Paper Info
Title
Specialising simulator generators for high-performance Monte-Carlo methods
Abstract
We address the tension between software generality and performance in the domain of simulations based on Monte-Carlo methods. We simultaneously achieve generality and high performance by a novel development methodology and software architecture centred around the concept of a specialising simulator generator. Our approach combines and extends methods from functional programming, generative programming, partial evaluation, and runtime code generation. We also show how to generate parallelised simulators. We evaluated our approach by implementing a simulator for advanced forms of polymerisation kinetics. We achieved unprecedented performance, making Monte-Carlo methods practically useful in an area that was previously dominated by deterministic PDE solvers. This is of high practical relevance, as Monte-Carlo simulations can provide detailed microscopic information that cannot be obtained with deterministic solvers.
Year
DOI
Venue
2008
10.1007/978-3-540-77442-6_9
PADL
Keywords
Field
DocType
generative programming,simulator generator,approach combine,high practical relevance,functional programming,deterministic pde solvers,high-performance monte-carlo method,high performance,monte-carlo method,deterministic solvers,unprecedented performance,monte-carlo simulation,code generation,generic programming,monte carlo simulation,software architecture,partial evaluation,kinetics,monte carlo method
Monte Carlo method,Functional programming,Simulation,Computer science,Partial evaluation,Theoretical computer science,Code generation,Software,Software architecture,Partial differential equation,Generality
Conference
Volume
ISSN
ISBN
4902
0302-9743
3-540-77441-6
Citations 
PageRank 
References 
2
0.37
10
Authors
5
Name
Order
Citations
PageRank
Gabriele Keller165736.02
Hugh Chaffey-Millar220.37
Manuel M. T. Chakravarty366641.89
Don Stewart41337.54
Christopher Barner-Kowollik520.37