By Topic

Speed-up techniques for computation of Markov chain model to find an optimal batting order

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)

In this paper, we propose speed-up techniques for computation of the Markov chain model to find an optimal batting order in a baseball team. The proposed technique parallelizes computation of the Markov chain model for batting orders, where probabilities to obtain scores by the batting orders are computed using the D'Esopo and Lefkowitz model, on the grid. In addition, the proposed technique improves the performance by sharing parameters about batting orders. On a grid environment, load balancing is appropriately performed considering performances of computing resources. The experimental results show that the proposed technique finds the optimal batting order in 27,216,000 batting orders for 3,278 seconds on the Grid testbed

Published in:

Eighth International Conference on High-Performance Computing in Asia-Pacific Region (HPCASIA'05)

Date of Conference:

1-1 July 2005