Understanding Power and Energy Utilization in Large Scale Production Physics Simulation Codes
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arXiv
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| Hauptverfasser: | , , , , , , , , , , |
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| Format: | Preprint |
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2022
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| _version_ | 1866918107377827840 |
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| author | Bertsch, Adam Collette, Michael R. Dawson, Shawn A. Hammond, Si D. Karlin, Ian McKinley, M. Scott Pedretti, Kevin Rieben, Robert N. Ryujin, Brian S. Vargas, Arturo Weiss, Kenneth |
| author_facet | Bertsch, Adam Collette, Michael R. Dawson, Shawn A. Hammond, Si D. Karlin, Ian McKinley, M. Scott Pedretti, Kevin Rieben, Robert N. Ryujin, Brian S. Vargas, Arturo Weiss, Kenneth |
| contents | Power is an often-cited reason for the move to advanced architectures on the path to Exascale computing. This is due to practical considerations related to delivering enough power to successfully site and operate these machines, as well as concerns about energy usage while running large simulations. Since obtaining accurate power measurements can be challenging, it may be tempting to use the processor thermal design power (TDP) as a surrogate due to its simplicity and availability. However, TDP is not indicative of typical power usage while running simulations. Using commodity and advanced technology systems at Lawrence Livermore and Sandia National Labs, we performed a series of experiments to measure power and energy usage in running simulation codes. These experiments indicate that large scale Lawrence Livermore simulation codes are significantly more efficient than a simple processor TDP model might suggest. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2201_01278 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Understanding Power and Energy Utilization in Large Scale Production Physics Simulation Codes Bertsch, Adam Collette, Michael R. Dawson, Shawn A. Hammond, Si D. Karlin, Ian McKinley, M. Scott Pedretti, Kevin Rieben, Robert N. Ryujin, Brian S. Vargas, Arturo Weiss, Kenneth Distributed, Parallel, and Cluster Computing Power is an often-cited reason for the move to advanced architectures on the path to Exascale computing. This is due to practical considerations related to delivering enough power to successfully site and operate these machines, as well as concerns about energy usage while running large simulations. Since obtaining accurate power measurements can be challenging, it may be tempting to use the processor thermal design power (TDP) as a surrogate due to its simplicity and availability. However, TDP is not indicative of typical power usage while running simulations. Using commodity and advanced technology systems at Lawrence Livermore and Sandia National Labs, we performed a series of experiments to measure power and energy usage in running simulation codes. These experiments indicate that large scale Lawrence Livermore simulation codes are significantly more efficient than a simple processor TDP model might suggest. |
| title | Understanding Power and Energy Utilization in Large Scale Production Physics Simulation Codes |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2201.01278 |