March 2026

Conference Paper

An Event Detection Framework for Virtual Observation System: Anomaly Identification for an ACME Land Simulation

By:
Yao, Zhuo ; Wang, Dali ; Wang, Yifan ; Yuan, Fengming
Page Number:
44-55
Volume:
II
Issue Number:
n/a
Book Title:
Computational Science – ICCS 2018
Publication Date:
March 12, 2026
Publisher Location:
Springer, Cham, Switzerland
Conference Name:
International Conference on Computational Science (ICCS 2018)
Conference Location:
Wuxi, China
Conference Sponsor:
Springer
View DOI Listing:
https://doi.org/10.1007/978-3-319-93701-4_4

Abstract

Based on previous work on in-situ data transfer infrastructure and compiler-based software analysis, we have designed a virtual observation system for real time computer simulations. This paper presents an event detection framework for a virtual observation system. By using signal processing and detection approaches to the memory-based data streams, this framework can be reconfigured to capture high-frequency events and low-frequency events. These approaches used in the framework can dramatically reduce the data transfer needed for in-situ data analysis (between distributed computing nodes or between the CPU/GPU nodes). In the paper, we also use a terrestrial ecosystem system simulation within the Earth System Model to demonstrate the practical values of this effort.


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