sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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Using MuMMI to Model and Optimize Energy and Performance of HPC Applications on Power-Aware Supercomputers

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, Regular Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):Xingfu Wu, Valerie Taylor

ROOM:Level 4 - Lobby


The MuMMI (Multiple Metrics Modeling Infrastructure) facilitates systematic measurement, modeling, and prediction of performance and power consumption, and performance-power tradeoffs and optimization for Power-aware HPC systems. In this paper, we use the MuMMI to model performance and power. These models focus on four metrics: runtime, system power, CPU power and memory power. We rank the counters from these models to identify the most important counters for application optimization focus, then demonstrate the counter-guided optimizations with an aerospace application PMLB executed on two power-aware supercomputers, Mira at Argonne National Laboratory), and SystemG at Virginia Tech.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

Xingfu Wu - Texas A&M University

Valerie Taylor - Texas A&M University

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