Programmable In Situ System for Iterative Workflows
| LNCS: | Lecture Notes in Computer Science (LNCS), vol. 10773, pages 122–131, 2018. |
| JSSPP: | Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing (JSSPP), 2017. |
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LNCS |
| DOI: | 10.1007/978-3-319-77398-8_7 |
Abstract
We describe an in situ system for solving iterative problems. We specifically target inverse problems, where expensive simulations are approximated using a surrogate model. The model explores the parameter space of the simulation through iterative trials, each of which becomes a job managed by a parallel scheduler. Our work extends Henson [1], a cooperative multi-tasking system for in situ execution of loosely coupled codes.
We describe an in situ system for solving iterative problems. We specifically target inverse problems, where expensive simulations are approximated using a surrogate model. The model explores the parameter space of the simulation through iterative trials, each of which becomes a job managed by a parallel scheduler. Our work extends Henson [1], a cooperative multi-tasking system for in situ execution of loosely coupled codes.
References
[1]
D. Morozov and Z. Lukic. Master of Puppets: Cooperative Multitasking for In Situ Processing. Proceedings of the Symposium on High-Performance Parallel and Distributed Computing (HPDC), pages 285-288, 2016.