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# MCSL Monte Carlo simulation language - PowerPoint PPT Presentation

MCSL Monte Carlo simulation language. Diego Garcia Eita Shuto Yunling Wang Chong Zhai. Outline of Presentation. Introduction of language Language tutorial and examples Architectural design and implementation Summary and lessons learned. Monte Carlo methods.

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### MCSLMonte Carlo simulation language

Diego Garcia

Eita Shuto

Yunling Wang

Chong Zhai

• Introduction of language

• Language tutorial and examples

• Architectural design and implementation

• Summary and lessons learned

• a class of computational algorithms that rely on repeated random sampling to compute their results.

• Why interested with it?

• widely used

• good performance

• possibly the only

• efficient approach

• Physics

• high energy particle physics, quantum many-body problem, transportation theory

• Mathematics

• Integration, Optimization, Inverse problems, Computational mathematics

• Computer science

• Las Vegas algorithm, LURCH, Computer Go, General Game Playing

• Finance

• Option, instrument, portfolio or investment

• Generation particular distributed psedu-random numbers (or low discrepancy sequence)

• Evaluate the function by sampling with these numbers

• Aggregate results! (weight might be counted, variational method or conditional acceptance might be considered)

• Fast Random number algorithm (with good performance also)

• Other than iteration, consider all samples as a single vector

• Built-in Function to simplify aggregate process with different conditioning.

Example One Calculation of “π” =3.14159265358979323846…

Example 2-Pollard'srho algorithm

• Teamwork and effective project management

• Incremental Development Approach

• 1

• 2

• 3

• 4

• MCSL Team

• Columbia University

• Dec 19th, 2008