Scheduling across Multiple Applications using Task-Based Programming Models
Task-based programming models have shown their potential for efficiency and scalability in parallel and distributed systems. With such a model, a parallel application is broken down into a graph of tasks, which are subsequently scheduled for execution. Recently, implementations of task-based models...
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| Published in: | 2020 IEEE/ACM Fourth Annual Workshop on Emerging Parallel and Distributed Runtime Systems and Middleware (IPDRM) pp. 1 - 8 |
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| Main Authors: | , , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
01.11.2020
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| Abstract | Task-based programming models have shown their potential for efficiency and scalability in parallel and distributed systems. With such a model, a parallel application is broken down into a graph of tasks, which are subsequently scheduled for execution. Recently, implementations of task-based models have addressed distributed memory and heterogeneous systems with accelerators. However, the problem of scheduling tasks as well as allocating resources at runtime is still a challenge. In this paper, we propose coordinated and cooperative task scheduling across multiple applications. The main idea is to exploit the application's idle time e.g. from imbalance to serve tasks from another application. The experiments use Chameleon, a task-based framework for reactive tasking in distributed memory systems. In various example scenarios, we show improvements in CPU utilization of 5% - 15% by coordinated scheduling. |
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| AbstractList | Task-based programming models have shown their potential for efficiency and scalability in parallel and distributed systems. With such a model, a parallel application is broken down into a graph of tasks, which are subsequently scheduled for execution. Recently, implementations of task-based models have addressed distributed memory and heterogeneous systems with accelerators. However, the problem of scheduling tasks as well as allocating resources at runtime is still a challenge. In this paper, we propose coordinated and cooperative task scheduling across multiple applications. The main idea is to exploit the application's idle time e.g. from imbalance to serve tasks from another application. The experiments use Chameleon, a task-based framework for reactive tasking in distributed memory systems. In various example scenarios, we show improvements in CPU utilization of 5% - 15% by coordinated scheduling. |
| Author | Samfass, Philipp Fuerlinger, Karl Chung, Minh Thanh Weidendorfer, Josef Kranzlmuller, Dieter |
| Author_xml | – sequence: 1 givenname: Minh Thanh surname: Chung fullname: Chung, Minh Thanh email: minh.thanh.chung@ifi.lmu.de organization: MNM-Team, Ludwig-Maximilians-Universitaet,Munich,Germany – sequence: 2 givenname: Josef surname: Weidendorfer fullname: Weidendorfer, Josef email: josef.weidendorfer@lrz.de organization: Leibniz Supercomputing Centre (LRZ),Garching,Germany – sequence: 3 givenname: Philipp surname: Samfass fullname: Samfass, Philipp email: samfass@in.tum.de organization: Technical University of Munich,Department of Informatics – sequence: 4 givenname: Karl surname: Fuerlinger fullname: Fuerlinger, Karl email: karl.fuerlinger@ifi.lmu.de organization: MNM-Team, Ludwig-Maximilians-Universitaet,Munich,Germany – sequence: 5 givenname: Dieter surname: Kranzlmuller fullname: Kranzlmuller, Dieter email: kranzlmueller@ifi.lmu.de organization: MNM-Team, Ludwig-Maximilians-Universitaet Leibniz Supercomputing Centre (LRZ),Munich,Germany |
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| PublicationTitle | 2020 IEEE/ACM Fourth Annual Workshop on Emerging Parallel and Distributed Runtime Systems and Middleware (IPDRM) |
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| Snippet | Task-based programming models have shown their potential for efficiency and scalability in parallel and distributed systems. With such a model, a parallel... |
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| SubjectTerms | cooperative task scheduling coordinated scheduling distributed memory systems distributed system Libraries parallel application parallel distributed systems parallel programming Programming reactive tasking resource allocation resource management Runtime scheduling scheduling tasks Synchronization task analysis task migration task-based framework task-based models task-based programming model task-based programming models |
| Title | Scheduling across Multiple Applications using Task-Based Programming Models |
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