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Distributed adaptive task allocation in heterogeneous computing environments to maximize throughput

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2 Author(s)
B. Hong ; Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA ; V. K. Prasanna

Summary form only given. We consider the task allocation problem for computing a large set of equal-sized independent tasks on heterogeneous computing systems. This problem represents the computation paradigm for a wide range of applications such as SETl@home and Monte Carlo simulations. We consider a general problem in which the interconnection between the nodes is modeled using a graph. We maximize the throughput of the system by using an extended network flow representation. We then develop a decentralized adaptive algorithm. This algorithm leads to a simple decentralized protocol that coordinates the resources in the system. The effectiveness of the proposed task allocation approach is verified through simulations.

Published in:

Parallel and Distributed Processing Symposium, 2004. Proceedings. 18th International

Date of Conference:

26-30 April 2004