Gate Cloud: An Integration of Gate Monte Carlo Simulation with a Cloud Computing Environment

Abstract

The GEANT4-based GATE is a unique and powerful Monte Carlo (MC) platform, which provides a single code library allowing the simulation of specific medical physics applications. However, this rigorous yet flexible platform is used only sparingly in the clinic due to its lengthy calculation time and significant computational overhead. By accessing the much more powerful computational resources of a cloud computing environment, GATE's run time can be significantly reduced to clinically feasible levels without the sizable investment of a local high performance cluster. This study investigated a reliable and efficient execution of GATE MC simulation using a commercial cloud computing services. A Monte Carlo cloud computing framework, Gate Cloud, for medical physics applications was proposed. Amazon's Elastic Compute Cloud (EC2) was used to launch several nodes equipped with GATE V6.1. The Positron emission tomography (PET) Benchmark included in the GATE software was repeated for various cluster sizes between 1 and 100 nodes in order to establish the ideal cluster size in terms of cost and time efficiency. The study shows that increasing the number of nodes in the cluster resulted in a decrease in calculation time that could be expressed with an inverse power model. Simulation results were not affected by the cluster size, indicating that integrity of a calculation is preserved in a cloud computing environment. With high power computing continuing to lower in price and accessibility, implementing Gate Cloud for clinical applications will continue to become more attractive.