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Adaptive allocation of independent tasks to maximize throughput
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/2544
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| Title: | Adaptive allocation of independent tasks to maximize throughput |
| Authors: | Hong, Bo
Prasanna, Viktor K. |
| Keywords: | Task Allocation
Heterogeneous Computing
Network Flow
Decentralized Algorithm
Throughput |
| Issue Date: | Oct-2007 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Citation: | IEEE Transactions on Parallel And Distributed Systems, 18(10): pp. 1420-1435. |
| Abstract: | In this paper, we consider the task allocation problem for computing a large set of equal-sized independent tasks on a
heterogeneous computing system where the tasks initially reside on a single computer (the root) in the system. This problem
represents the computation paradigm for a wide range of applications such as SETI@home and Monte Carlo simulations. We consider
the scenario where the systems have a general graph-structured topology and the computers are capable of concurrent
communications and overlapping communications with computation. We show that the maximization of system throughput reduces to
a standard network flow problem. We then develop a decentralized adaptive algorithm that solves a relaxed form of the standard
network flow problem and maximizes the system throughput. This algorithm is then approximated by a simple decentralized protocol to
coordinate the resources adaptively. Simulations are conducted to verify the effectiveness of the proposed approach. For both
uniformly distributed and power law distributed systems, a close-to-optimal throughput is achieved, and improved performance over a
bandwidth-centric heuristic is observed. The adaptivity of the proposed approach is also verified through simulations. |
| URI: | http://dx.doi.org/10.1109/TPDS.2007.1042
http://hdl.handle.net/1860/2544 |
| Appears in Collections: | Faculty Research and Publications (ECE)
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