Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure

Abstract

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a 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 approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC 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 then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

FIG. 1

Schematic of a high level view of the cloud-based MC computing. A Python script is executed on a local computer to allocate via the Internet one master node and a chosen number of worker nodes. Each worker node simulates a chosen number of particles independently and the final result is transferred to the local client computer.

FIG. 2

Percentage depth dose curves for pencil beam electrons (left) and photons (middle) of varying energies. Lateral dose profiles for a 10cm×10cm 20 MeV electron field at three depths are plotted in the right panel.

FIG. 5

Time versus number of EC2 nodes for 10,000 particles, 20 MeV electrons.