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Parallel random number generations for Monte Carlo simulation

Published: 24 March 2011 Publication History

Abstract

Modeling and simulation has been popularly used to explain complex phenomena or find knowledge in many areas such as science and engineering, business and economics, and social science. Monte Carlo simulation has been popularly used in modeling and simulation, and generating a sequence of random numbers has been at the center of Monte Carlo simulation. With the advent of parallel computing architecture, parallel modeling and simulation has been popular in many areas and many researches have been done to generate a sequence of random numbers in parallel computing environment. In this paper, we are proposing a framework to generate a sequence of random numbers in parallel and showing the usage of the framework in financial applications.

References

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A. G. Ananth Grama and G. Karypis. Introduction to Parallel Computing, Addison-Wesley Publishing Company, 2005.
[2]
J. Halton. A retrospective and prospective survey of the Monte-Carlo method. SIAM Review, 12:1--63, 1970.
[3]
D. Higham. Black-Scholes option valuation for scientific computing students. Computing in Science and Engineering, 6(6):72--79, 2004.
[4]
D. Knuth. The Art of Computer Programming, Vol2. Seminumerical Algorithms. Addison-Wesley Publishing Company, 1981.
[5]
M. Mascagi and A. Srinivasan. Algorithm 806: Sprng" A scalable library for pseudorandom number generation. ACM Transactions on Mathematical Software, 26:436--461, 2000.
[6]
M. Mascagni. Parallel pseudorandom number generation. SIAM News, 32:5, 1999.

Cited By

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  • (2016)Cryptographic Key Extraction from MusicAdvances in Computational Intelligence10.1007/978-981-10-2525-9_30(309-317)Online publication date: 9-Nov-2016

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Published In

cover image ACM Conferences
ACMSE '11: Proceedings of the 49th annual ACM Southeast Conference
March 2011
399 pages
ISBN:9781450306867
DOI:10.1145/2016039
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 March 2011

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Author Tags

  1. option pricing
  2. parallel algorithm
  3. random number generator

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ACM SE '11
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ACM SE '11: ACM Southeast Regional Conference
March 24 - 26, 2011
Georgia, Kennesaw

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Overall Acceptance Rate 502 of 1,023 submissions, 49%

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Cited By

View all
  • (2016)Cryptographic Key Extraction from MusicAdvances in Computational Intelligence10.1007/978-981-10-2525-9_30(309-317)Online publication date: 9-Nov-2016

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