Agent-based simulation (ABS) systems are increasingly being used to solve a wide-array of problems in business, telecommunications, robotics, games, and military applications. ABS modelers face two challenges: First, performance is affected, as their simulations become more complex and larger scale; and second, development is difficult because there is no common interface to the array of platforms that support ABS work. We seek to transform popular, intuitive, sequential ABS APIs into efficient parallel code automatically. As a first step we are parallelizing the popular MASON multiagent simulation kit, other future potential targets include Player/Stage and Teambots. To achieve this, we have mapped the core MASON API to correlate with the agent API of SASSY, a parallel and scalable, agent-based simulation system. We then use Soot, a Java bytecode optimization framework, to automatically convert MASON bytecode into SASSY bytecode. This allows simple, sequential MASON code to be run in a parallel environment.
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