arrow
Return

A Survey on Agent-based Simulation Using Hardware Accelerators

delete2019-01-28
delete28
delete
OA
AI
J
Jiajian Xiao *
P
Philipp Andelfinger
D
David Eckhoff
W
Wentong Cai
A
Alois Knoll
DOI:10.1145/3291048delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
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.
Keywords:
Agent-based simulation
heterogeneous computing
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

ACM Computing Surveys cover
ACM Computing Surveys
IF:
28
Papers:
2.4K
Citations:
3.5W

Organization

N
Nanyang Technological University
Scholars:
4.9W
Papers: 4.8W
Citations: 8.1W
T
Technical University of Munich
Scholars:
5.2W
Papers: 3.9W
Citations: 6.2W