Multi-Agent Systems Meet GPU: Deploying Agent-Based Architectures on Graphics Processors - Technological Innovation for the Internet of Things Access content directly
Conference Papers Year : 2013

Multi-Agent Systems Meet GPU: Deploying Agent-Based Architectures on Graphics Processors

Roman Pavlov
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Jörg P. Müller
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  • PersonId : 986653

Abstract

Even given today’s rich hardware platforms, computation-intensive algorithms and applications, such as large-scale simulations, are still challenging to run with acceptable response times. One way to increase the performance of these algorithms and applications is by using the computing power of Graphics Processing Units (GPU). However, effectively mapping distributed software models to GPU is a non-trivial endeavor. In this paper, we investigate ways of improving execution performance of multi-agent systems (MAS) models by means of relevant task allocation mechanisms, which are suitable for GPU execution. Several task allocation architecture variants for MAS using GPU are identified and their properties analyzed. In particular, we study three cases: Agents and their runtime environment can be (i) completely on the host (CPU); (ii) partly on host and device (GPU); (iii) completely on the device. For each of these architecture variants, we propose task allocation models that take GPU restrictions into account.
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hal-01348742 , version 1 (25-07-2016)

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Roman Pavlov, Jörg P. Müller. Multi-Agent Systems Meet GPU: Deploying Agent-Based Architectures on Graphics Processors. 4th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2013, Costa de Caparica, Portugal. pp.115-122, ⟨10.1007/978-3-642-37291-9_13⟩. ⟨hal-01348742⟩
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