Far East Journal of Theoretical Statistics
Volume 4, Issue 2, Pages 207 - 236
(December 2000)
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PARALLEL
COMPUTING AND MONTE CARLO ALGORITHMS
Jeffrey S. Rosenthal (Canada)
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Abstract: We argue that Monte Carlo algorithms are ideally
suited to parallel computing, and that “parallel
Monte Carlo” should be more widely used. We consider
a number of issues that arise, including dealing with
slow or unreliable computers. We also discuss the
possibilities of parallel Markov chain Monte Carlo. We
illustrate our results with actual computer
experiments. |
Keywords and phrases: parallel computing, distributed
computing, parallel Monte Carlo, Markov chain Monte
Carlo, Gibbs sampler, Metropolis-Hastings algorithm,
estimation. |
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