Optimizing Java Bytecode Using the Soot Framework: Is It Feasible?
CC '00 Proceedings of the 9th International Conference on Compiler Construction
Soot - a Java bytecode optimization framework
CASCON '99 Proceedings of the 1999 conference of the Centre for Advanced Studies on Collaborative research
Behavioral diversity in learning robot teams
Behavioral diversity in learning robot teams
Proceedings of the 38th conference on Winter simulation
Quantitative assessment of an agent-based simulation on a time warp executive
Proceedings of the 40th Conference on Winter Simulation
Optimistic parallelism requires abstractions
Communications of the ACM - The Status of the P versus NP Problem
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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.