10414

Dynamic Load Balancing on Massively Parallel Computer Architectures

Florian Wende
Freie Universitat Berlin
Konrad-Zuse-Zentrum fur Informationstechnik Berlin, 2013
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This thesis reports on using dynamic load balancing methods on massively parallel computers in the context of multi-threaded computations. In particular we investigate the applicability of a randomized work stealing algorithm to ray tracing and breadth-first search as representatives of real-world applications with dynamic work creation. For our considerations we made use of current massively parallel hardware accelerators: Nvidia Tesla M2090, and Intel Xeon Phi. For both of the two we demonstrate the suitability of the work stealing scheme for the said real-world applications. Also the necessity of dynamic load balancing for irregular computations on such hardware is illustrated.
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