portegies Zwart, Ming Zhu

Published in: Publications of the Astronomical Society of the Pacific, Issue 129/979, 2017, Page(s) 094503, ISSN 0004-6280

DOI: 10.1088/1538-3873/aa7c49

Other (12)

Predicting Queue Wait Time Probabilities for Multi-Scale Computing

Author(s): V. Jancauskas, T. Piontek, P. Kopta, B. Bosak

Published in: Philosophical Transactions of the Royal Society, 2018

Development of a multiscale simulation approach for forced migration

Author(s): D. Groen

Published in: ICCS 2018, Springer Lecture Notes in Computer Science (LNCS), 2018

The heterogeneous multiscale method applied to inelastic polymer mechanics

Author(s): M. Vassaux, R. Richardson, P. V. Coveney

Published in: 2018

DOI: 10.1098/rsta.2018.0150

Big Data: the End of the Scientific Method?

Author(s): Sauro Succi, Peter V. Coveney

Published in: Phil Trans R Soc (Series A), 2018

DOI: 10.1098/rsta.2018.0145

Load Balancing Massively Parallel Cell-based Blood Flow Simulations

Author(s): S. Alowayyed, V. Azizi, G. Zavodszky and A. G. Hoekstra

Published in: Computer Physics Communications, 2018

Modelling Refugees Escaping Violent Events: A Feasibility Study From An Input Data Perspective

Author(s): N. T. Chan, D. Suleimenova, D. Bell, D. Groen

Published in: Proceedings of the Operational Research Society Simulation Workshop 2018, 2018

Mastering the scales: A survey on the benefits of multiscale computing software

Author(s): D. Groen, J. Knap, P. Neumann, D. Suleimenova, L. Veen, K. Leiter

Published in: Philosophical Transactions A: Mathematical, Physical and Engineering Sciences, 2018

DOI: 10.1098/rsta.2018.0147

Multiscale Computing for Science and Engineering in the Era of Exascale Performance

Author(s): A. G. Hoekstra, B. Chopard, D. Coster, S. Portegies Zwar, P. V. Coveney

Published in: 2018

DOI: 10.1098/rsta.2018.0144

ComPat Framework for Multiscale Simulations Applied to Fusion Plasmas

Author(s): O. Luk, O. Hoenen, A. Bottino, B. Scott, D. Coster

Published in: Computer Physics Communications, 2018

Application of the Extreme Scaling Computing Pattern on Multiscale Fusion Plasma Modelling

Author(s): O. O. Luk, O. Hoenen, O. Perks, K. Brabazon, T. Piontek, P. Kopta, B. Bosak, A. Bottino, B. D. Scott, D. P. Coster

Published in: 2018

DOI: 10.1098/rsta.2018.0152

A Distributed Multi-agent Market Place for HPC Compute Cycle Resource Trading”

Author(s): S. J. Zasada and P. V. Coveney

Published in: CoRR, 2015

High-throughput Binding Affinity Calculations at Extreme Scales

Author(s): Dakka, Jumana; Turilli, Matteo; Wright, David W; Zasada, Stefan J; Balasubramanian, Vivek; Wan, Shunzhou; Coveney, Peter V; Jha, Shantenu

Published in: BioMed Central, Issue 1, 2018

Conference proceedings (1)

Concurrent and Adaptive Extreme Scale Binding Free Energy Calculations

Author(s): Dakka, Jumana; Farkas-Pall, Kristof; Turilli, Matteo; Wright, David W; Coveney, Peter V; Jha, Shantenu

Published in: arXiv, Issue 1, 2018

Monographic books (1)

Astrophysical Recipes: the Art of AMUSE

Author(s): S. Portegies Zwart and S. McMillan

Published in: AAS IOP Astronomy, 2018

Project information

ComPat

Grant agreement ID: 671564

Project website

Start date

1 October 2015
End date

30 September 2018

Funded under:

H2020-EU.1.2.2.

Overall budget:

€ 4 122 864,36
EU contribution

€ 3 942 885

Coordinated by:

UNIVERSITEIT VAN AMSTERDAM

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Last update: 17 August 2017

Record number: 197534

CORDIS

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Participants (12)

Project information

Periodic Reporting for period 2 - ComPat (Computing Patterns for High Performance Multiscale Computing)

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