A Framework for Megascale Agent Based Simulations on the GPU

Abstract

This paper presents a series of efficient, data parallel algorithms for simulating agent based models on a graphics processing unit (GPU). These include methods for handling environment updates, agent interactions, and replication. One of the most important techniques presented in this work is a novel stochastic allocator which enables parallel agent replication in O(1) average time. We believe that our system is the first ever completely GPU based agent simulation framework. Due to a combination of algorithmic and architectural advancements, our prototype system achieves a speed up of several orders of magnitude over conventional CPU based approaches