Paper Info
Title
Transparent and adaptive computation-block caching for agent-based simulation on a PDES core
Abstract
We present adaptive computation-block caching that supports improved performance and is suited for agent-based simulations. The approach is illustrated in SASSY (scalable agents simulation system). SASSY leverages a parallel discrete event simulation for performance, but provides an agent-based API to the developer. Agent-based simulation is suited to computation-block caching because relevant calculations completed at each event may be relatively heavyweight and may be repeated. The potential savings of avoiding a computation entirely may offset the overhead cost of caching. The approach is refined through the use of statistical methods for choosing which computation blocks should be cached or not. If the relevant computation is trivial, caching is not worth the cost. In other cases caching provides a substantial speedup. Our mechanism tracks these costs online and adjusts accordingly. It requires no additional coding but is automatically integrated into applications. We assess the performance of the approach in a benchmark-application.
Year
DOI
Venue
2008
10.1109/WSC.2008.4736149
Winter Simulation Conference
Keywords
Field
DocType
overhead cost,statistical methods,application program interfaces,discrete event simulation,cache storage,pdes core,multi-agent systems,relevant calculation,agent-based api,scalable agents simulation system,computation block,adaptive computation-block caching,agent-based simulation,cases caching,relevant computation,parallel discrete event simulation,simulation,mean squared error,multi agent systems
Cache,Simulation,Computer science,Parallel computing,Coding (social sciences),Multi-agent system,Offset (computer science),Speedup,Discrete event simulation,Scalability,Computation
Conference
ISBN
Citations 
PageRank 
978-1-4244-2708-6
0
0.34
References 
Authors
12
3
Name
Order
Citations
PageRank
Yin Xiong1281.72
Maria Hybinette245941.13
Eileen Kraemer355065.47