Reducing the run-time of MCMC programs by multithreading on SMP architectures

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Reducing the run-time of MCMC programs by multithreading on SMP architectures. / Byrd, Jonathan M.R.; Jarvis, Stephen A.; Bhalerao, Abhir H.

IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM. 2008. 4536354 (IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Byrd, JMR, Jarvis, SA & Bhalerao, AH 2008, Reducing the run-time of MCMC programs by multithreading on SMP architectures. in IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM., 4536354, IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM, IPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium, Miami, FL, United States, 14/04/08. https://doi.org/10.1109/IPDPS.2008.4536354

APA

Byrd, J. M. R., Jarvis, S. A., & Bhalerao, A. H. (2008). Reducing the run-time of MCMC programs by multithreading on SMP architectures. In IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM [4536354] (IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM). https://doi.org/10.1109/IPDPS.2008.4536354

Vancouver

Byrd JMR, Jarvis SA, Bhalerao AH. Reducing the run-time of MCMC programs by multithreading on SMP architectures. In IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM. 2008. 4536354. (IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM). https://doi.org/10.1109/IPDPS.2008.4536354

Author

Byrd, Jonathan M.R. ; Jarvis, Stephen A. ; Bhalerao, Abhir H. / Reducing the run-time of MCMC programs by multithreading on SMP architectures. IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM. 2008. (IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM).

Bibtex

@inproceedings{9502dd1e819f4a60a99279a8b6cd22f5,
title = "Reducing the run-time of MCMC programs by multithreading on SMP architectures",
abstract = "The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As suchMCMC has found a wide variety of applications in fields including computational biology and physics, financial econometrics, machine learning and image processing. This paper presents a new method for reducing the runtime of Markov Chain Monte Carlo simulations by using SMP machines to speculatively perform iterations in parallel, reducing the runtime of MCMC programs whilst producing statistically identical results to conventional sequential implementations. We calculate the theoretical reduction in runtime that may be achieved using our technique under perfect conditions, and test and compare the method on a selection of multi-core and multi-processor architectures. Experiments are presented that show reductions in runtime of 35% using two cores and 55% using four cores.",
author = "Byrd, {Jonathan M.R.} and Jarvis, {Stephen A.} and Bhalerao, {Abhir H.}",
year = "2008",
doi = "10.1109/IPDPS.2008.4536354",
language = "English",
isbn = "9781424416943",
series = "IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM",
booktitle = "IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM",
note = "IPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium ; Conference date: 14-04-2008 Through 18-04-2008",

}

RIS

TY - GEN

T1 - Reducing the run-time of MCMC programs by multithreading on SMP architectures

AU - Byrd, Jonathan M.R.

AU - Jarvis, Stephen A.

AU - Bhalerao, Abhir H.

PY - 2008

Y1 - 2008

N2 - The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As suchMCMC has found a wide variety of applications in fields including computational biology and physics, financial econometrics, machine learning and image processing. This paper presents a new method for reducing the runtime of Markov Chain Monte Carlo simulations by using SMP machines to speculatively perform iterations in parallel, reducing the runtime of MCMC programs whilst producing statistically identical results to conventional sequential implementations. We calculate the theoretical reduction in runtime that may be achieved using our technique under perfect conditions, and test and compare the method on a selection of multi-core and multi-processor architectures. Experiments are presented that show reductions in runtime of 35% using two cores and 55% using four cores.

AB - The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As suchMCMC has found a wide variety of applications in fields including computational biology and physics, financial econometrics, machine learning and image processing. This paper presents a new method for reducing the runtime of Markov Chain Monte Carlo simulations by using SMP machines to speculatively perform iterations in parallel, reducing the runtime of MCMC programs whilst producing statistically identical results to conventional sequential implementations. We calculate the theoretical reduction in runtime that may be achieved using our technique under perfect conditions, and test and compare the method on a selection of multi-core and multi-processor architectures. Experiments are presented that show reductions in runtime of 35% using two cores and 55% using four cores.

UR - http://www.scopus.com/inward/record.url?scp=51049124313&partnerID=8YFLogxK

U2 - 10.1109/IPDPS.2008.4536354

DO - 10.1109/IPDPS.2008.4536354

M3 - Conference contribution

AN - SCOPUS:51049124313

SN - 9781424416943

T3 - IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM

BT - IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM

T2 - IPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium

Y2 - 14 April 2008 through 18 April 2008

ER -