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Award Abstract #1229744

MRI: Acquisition of a High Performance Computer Cluster for Multidisciplinary Computational Research at Prairie View A&M University

Div Of Advanced Cyberinfrastructure
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Initial Amendment Date: September 14, 2012
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Latest Amendment Date: June 11, 2015
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Award Number: 1229744
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Award Instrument: Standard Grant
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Program Manager: Edward Walker
ACI Div Of Advanced Cyberinfrastructure
CSE Direct For Computer & Info Scie & Enginr
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Start Date: October 1, 2012
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End Date: September 30, 2016 (Estimated)
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Awarded Amount to Date: $394,222.00
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Investigator(s): Suxia Cui sucui@pvamu.edu (Principal Investigator)
Yonghui Wang (Co-Principal Investigator)
Lei Huang (Co-Principal Investigator)
Dhadesugoor Vaman (Former Co-Principal Investigator)
Yi Lu (Former Co-Principal Investigator)
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Sponsor: Prairie View A & M University
P O Box 667
Prairie View, TX 77446-0667 (936)261-1689
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Program Reference Code(s): 9102, 1189
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Program Element Code(s): 1189


This work provides a High Performance Computing (HPC) cluster at Prairie View A&M University to support a broad array of multidisciplinary computing-intensive research and research training.

The proposed cluster features Ethernet ports connection between nodes, shared network storage and massive parallel computation on graphics processor cores. Moreover, the on board Gigabit Ethernet ports with switch connection can support large data sets transmission to enable the research in real time multimedia network simulation.

Demonstrating compressive sensing (CS) on real time multi-view video application requires considerable computational capability but is critical for surveillance camera and sensor networks. The impacts are nontrivial in homeland security applications especially on the battlefield where sensors and hand-held radios are mobile. Video sensors detect physical properties and rapidly transmit the data to a command control center for remote executable actions. A High Performance Computing cluster makes it possible to explore parallel processing of CS sampling and rendering and the Prairie View cluster is ideally suited for high-speed, parallel video processing in the research of these applications. This cluster enables new research in simulating cognitive radio networks with more complicated situations The real time simulation will help not only understanding how real time processing affects the cognitive radio applications, but also designing algorithms for applications in real world environment.

This research includes the integration of research and education. The most direct and immediate impact is that research data, source code, and curriculum materials obtained from the research projects supported by this HPC cluster are freely accessible across the research communities. Strengthening the real time multimedia signal reconstruction, analysis and modeling research impacts homeland security needs and efficient usage of network resources. Additionally, the development of new courses, expanded research experiences for Graduate and undergraduate students, and outreach to high school and middle school students are an integral part of planned use of the Prairie View HPC Cluster.


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D. Prabesh, D.R.Vaman. "End to End Quality of Service Assurance for Multi-Service Provisioning in Mobile Ad Hoc Networks," International Journal of Network Security & its Applications (IJNSA), v.4, 2014.

Golam R. Khan, Sharmistha Khan, Dhadesugoor R. Vaman, and Suxia Cui. "A Novel Resource Efficient Dmms Approach for Network Monitoring and Controlling Functions," International Journal of Wireless & Mobile Networks, v.7, 2015, p. 1.

Yuzhong Yan, Mahsa Hanifi, Liqi Yi, and Lei Huang. "Building a Productive Domain-Specific Cloud for Big Data Processing and Analytics Service," Journal of Computer and Communications, v.3, 2015, p. 107.

Sharmistha Khan, Golam R Khan, Dhadesugoor R. Vaman, Siew T. Koay and Suxia Cui. "Analyzing The Performance of the Dynamic Position Location and Tracking (D-Pl&T) of Mobile Nodes Using Omni Directional Antenna in Manet," International Journal of Computer Networks and Communications, v.7, 2015, p. 1.


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