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In this paper we present a workflow management system which permits the kinds of data-driven workflows required by urgent computing, namely where new data is integrated into the workflow as a disaster progresses in order refine the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-26 Gordon P. S. Gibb , Nick Brown , Rupert W , Nash , Miguel Mendes , Santiago Monedero , Humberto Díaz Fidalgo , Joaquín Ramírez Cisneros , Adrián Cardil , Max Kontak

Progress in science is deeply bound to the effective use of high-performance computing infrastructures and to the efficient extraction of knowledge from vast amounts of data. Such data comes from different sources that follow a cycle…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-15 Rosa M Badia , Jorge Ejarque , Francesc Lordan , Daniele Lezzi , Javier Conejero , Javier Álvarez Cid-Fuentes , Yolanda Becerra , Anna Queralt

The role of scalable high-performance workflows and flexible workflow management systems that can support multiple simulations will continue to increase in importance. For example, with the end of Dennard scaling, there is a need to…

Software Engineering · Computer Science 2017-10-19 Jay Jay Billings , Shantenu Jha

As a broader set of applications from simulations to data analysis and machine learning require more parallel computational capability, the demand for interactive and urgent high performance computing (HPC) continues to increase. This paper…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-29 Albert Reuther , Nick Brown , William Arndt , Johannes Blaschke , Christian Boehme , Antony Chazapis , Bjoern Enders , Robert Henschel , Julian Kunkel , Maxime Martinasso

Runtime scheduling and workflow systems are an increasingly popular algorithmic component in HPC because they allow full system utilization with relaxed synchronization requirements. There are so many special-purpose tools for task…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-03 David M. Rogers

Scientific workflow management systems support large-scale data analysis on cluster infrastructures. For this, they interact with resource managers which schedule workflow tasks onto cluster nodes. In addition to workflow task descriptions,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-30 Jonathan Bader , Kathleen West , Soeren Becker , Svetlana Kulagina , Fabian Lehmann , Lauritz Thamsen , Henning Meyerhenke , Odej Kao

The importance of workflows is highlighted by the fact that they have underpinned some of the most significant discoveries of the past decades. Many of these workflows have significant computational, storage, and communication demands, and…

The convergence of IoT, Edge, Cloud, and HPC technologies creates a compute continuum that merges cloud scalability and flexibility with HPC's computational power and specialized optimizations. However, integrating cloud and HPC resources…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-20 Aasish Kumar Sharma , Christian Boehme , Patrick Gelß , Ramin Yahyapour , Julian Kunkel

The ever-growing processing power of supercomputers in recent decades enables us to explore increasing complex scientific problems. Effective scheduling these jobs is crucial for individual job performance and system efficiency. The…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-21 Yuping Fan

Technological advances are creating exciting new opportunities that have the potential to move HPC well beyond traditional computational workloads. In this paper we focus on the potential for HPC to be instrumental in responding to…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-20 Nick Brown , Rupert Nash , Gordon Gibb , Bianca Prodan , Max Kontak , Vyacheslav Olshevsky , Wei Der Chien

Computer-based scientific experiments are becoming increasingly data-intensive, necessitating the use of High-Performance Computing (HPC) clusters to handle large scientific workflows. These workflows result in complex data and control…

Databases · Computer Science 2025-02-17 Zahra Sadeghibogar , Alessandro Berti , Marco Pegoraro , Wil M. P. van der Aalst

A workflow describes the entirety of processing steps in an analysis, such as employed in many fields of physics. Workflow management makes the dependencies between individual steps of a workflow and their computational requirements…

Data Analysis, Statistics and Probability · Physics 2023-09-15 Caspar Schmitt , Boyang Yu , Thomas Kuhr

This is a position paper, submitted to the Future Online Analysis Platform Workshop (https://press3.mcs.anl.gov/futureplatform/), which argues that simple data analysis applications are common today, but future online supercomputing…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-27 Justin M Wozniak , Jonathan Ozik , Daniel S. Katz , Michael Wilde

Running scientific workflows on a supercomputer can be a daunting task for a scientific domain specialist. Workflow management solutions (WMS) are a standard method for reducing the complexity of application deployment on high performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-30 Wouter Klijn , Sandra Diaz-Pier , Abigail Morrison , Alexander Peyser

The use of High Performance Computing (HPC) to compliment urgent decision making in the event of disasters is an important future potential use of supercomputers. However, the usage modes involved are rather different from how HPC has been…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-06 Gordon Gibb , Rupert Nash , Nick Brown , Bianca Prodan

Scientific workflows are powerful tools for management of scalable experiments, often composed of complex tasks running on distributed resources. Existing cyberinfrastructure provides components that can be utilized within repeatable…

Computers and Society · Computer Science 2019-03-05 Ilkay Altintas , Shweta Purawat , Daniel Crawl , Alok Singh , Kyle Marcus

Workflows are prevalent in today's computing infrastructures. The workflow model support various different domains, from machine learning to finance and from astronomy to chemistry. Different Quality-of-Service (QoS) requirements and other…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-04-22 Laurens Versluis , Alexandru Iosup

Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on workflows to orchestrate large and complex scientific experiments that range from execution of a…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-04-04 Rafael Ferreira da Silva , Rosa M. Badia , Venkat Bala , Debbie Bard , Peer-Timo Bremer , Ian Buckley , Silvina Caino-Lores , Kyle Chard , Carole Goble , Shantenu Jha , Daniel S. Katz , Daniel Laney , Manish Parashar , Frederic Suter , Nick Tyler , Thomas Uram , Ilkay Altintas , Stefan Andersson , William Arndt , Juan Aznar , Jonathan Bader , Bartosz Balis , Chris Blanton , Kelly Rosa Braghetto , Aharon Brodutch , Paul Brunk , Henri Casanova , Alba Cervera Lierta , Justin Chigu , Taina Coleman , Nick Collier , Iacopo Colonnelli , Frederik Coppens , Michael Crusoe , Will Cunningham , Bruno de Paula Kinoshita , Paolo Di Tommaso , Charles Doutriaux , Matthew Downton , Wael Elwasif , Bjoern Enders , Chris Erdmann , Thomas Fahringer , Ludmilla Figueiredo , Rosa Filgueira , Martin Foltin , Anne Fouilloux , Luiz Gadelha , Andy Gallo , Artur Garcia Saez , Daniel Garijo , Roman Gerlach , Ryan Grant , Samuel Grayson , Patricia Grubel , Johan Gustafsson , Valerie Hayot-Sasson , Oscar Hernandez , Marcus Hilbrich , AnnMary Justine , Ian Laflotte , Fabian Lehmann , Andre Luckow , Jakob Luettgau , Ketan Maheshwari , Motohiko Matsuda , Doriana Medic , Pete Mendygral , Marek Michalewicz , Jorji Nonaka , Maciej Pawlik , Loic Pottier , Line Pouchard , Mathias Putz , Santosh Kumar Radha , Lavanya Ramakrishnan , Sashko Ristov , Paul Romano , Daniel Rosendo , Martin Ruefenacht , Katarzyna Rycerz , Nishant Saurabh , Volodymyr Savchenko , Martin Schulz , Christine Simpson , Raul Sirvent , Tyler Skluzacek , Stian Soiland-Reyes , Renan Souza , Sreenivas Rangan Sukumar , Ziheng Sun , Alan Sussman , Douglas Thain , Mikhail Titov , Benjamin Tovar , Aalap Tripathy , Matteo Turilli , Bartosz Tuznik , Hubertus van Dam , Aurelio Vivas , Logan Ward , Patrick Widener , Sean Wilkinson , Justyna Zawalska , Mahnoor Zulfiqar
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