Journal Article
. 2004 Jul; 75(3):251-8.
doi: 10.1016/j.cmpb.2004.02.003.

Simulation of emission tomography using grid middleware for distributed computing

M G Thomason 1 R F Longton  J Gregor  G T Smith  R K Hutson  
  • PMID: 15265623
  •     2 citations


SimSET is Monte Carlo simulation software for emission tomography. This paper describes a simple but effective scheme for parallel execution of SimSET using NetSolve, a client-server system for distributed computation. NetSolve (version 1.4.1) is "grid middleware" which enables a user (the client) to run specific computations remotely and simultaneously on a grid of networked computers (the servers). Since the servers do not have to be identical machines, computation may take place in a heterogeneous environment. To take advantage of diversity in machines and their workloads, a client-side scheduler was implemented for the Monte Carlo simulation. The scheduler partitions the total decay events by taking into account the inherent compute-speeds and recent average workloads, i.e., the scheduler assigns more decay events to processors expected to give faster service and fewer decay events to those expected to give slower service. When compute-speeds and sustained workloads are taken into account, the speed-up is essentially linear in the number of equivalent "maximum-service" processors. One modification in the SimSET code (version was made to ensure that the total number of decay events specified by the user is maintained in the distributed simulation. No other modifications in the standard SimSET code were made. Each processor runs complete SimSET code for its assignment of decay events, independently of others running simultaneously. Empirical results are reported for simulation of a clinical-quality lung perfusion study.

Execution of the SimSET Monte Carlo PET/SPECT simulator in the condor distributed computing environment.
Karl G Baum, María Helguera.
J Digit Imaging, 2007 Aug 11; 20 Suppl 1. PMID: 17690935    Free PMC article.
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Klaus Kayser, Jürgen Görtler, Stephan Borkenfeld, Gian Kayser.
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