Title
High-performance Physics Simulations Using Multi-core CPUs and GPGPUs in a Volunteer Computing Context
Abstract
This paper presents two conceptually simple methods for parallelizing a Parallel Tempering Monte Carlo simulation in a distributed volunteer computing context, where computers belonging to the general public are used. The first method uses conventional multi-threading. The second method uses CUDA, a graphics card computing system. Parallel Tempering is described, and challenges such as parallel random number generation and mapping of Monte Carlo chains to different threads are explained. While conventional multi-threading on central processing units is well-established, GPGPU programming techniques and technologies are still developing and present several challenges, such as the effective use of a relatively large number of threads. Having multiple chains in Parallel Tempering allows parallelization in a manner that is similar to the serial algorithm. Volunteer computing introduces important constraints to high performance computing, and we show that both versions of the application are able to adapt themselves to the varying and unpredictable computing resources of volunteersâ聙聶 computers, while leaving the machines responsive enough to use. We present experiments to show the scalable performance of these two approaches, and indicate that the efficiency of the methods increases with bigger problem sizes.
Year
DOI
Venue
2011
10.1177/1094342010372928
International Journal of High Performance Computing Applications
Keywords
DocType
Volume
high-performance physics,monte carlo chain,conceptually simple method,volunteer computing context,volunteer computing,parallel tempering monte carlo,multi-core cpus,high performance computing,conventional multi-threading,unpredictable computing resource,graphics card computing system,parallel tempering,cluster computing,monte carlo simulation,monte carlo
Journal
25
Issue
ISSN
Citations 
1
1094-3420
5
PageRank 
References 
Authors
1.13
3
3
Name
Order
Citations
PageRank
Kamran Karimi111817.23
Neil Dickson2636.72
Firas Hamze313114.05