A Survey on Agent-based Simulation using Hardware Accelerators
| Autor: | Wentong Cai, David Eckhoff, Jiajian Xiao, Philipp Andelfinger, Alois Knoll |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
FOS: Computer and information sciences
General Computer Science Computer science Process (engineering) 0211 other engineering and technologies Symmetric multiprocessor system 02 engineering and technology Theoretical Computer Science CUDA 0202 electrical engineering electronic engineering information engineering Computer Science - Multiagent Systems Field-programmable gate array 021103 operations research Computer Science - Performance Computer performance business.industry Sketch Variety (cybernetics) ddc Performance (cs.PF) Computer Science - Distributed Parallel and Cluster Computing 020201 artificial intelligence & image processing State (computer science) Distributed Parallel and Cluster Computing (cs.DC) business Computer hardware Multiagent Systems (cs.MA) |
| Popis: | 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 FPGAs. 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 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. Submitted for review to ACM Computing Surveys on 24/05/2018 |
| Databáze: | OpenAIRE |
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