Abstract
Successful simulations for scientific discovery on high-performance computing platforms require careful planning, including verification of specific application configuration and runtime parameters, estimation of resource requirements, and steering and monitoring of the simulation. However, simulation planning is an aspect of scientific computing that is extremely sparse in available literature or training. In this paper we focus on the resource management aspect of such planning through formulation of a component-based cost model. We illustrate the methodology and formulation through FLASH, a highly configurable simulation code used in multiple scientific domains.
| Original language | English |
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| Title of host publication | Proceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 683-688 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728135106 |
| DOIs | |
| State | Published - May 2019 |
| Event | 33rd IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019 - Rio de Janeiro, Brazil Duration: May 20 2019 → May 24 2019 |
Publication series
| Name | Proceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019 |
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Conference
| Conference | 33rd IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019 |
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| Country/Territory | Brazil |
| City | Rio de Janeiro |
| Period | 05/20/19 → 05/24/19 |
Funding
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research and Office of Nuclear Physics, Scientific Discovery through Advanced Computing (SciDAC) program. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.
Keywords
- Application configuration
- Cost model
- Scientific computing
- Simulation planning