Abstract
In some application domains, using a Multi-Agent Systems (MAS) modeling approach may require to handle a large number of agents (crowds, traffic, ecosystems, etc.). In such cases, the computational resources which are needed often raise scalability problems. Considering this kind of issues, General-Purpose computing on Graphics Processing Units (GPGPU) appears to be an appealing solution as it enables huge speed up on a regular PC. However, this technology relies on a highly specialized architecture, implying a very specific programming approach. That is the reason why GPGPU is not widespread technology in the MAS community. This paper reviews the literature which is at the intersection between MAS and GPGPU. The different approaches used are presented and the most promising solutions for a generalization of GPGPU technology in our community will be highlighted.