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Simple Run-Time Infrastructure (SRTI): An accessible distributed computing platform for interdisciplinary simulation

delete2021-10-01
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OA
AI
S
Szu-Yun Lin *
A
Andrew W. Hlynka
L
Lichao Xu
路皓 cover
路皓 (Hao Lü)
O
Omar A. Sediek
S
Sherif El‐Tawil
V
Vineet R. Kamat
J
Jason McCormick
C
Carol C. Menassa
S
Seymour M.J. Spence
A
Atul Prakash
B
Benigno E. Aguirre
DOI:10.1016/j.jocs.2021.101455delete
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Abstract

Abstract

En 中文
Distributed computing is a necessity for conducting cross-disciplinary research where field-specific computational models (simulators) are available, but have not been designed to work together. An example of this is natural hazards research. Simulators abound in the disparate fields that fall under this area, e.g. social science, engineering, economics, and health, but little progress has been made to integrate the simulators to study overarching and cross-disciplinary disaster scenarios. The reason for slow penetration of this technology is the high barrier to entry, which requires extensive knowledge of computer science and programming. Building upon an existing platform named Simple Run Time Infrastructure (SRTI v1), a new, fundamentally different version (SRTI v2) is developed to address the issues mentioned above. Designed to provide a low barrier to use, SRTI v2 is developed for users with limited programming experience and designed to simplify and streamline a user's effort to compose a distributed simulation and handle time management. To achieve this primary objective, pre compiled components are provided including the RTI Management Server, RTI Wrapper, and a GUI. By exploiting these pre-compiled components, users can compose a scalable distributed simulation with heterogeneous computational models. To demonstrate the concepts behind SRTI, a cross-language simulation, modified and extended from a time-dependent resilience analysis of an electric power system in the literature, is presented to show the scalability and usability of SRTI. Features of the different versions of SRTI are discussed and useful features to develop in the future are outlined.
Keywords:
Distributed computing platform
Distributed simulation
Interdisciplinary simulation
Natural hazards modeling
Hybrid communication
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Nature Computational Science cover
Nature Computational Science
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National Taiwan University
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University of Michigan
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