Affiliation:
1. TUM Create Ltd. & Technische Universität München
2. TUM Create Ltd. & Nanyang Technological University, Singapore
3. Nanyang Technological University, Singapore
4. Technische Universität München & Nanyang Technological University
Abstract
Due to decelerating gains in single-core CPU performance, computationally expensive simulations are increasingly executed on highly parallel hardware platforms. Agent-based simulations, where simulated entities act with a certain degree of autonomy, frequently provide ample opportunities for parallelisation. Thus, a vast variety of approaches proposed in the literature demonstrated considerable performance gains using hardware platforms such as many-core CPUs and GPUs, merged CPU-GPU chips as well as Field Programmable Gate Arrays. Typically, a combination of techniques is required to achieve high performance for a given simulation model, putting substantial burden on modellers. To the best of our knowledge, no systematic overview of techniques for agent-based simulations on hardware accelerators has been given in the literature. To close this gap, we provide an overview and categorisation of the literature according to the applied techniques. Since, at the current state of research, challenges such as the partitioning of a model for execution on heterogeneous hardware are still addressed in a largely manual process, we sketch directions for future research towards automating the hardware mapping and execution. This survey targets modellers seeking an overview of suitable hardware platforms and execution techniques for a specific simulation model, as well as methodology researchers interested in potential research gaps requiring further exploration.
Funder
Singapore National Research Foundation under its Campus for Research Excellence And Technological Enterprise (CREATE) programme
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Cited by
30 articles.
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