Applying Graph Partitioning Methods in Measurement-Based Dynamic Load Balancing

Technical Report · Mon Feb 27 04:00:00 EST 2012

DOI:https://doi.org/10.2172/1093410· OSTI ID:1093410

Bhatele, Abhinav ^[1]; Fourestier, Sebastien ^[1]; Menon, Harshitha ^[1]; Kale, Laxmikant V. ^[1]; Pellegrini, Francois ^[1]

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1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Load imbalance can lead to wasted CPU hours especially when running on a large number of processors. Achieving the best parallel efficiency for a program requires optimal load balancing which is a NP-hard problem. Charm++, a migratable objects based programming model, provides a measurement-based dynamic load balancing frame work. This paper explores the use of graph partitioning algorithms, traditionally used for partitioning physical domains/meshes, for measurement based dynamic load balancing of parallel applications. In particular, we present repartitioning methods developed in a graph partitioning toolbox called Scotch that consider the previous mapping to minimize migration costs. We also discuss a new imbalance reduction algorithm for graphs with irregular load distributions. We compare several load balancing algorithms using a micro-benchmark and the NAS BT multi-zone bench mark. New algorithms developed in Scotch lead to better performance compared to other existing partitioners, both in terms of the application execution time and fewer number of objects migrated.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: W-7405-ENG-48
• OSTI ID: 1093410
• Report Number(s): LLNL-TR--532851
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
Dynamic
Graph Partitioning
Performance
load Balancing