NDLI: Application Runtime Variability and Power Optimization for Exascale Computers

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Application Runtime Variability and Power Optimization for Exascale Computers

Content Provider	ACM Digital Library
Author	Deb, Diptorup Lewis, Rob Bhalachandra, Sridutt Porterfield, Allan Rountree, Barry Fowler, Rob
Abstract	Exascale computing will be as much about solving problems with the least power/energy as about solving them quickly. In the future, systems are likely to be over-provisioned with processors and will rely on hardware-enforced power bounds to allow operation within power budget/thermal design limits. Variability in High Performance Computing (HPC) makes scheduling and application optimization difficult. For three HPC applications - ADCIRC, WRF and LQCD, we show the effects of heterogeneity on run-to-run execution consistency (with and without a power limit applied). A 4% hardware run-to-run variation is seen in case of a perfectly balanced compute-bound application, while up to 6% variation was observed for an application with minor load imbalances. A simple model based on Dynamic Duty Cycle Modulation (DDCM) is introduced. The model was implemented within the MPI profiling interface for collective operations and used in conjunction with the three applications without source code changes. Energy savings of over 10% are obtained for ADCIRC with only a 1--3% slowdown. With a power limit in place, the energy saving is partially translated to performance improvement. With a power limit of 50W, one version of the model executes 3% faster while saving 6% in energy, and a second version executes 1% faster while saving over 10% energy.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781450336062
DOI	10.1145/2768405.2768408
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-06-16
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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