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  1. Proceedings of the 2010 Workshop on Parallel Programming Patterns (ParaPLoP '10)
  2. Monte Carlo methods: a computational pattern for our pattern language
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Monte Carlo methods: a computational pattern for our pattern language

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Monte Carlo methods: a computational pattern for our pattern language

Content Provider ACM Digital Library
Author Chong, Jike Keutzer, Kurt Gonina, Ekaterina
Abstract The Monte Carlo methods are an important set of algorithms in computer science. They involve estimating results by statistically sampling a parameter space with a thousands to millions of experiments. The algorithm requires a small set of parameters as input, with which it generates a large amount of computation, and outputs a concise set of aggregated results. The large amount of computation has many independent component with obvious boundaries for parallelization. While the algorithm is well-suited for executing on a highly parallel computing platform, there still exist many challenges such as: selecting a suitable random number generator with the appropriate statistical and computational properties, selecting a suitable distribution conversion method that preserves the statistical properties of the random sequences, leveraging the right abstraction for the computation in the experiments, and designing the an efficient data structures for a particular data working set. This paper presents the Monte Carlo Methods software programming pattern and focuses on the numerical, task, and data perspectives to guide software developers in constructing efficient implementations of applications based on Monte Carlo methods.
Starting Page 1
Ending Page 10
Page Count 10
File Format PDF
ISBN 9781450301275
DOI 10.1145/1953611.1953626
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-03-30
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Monte carlo methods Software patterns Random number generators Computational pattern Parallelization
Content Type Text
Resource Type Article
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