Special Issue "High-Performance Computing 2020"

A special issue of Mathematical and Computational Applications (ISSN 2297-8747).

Deadline for manuscript submissions: closed (31 May 2020).

Special Issue Editors

Dr. Alois Schlögl
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Guest Editor
IST Austria (Institute of Science and Technology Austria), Am Campus 1, A-3400 Klosterneuburg, Austria
Interests: electrophysiological modelling; high-performance computing; scientific computing
Prof. Dr. Ulrich Langer
E-Mail Website
Guest Editor
Institute of Computational Mathematics, Johannes Kepler University Linz, Altenberger Strasse 69, A-4040 Linz, Austria
Interests: numerical methods for PDEs; computational mechanics; computational electrodynamics; multi-grid methods; domain decomposition methods; FEM, IGA, BEM; parallel computing
Prof. Dr. Gundolf Haase
E-Mail Website
Guest Editor
Institute for Mathematics and Scientific Computing, Karl-Franzens-University Graz, Heinrichstr. 36, A-8010 Graz, Austria
Interests: many-core parallelization as on GPUs; fast optimization; adaptive multilevel methods in optimal shape design; parallel algorithms; domain decomposition methods; multilevel methods (a simple benchmark); algebraic multigrid; many-particle simulations; Eikonal solver; meshing
Prof. Dr. Alexander Ostermann
E-Mail Website
Guest Editor
Department of Mathematics, University of Innsbruck, Innrain 52, 6020 Innsbruck, Austria
Interests: numerical analysis; differential equations; engineering mathematics; geometry
Prof. Dr. Herbert Störi
E-Mail Website
Guest Editor
Vienna Scientific Cluster, Vienna, Austria
Interests: applications of plasma physics; characterisation of surfaces; tribology
Prof. Dr. Christoph Dellago
E-Mail Website
Guest Editor
Faculty of Physics, University of Vienna, Sensengasse 8/9, 1090 Vienna, Austria
Interests: computational statistical mechanics; molecular simulation; chaotic dynamics of classical many-particle systems; chemical reactions; behavior of nanoscale matter

Special Issue Information

Dear Colleagues,

The Special Issue will mainly consist of selected papers presented at “Austrian HPC Meeting 2020” (https://ahpc2020.ist.ac.at/). Papers considered to fit the scope of the journal and to be of sufficient quality after evaluation by the reviewers will be published free of charge.

High-performance computing (HPC) operates at the limits of computationally feasible problems, and helps to conquer new territories of science. Learning about current limitations and exchanging ideas on how to address these issues is key for the further development in scientific and technological competitiveness. This Austrian HPC Meeting will be an excellent opportunity to present and learn about the latest research results, and to exchange ideas between the users and providers of HPC resources.

Dr. Alois Schlögl
Prof. Dr. Ulrich Langer
Prof. Dr. Gundolf Haase
Prof. Dr. Alexander Ostermann
Prof. Dr. Herbert Störi
Prof. Dr. Christoph Dellago
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematical and Computational Applications is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (3 papers)

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Open AccessFeature PaperArticle
Parallel Matrix-Free Higher-Order Finite Element Solvers for Phase-Field Fracture Problems
Math. Comput. Appl. 2020, 25(3), 40; https://doi.org/10.3390/mca25030040 - 07 Jul 2020
Cited by 1 | Viewed by 629
Abstract
Phase-field fracture models lead to variational problems that can be written as a coupled variational equality and inequality system. Numerically, such problems can be treated with Galerkin finite elements and primal-dual active set methods. Specifically, low-order and high-order finite elements may be employed, [...] Read more.
Phase-field fracture models lead to variational problems that can be written as a coupled variational equality and inequality system. Numerically, such problems can be treated with Galerkin finite elements and primal-dual active set methods. Specifically, low-order and high-order finite elements may be employed, where, for the latter, only few studies exist to date. The most time-consuming part in the discrete version of the primal-dual active set (semi-smooth Newton) algorithm consists in the solutions of changing linear systems arising at each semi-smooth Newton step. We propose a new parallel matrix-free monolithic multigrid preconditioner for these systems. We provide two numerical tests, and discuss the performance of the parallel solver proposed in the paper. Furthermore, we compare our new preconditioner with a block-AMG preconditioner available in the literature. Full article
(This article belongs to the Special Issue High-Performance Computing 2020)
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Open AccessCommunication
CyVerse Austria—A Local, Collaborative Cyberinfrastructure
Math. Comput. Appl. 2020, 25(2), 38; https://doi.org/10.3390/mca25020038 - 24 Jun 2020
Viewed by 1053
Abstract
Life sciences (LS) are advanced in research data management, since LS have established disciplinary tools for data archiving as well as metadata standards for data reuse. However, there is a lack of tools supporting the active research process in terms of data management [...] Read more.
Life sciences (LS) are advanced in research data management, since LS have established disciplinary tools for data archiving as well as metadata standards for data reuse. However, there is a lack of tools supporting the active research process in terms of data management and data analytics. This leads to tedious and demanding work to ensure that research data before and after publication are FAIR (findable, accessible, interoperable and reusable) and that analyses are reproducible. The initiative CyVerse US from the University of Arizona, US, supports all processes from data generation, management, sharing and collaboration to analytics. Within the presented project, we deployed an independent instance of CyVerse in Graz, Austria (CAT) in frame of the BioTechMed association. CAT helped to enhance and simplify collaborations between the three main universities in Graz. Presuming steps were (i) creating a distributed computational and data management architecture (iRODS-based), (ii) identifying and incorporating relevant data from researchers in LS and (iii) identifying and hosting relevant tools, including analytics software to ensure reproducible analytics using Docker technology for the researchers taking part in the initiative. This initiative supports research-related processes, including data management and analytics for LS researchers. It also holds the potential to serve other disciplines and provides potential for Austrian universities to integrate their infrastructure in the European Open Science Cloud. Full article
(This article belongs to the Special Issue High-Performance Computing 2020)
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Open AccessProject Report
How Europe Is Preparing Its Core Solution for Exascale Machines and a Global, Sovereign, Advanced Computing Platform
Math. Comput. Appl. 2020, 25(3), 46; https://doi.org/10.3390/mca25030046 - 20 Jul 2020
Cited by 2 | Viewed by 1406
Abstract
In this paper, we present an overview of the European Processor Initiative (EPI), one of the cornerstones of the EuroHPC Joint Undertaking, a new European Union strategic entity focused on pooling the Union’s and national resources on HPC to acquire, build and deploy [...] Read more.
In this paper, we present an overview of the European Processor Initiative (EPI), one of the cornerstones of the EuroHPC Joint Undertaking, a new European Union strategic entity focused on pooling the Union’s and national resources on HPC to acquire, build and deploy the most powerful supercomputers in the world within Europe. EPI started its activities in December 2018. The first three years drew processor and platform designers, embedded software, middleware, applications and usage experts from 10 EU countries together to co-design Europe’s first HPC Systems on Chip and accelerators with its unique Common Platform (CP) technology. One of EPI’s core activities also takes place in the automotive sector, providing architectural solutions for a novel embedded high-performance computing (eHPC) platform and ensuring the overall economic viability of the initiative. Full article
(This article belongs to the Special Issue High-Performance Computing 2020)
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