SU‐E‐T‐670: Toward Real‐Time Monte Carlo Simulation Using a Commercial Cloud Computing Infrastructure

Abstract

Purpose: Monte‐Carlo methods are the gold standard for modeling photon and electron transport in heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on‐demand from a third party, is a new practical approach for performing ultra‐fast Monte Carlo calculation in radiation therapy. Methods: We deployed the EGS5 Monte‐Carlo package in a commercial cloud environment. Launched from a single local computer with Internet access, a python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is distributed among independent worker nodes via the Message Passing Interface (MPI), and the results aggregated on the local computer for display and data analysis. Our novel approach is evaluated for pencil‐beams and broad beams of high‐energy electrons and photons. Results: The output of the cloud‐based Monte‐Carlo simulation is identical to that produced by the single‐threaded implementation. For 1 million electrons, a simulation that takes 2.58 hour on a local computer can be executed in 3.3 minutes on the cloud, a 47X speed‐up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Conclusion: Cloud computing is a promising platform for Monte Carlo simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, an abstraction that may change the way dose calculations are performed and radiation treatment plans are completed. Problems of a parallel nature can be solved efficiently using cloud computing.