Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Bader, Jonathan"'
Autor:
Lehmann, Fabian, Bader, Jonathan, De Mecquenem, Ninon, Wang, Xing, Bountris, Vasilis, Friederici, Florian, Leser, Ulf, Thamsen, Lauritz
Scientific workflows are used to analyze large amounts of data. These workflows comprise numerous tasks, many of which are executed repeatedly, running the same custom program on different inputs. Users specify resource allocations for each task, whi
Externí odkaz:
http://arxiv.org/abs/2408.00047
Autor:
Bader, Jonathan, Skalski, Fabian, Lehmann, Fabian, Scheinert, Dominik, Will, Jonathan, Thamsen, Lauritz, Kao, Odej
As the amount of available data continues to grow in fields as diverse as bioinformatics, physics, and remote sensing, the importance of scientific workflows in the design and implementation of reproducible data analysis pipelines increases. When dev
Externí odkaz:
http://arxiv.org/abs/2407.16353
With the increasing amount of data available to scientists in disciplines as diverse as bioinformatics, physics, and remote sensing, scientific workflow systems are becoming increasingly important for composing and executing scalable data analysis pi
Externí odkaz:
http://arxiv.org/abs/2311.08185
Publikováno v:
Future Generation Computer Systems, Volume 150, January 2024, Pages 171-185
Many resource management techniques for task scheduling, energy and carbon efficiency, and cost optimization in workflows rely on a-priori task runtime knowledge. Building runtime prediction models on historical data is often not feasible in practice
Externí odkaz:
http://arxiv.org/abs/2309.06918
Autor:
da Silva, Rafael Ferreira, Badia, Rosa M., Bala, Venkat, Bard, Debbie, Bremer, Peer-Timo, Buckley, Ian, Caino-Lores, Silvina, Chard, Kyle, Goble, Carole, Jha, Shantenu, Katz, Daniel S., Laney, Daniel, Parashar, Manish, Suter, Frederic, Tyler, Nick, Uram, Thomas, Altintas, Ilkay, Andersson, Stefan, Arndt, William, Aznar, Juan, Bader, Jonathan, Balis, Bartosz, Blanton, Chris, Braghetto, Kelly Rosa, Brodutch, Aharon, Brunk, Paul, Casanova, Henri, Lierta, Alba Cervera, Chigu, Justin, Coleman, Taina, Collier, Nick, Colonnelli, Iacopo, Coppens, Frederik, Crusoe, Michael, Cunningham, Will, Kinoshita, Bruno de Paula, Di Tommaso, Paolo, Doutriaux, Charles, Downton, Matthew, Elwasif, Wael, Enders, Bjoern, Erdmann, Chris, Fahringer, Thomas, Figueiredo, Ludmilla, Filgueira, Rosa, Foltin, Martin, Fouilloux, Anne, Gadelha, Luiz, Gallo, Andy, Saez, Artur Garcia, Garijo, Daniel, Gerlach, Roman, Grant, Ryan, Grayson, Samuel, Grubel, Patricia, Gustafsson, Johan, Hayot-Sasson, Valerie, Hernandez, Oscar, Hilbrich, Marcus, Justine, AnnMary, Laflotte, Ian, Lehmann, Fabian, Luckow, Andre, Luettgau, Jakob, Maheshwari, Ketan, Matsuda, Motohiko, Medic, Doriana, Mendygral, Pete, Michalewicz, Marek, Nonaka, Jorji, Pawlik, Maciej, Pottier, Loic, Pouchard, Line, Putz, Mathias, Radha, Santosh Kumar, Ramakrishnan, Lavanya, Ristov, Sashko, Romano, Paul, Rosendo, Daniel, Ruefenacht, Martin, Rycerz, Katarzyna, Saurabh, Nishant, Savchenko, Volodymyr, Schulz, Martin, Simpson, Christine, Sirvent, Raul, Skluzacek, Tyler, Soiland-Reyes, Stian, Souza, Renan, Sukumar, Sreenivas Rangan, Sun, Ziheng, Sussman, Alan, Thain, Douglas, Titov, Mikhail, Tovar, Benjamin, Tripathy, Aalap, Turilli, Matteo, Tuznik, Bartosz, van Dam, Hubertus, Vivas, Aurelio, Ward, Logan, Widener, Patrick, Wilkinson, Sean, Zawalska, Justyna, Zulfiqar, Mahnoor
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 cloud-based data
Externí odkaz:
http://arxiv.org/abs/2304.00019
Publikováno v:
2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
Scientific workflow management systems (SWMSs) and resource managers together ensure that tasks are scheduled on provisioned resources so that all dependencies are obeyed, and some optimization goal, such as makespan minimization, is achieved. In pra
Externí odkaz:
http://arxiv.org/abs/2302.07652
Autor:
Bader, Jonathan, Witzke, Joel, Becker, Soeren, Lößer, Ansgar, Lehmann, Fabian, Doehler, Leon, Vu, Anh Duc, Kao, Odej
Scientific workflows consist of thousands of highly parallelized tasks executed in a distributed environment involving many components. Automatic tracing and investigation of the components' and tasks' performance metrics, traces, and behavior are ne
Externí odkaz:
http://arxiv.org/abs/2211.12744
Scientific workflows are designed as directed acyclic graphs (DAGs) and consist of multiple dependent task definitions. They are executed over a large amount of data, often resulting in thousands of tasks with heterogeneous compute requirements and l
Externí odkaz:
http://arxiv.org/abs/2211.12076
Autor:
Scheinert, Dominik, Becker, Soeren, Bader, Jonathan, Thamsen, Lauritz, Will, Jonathan, Kao, Odej
Publikováno v:
IEEE BigData (2022) 209-216
Choosing a good resource configuration for big data analytics applications can be challenging, especially in cloud environments. Automated approaches are desirable as poor decisions can reduce performance and raise costs. The majority of existing aut
Externí odkaz:
http://arxiv.org/abs/2211.08227
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data) pp. 161-169
Selecting appropriate computational resources for data processing jobs on large clusters is difficult, even for expert users like data engineers. Inadequate choices can result in vastly increased costs, without significantly improving performance. On
Externí odkaz:
http://arxiv.org/abs/2211.04240