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Development of Scalable Three-Dimensional Elasto-Plastic Nonlinear Wave Propagation Analysis Method for Earthquake Damage Estimation of Soft Grounds Read chapter Read first chapter

2018 | OriginalPaper | Chapter

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

Authors : Zhuo Yao, Dali Wang, Yifan Wang, Fengming Yuan

Published in: Computational Science – ICCS 2018

Publisher: Springer International Publishing

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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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previous chapter Viscoelastic Crustal Deformation Computation Method with Reduced Random Memory Accesses for GPU-Based Computers
next chapter Enabling Adaptive Mesh Refinement for Single Components in ECHAM6
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Metadata
Title
An Event Detection Framework for Virtual Observation System: Anomaly Identification for an ACME Land Simulation
Authors
Zhuo Yao
Dali Wang
Yifan Wang
Fengming Yuan
Copyright Year
2018
Book
Computational Science – ICCS 2018

Print ISBN: 978-3-319-93700-7

Electronic ISBN: 978-3-319-93701-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-93701-4_4

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