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Monte Carlo modeling of linear accelerator using distributed computing.

Sotirios Stathakis1, Federico Balbi, Anthony T Chronopoulos

  • 1University of Texas Health Science Center San Antonio, San Antonio, TX 78229, USA.

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Summary
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Distributed computing with EGSnrc Monte Carlo on a computer cluster shows nearly linear performance scaling. This approach efficiently simulates complex radiotherapy treatments, maintaining statistical accuracy across multiple nodes.

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Area of Science:

  • Medical Physics
  • Computational Science
  • Radiotherapy Physics

Background:

  • Monte Carlo simulations are crucial for accurate radiotherapy dose calculations.
  • High-performance computing is needed to handle complex treatment geometries and large numbers of histories.
  • Distributed computing offers a potential solution for accelerating these computationally intensive tasks.

Purpose of the Study:

  • To investigate and test the distributed computing implementation of the EGSnrc Monte Carlo system using a computer cluster.
  • To assess the computational performance and efficiency of the EGSnrc system when run on a cluster.

Main Methods:

  • Tested computational performance across various scenarios with differing numbers of computers.
  • Included detailed linac head modeling (MLC geometry, stereotactic radiosurgery cones).
  • Simulated radiation transport and dose computation in water phantoms and patient geometries.

Main Results:

  • Simulations in the cluster environment maintained the same total number of histories as single-computer simulations.
  • Achieved identical statistical uncertainty across all tested scenarios, regardless of computer count.
  • Demonstrated near-linear performance scaling with an increasing number of computers.

Conclusions:

  • The distributed EGSnrc implementation on a computer cluster is effective and efficient.
  • The approach offers significant speed-up for complex Monte Carlo simulations in radiotherapy.
  • This method enables faster and more accurate dose calculations for clinical applications.