SCHEDULE: NOV 16-22, 2013

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A Distributed Dynamic Load Balancer for Iterative Applications

SESSION: Load Balancing

EVENT TYPE: Papers, Awards, Best Student Paper Finalists

TIME: 2:30PM - 3:00PM

SESSION CHAIR: Sriram Krishnamoorthy

AUTHOR(S):Harshitha Menon, Laxmikant Kale

ROOM:405/406/407

ABSTRACT:
For many applications, computation load varies over time. Such applications require dynamic load balancing to improve performance. Centralized load balancing schemes, which perform the load balancing decisions at a central location, are not scalable. In contrast, fully distributed strategies are scalable but typically do not produce a balanced work distribution as they tend to consider only local information. This paper describes a fully distributed algorithm for load balancing that uses partial information about the global state of the system to perform load balancing. This algorithm, referred to as GrapevineLB, consists of two stages: global information propagation using a lightweight algorithm inspired by epidemic algorithms, and work unit transfer using a randomized algorithm. We provide analysis of the algorithm along with detailed simulation and performance comparison with other load balancing strategies. We demonstrate the effectiveness of GrapevineLB for adaptive mesh refinement and molecular dynamics on up to 131,072 cores of BlueGene/Q.

Chair/Author Details:

Sriram Krishnamoorthy (Chair) - Pacific Northwest National Laboratory

Harshitha Menon - University of Illinois at Urbana-Champaign

Laxmikant Kale - University of Illinois at Urbana-Champaign

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The full paper can be found in the ACM Digital Library