Award Abstract #0619616
MRI: Enabling Research on Terabyte-Scale Datasets

NSF Org:	CNS Division of Computer and Network Systems
Initial Amendment Date:	July 24, 2006
Latest Amendment Date:	July 24, 2006
Award Number:	0619616
Award Instrument:	Standard Grant
Program Manager:	Rita V. Rodriguez CNS Division of Computer and Network Systems CSE Directorate for Computer & Information Science & Engineering
Start Date:	August 1, 2006
Expires:	July 31, 2009 (Estimated)
Awarded Amount to Date:	$199000
Investigator(s):	Gene Cooperman gene@ccs.neu.edu (Principal Investigator) David Kaeli (Co-Principal Investigator) Javed Aslam (Co-Principal Investigator) Jennifer Dy (Co-Principal Investigator) Ravi Sundaram (Co-Principal Investigator)
Sponsor:	Northeastern University 360 HUNTINGTON AVE BOSTON, MA 02115 617/373-5600
NSF Program(s):	MAJOR RESEARCH INSTRUMENTATION
Field Application(s):	0000912 Computer Science
Program Reference Code(s):	HPCC, 9218
Program Element Code(s):	1189

ABSTRACT

This project, acquiring a cluster to perform research on terabyte-scale problems in the areas of information retrieval, network traffic analysis, intrusion detection, and image processing for biomedicine, enables long term studies by providing access to users with terabytes of storage for extended periods of time. In this shared facility, investigators will cooperatively exploit a cluster containing 20 terabytes of disk storage. Additionally, a high performance terabyte disk subsystem, connected by fibre channel will serve as a higher speed cache for the large disk storage. To complete the memory storage, data migration will leverage using existing tertiary storage backup systems. In order to attain both the highest efficiency and the highest flexibility in processing such large datasets, the cluster employs quad-processor nodes and 8 GB of RAM per node. Testing on full size data eliminates errors caused by sampling smaller datasets in many areas. Enabling new research, the projects range from analysis of distributed denial of service, through learning for biomedical images, to parallel tomosynthesis. Software tools to be refined on this facility include methodologies for Information Retrieval, Support Vector Machines (SVM), Clustering, Network Simulation, Out-of-Core Search, 3-D Image Reconstruction, and Spatial and Temporal Databases. It is anticipated that the increase in data manipulation capabilities will provide much quicker turn-around and make possible results that are inaccessible with the currently installed technology.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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B. Erem, G. Sharp, D. Kaeli and Z. Wu.  "Interactive Deformable Registration, Visualization and Analysis of 4D Computed Tomography,"  International Conference on Medical Biometrics,  2008,  p. 232.

Daniel Kunkle and Gene Cooperman.  "Twenty-Six Moves Suffice for Rubik's Cube,"  Proc. of International Symposium on Symbolic and Algebraic Computation (ISSAC '07), ACM Press, 2007,  2007,  p. 235.

Daniel Kunkle and Gene Cooperman.  "Solving Rubik's Cube: Disk is the New RAM (ACM Viewpoint),"  ACM Communications,  v.51,  2008,  p. 31.

Eric Robinson , Daniel Kunkle , Gene Cooperman.  "A comparative analysis of parallel disk-based Methods for enumerating implicit graphs,"  Proceedings of the 2007 international workshop on Parallel symbolic computation,  2007,  p. 78.

Eric Robinson, Jürgen Müller and Gene Cooperman.  "A Disk-Based Parallel Implementation for Direct Condensation of Large Permutation Modules,"  Proc. of International Symposium on Symbolic and Algebraic Computation (ISSAC '07), ACM Press, 2007,  2007,  p. 315.

F. Azmandian, S. Jiang and D. Kaeli.  "Towards the Development of an Error Checker for Radiotherapy Treatment Plans: A Preliminary Study,"  Physics in Medicine and Biology,  v.52,  2007,  p. 6711.

V. Sridharan, D. Kaeli and D. Liberty.  "A Taxonomy to Enable Error Recovery and Correction in Software,"  Workshop on Quality-Aware Design,  v.6,  2008, 

Ying Cui, Jennifer G. Dy, Gregory C. Sharp, Brian M. Alexander, and Steve B. Jiang.  "Learning Methods for Lung Tumor Markerless Gating in Image-Guided Radiotherapy,"  Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,  2008,  p. 902.

Z. Chen, D. Kaeli and K. Murphy.  "Performance Evaluation of Virtual Applicances,"  Workshop on Virtualization Performance: Analysis, Characterization, and Tools,  v.4,  2008, 


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