High Performance Computing for Disease
Surveillance
March 2007
David Bauer, The MITRE Corporation
Brandon W. Higgs, The MITRE Corporation
Mojdeh Mohtashemi, The MITRE Corporation, MIT CS and AI Laboratory
ABSTRACT
The global health, threatened by emerging infectious diseases, pandemic influenza, and biological warfare, is becoming increasingly dependent on the rapid acquisition, processing, integration and
interpretation of massive amounts of data. In response to these pressing
needs, new information infrastructures are needed to support active, real
time surveillance. Space-time detection techniques may have a high computational cost in both the time and space domains. High performance
computing platforms may be the best approach for efficiently computing
these techniques. Our work focuses on efficient parallelization of these
computations on a Linux Beowolf cluster in order to attempt to meet
these real time needs.
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Additional Search Keywords
HPC, High Performance Computing, Parallel Computing,
Disease Surveillance, Beowolf cluster
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