simulation research group a controller for distributed discrete-event simulation: akaroa2 group...
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![Page 1: Simulation Research Group A Controller for Distributed Discrete-Event Simulation: Akaroa2 Group Leaders: Krys Pawlikowski 1, Don McNickle 2, Greg Ewing](https://reader035.vdocuments.mx/reader035/viewer/2022072015/56649ebb5503460f94bc3014/html5/thumbnails/1.jpg)
Simulation Research GroupA Controller for Distributed Discrete-Event Simulation: Akaroa2
Group Leaders:
Krys Pawlikowski1, Don McNickle2, Greg Ewing1
1 Department of Computer Science and Software Engineering 2 Department of Management
Group Members:
Will Gittoes, Yumi Masuri, Adriaan Schmidt, Mirko Eickhoff
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Distributed Discrete-Event Simulation
Two Different Approaches:
• Break problem up into bits that can (nearly) be done in parallel – e.g. Timewarp
• Difficult to do, high communication costs, modest speed-up
• Speed up simulation by launching multiple replications in parallel – e.g. Akaroa2
• Easy to launch multiple replications, low communication cost, nearly linear speed-up
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Akaroa2
• Launches identical replications of a simulation on a network
• Written in C++, works under most OS
• Only one extra line in the simulation program required
• User specifies the level of accuracy required, then the simulation runs until that is achieved
• Downloaded 1700 times from www.akaroa.canterbury.ac.nz
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Akaroa2 on PlanetLab
Simulating this problem
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Problems that Akaroa2 addresses
Problems Solutions
Speed Even simple systems may
need millions of events
Appropriate Accuracy for Decision-Making
Runs are either wastefully long, or not accurate enough
Multiple replications in parallel
Automated run-length control
Automated statistical analysis of results
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Akaroa2: Architecture
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Akaroa2: Interface
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Akaroa2: Features
• Indifferent to fast or slow processors
• High fault tolerance: A dead processor is no different to a slow one
• Nearly linear speed-up: n processors produce results in 1/n of the time
• Extensively tested simulation features: RNG’s, transient analysis, confidence interval estimation
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Akaroa2: Use on PlanetLab
• Requires very low bandwidth
• After set-up the communication is entirely one way and does not need acknowledgement
• In principle can be distributed over any set of hosts on the Internet – e.g. PlanetLab
No difference in simulation speed
Distributing Akaroa2 on PlanetLab Farzana, Ewing, Pawlikowski, Yamada, 2009
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Extension to Other Data Streams
Much of the expertise built up over the last 20 years with Akaroa2 can be transferred to non-simulation data:
• A reliable, fault-tolerant architecture
• Analysis of streams of data from multiple sources
• Analysis methods for correlated streams of data