Name
Abstract | ||
|---|---|---|
In the age of exascale computing, it is crucial to provide the best possible performance under power constraints. A major part of this optimization is managing power and bandwidth intelligently in a cluster to maximize performance. There are significant improvements in the power efficiency of HPC runtimes, yet little work has explored our ability to determine the theoretical optimal performance under a give power and bandwidth bound. In this paper, we present a scalable model to identify the optimal power and bandwidth distribution such that the makespan of a program is minimized. We utilize the network flow formulation in constructing a linear program that is efficient to solve. We demonstrate the applicability of the model to MPI programs and provide synthetic benchmarks on the performance of the model.
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Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3149412.3149422 | E2SC@SC |
Field | DocType | ISBN |
Flow network,Electrical efficiency,Exascale computing,Job shop scheduling,Computer science,Parallel computing,Real-time computing,Bandwidth (signal processing),Linear programming,Scalability,Bounding overwatch,Distributed computing | Conference | 978-1-4503-5132-4 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramy Medhat | 1 | 38 | 4.55 |
| Shelby Funk | 2 | 348 | 23.89 |
| Barry Rountree | 3 | 1013 | 51.24 |