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

Conference ·
 [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. ORNL
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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.

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1463973
Resource Relation:
Journal Volume: 10861; Conference: International Conference on Computational Science (ICCS 2018) - Wuxi, , China - 6/11/2018 8:00:00 AM-6/14/2018 8:00:00 AM
Country of Publication:
United States
Language:
English

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