From the December 2014 Issue
Computing Nash Equilibria in Bimatrix Games: GPU-Based Parallel Support Enumeration
By Safraz Rampersaud, Lena Mashayekhy, and Daniel Grosu
Computing Nash equilibria is a very important problem in strategic analysis of markets, conflicts, and resource allocation. Unfortunately, computing these equilibria even for moderately sized games is computationally expensive. To obtain lower execution times it is essential to exploit the parallel processing capabilities offered by the currently available massively parallel architectures. To address this issue, we design a GPU-based parallel support enumeration algorithm for computing Nash equilibria in bimatrix games. The algorithm is based on a new parallelization method which achieves high degrees of parallelism suitable for massively parallel GPU architectures. We perform extensive experiments to characterize the performance of the proposed algorithm. The algorithm achieves significant speedups relative to the OpenMP and MPI-based parallel implementations of the support enumeration method running on a cluster of multi-core computers.
Editorials and Announcements
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- State of the Journal (Jan 2014)
- Editor's Note: EIC Farewell and New EIC Introduction (Dec 2013)
- Editor's Note (Nov 2013)
- Editor's Note (Jan 2013)
- Editor's Note (April 2012)
- Editor's Note (January 2012)
- Editorial: Media Center (November 2011)
- Editor's Note: How to Write Research Articles in Computing and Engineering Disciplines by Ivan Stojmenovic
- Full Supplemental PDF of Editor's Note: How to Write Research Articles in Computing and Engineering Disciplines by Ivan Stojmenovic and Veljko Milutinovic (PDF)
- Special Issue on Trust, Security, and Privacy in Parallel and Distributed Systems (Feb 2014)
- Special Issue on Cloud Computing (June 2013)
- Special Issue on Cyber-Physical Systems (CPS) (Sept 2012)
- Special Section on Many-Task Computing (June 2011)
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IEEE Transactions on Parallel and Distributed Systems (TPDS) is a scholarly archival journal published monthly. Parallelism and distributed computing are foundational research and technology to rapidly advance computer systems and their applications.
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