BRAIN TUMOR INFORMATICS
IN SILICO SCIENCE
CLINICAL AND TRANSLATIONAL INFORMATICS
HIGH END COMPUTING
IMAGING INFORMATICS

High End Computing

Share Last Updated: March 07, 2013


The Biomedical Informatics Department's focus on system software for data-intensive applications is designed to facilitate new approaches to research, experimentation and decision support. As the size and extent of data increases in a wide range of scientific and other endeavors, the capabilities described here will become increasingly essential.  Our work aims to preserve and enhance the productivity of researchers as well as assure access to knowledge that is crucial for decision-makers.

 

Related Projects:

High Performance Computing for Classification of Whole Slide Tissue Images

Keeneland: Brain Tumor Research with GPUs

 

Conference and Journal Publications:

  1. G. Teodoro, T. Pan, T. Kurc, J. Kong, L. Cooper, N. Podhorszki, S. Klasky, J. Saltz. "High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms." Accepted to IDPS'13. Boston, MA. May 2013.
     
  2. G. Teodoro, T. Pan, T. Kurc, J. Kong, L. Cooper, J. Saltz. "Efficient Irregular Wavefront Propagation Algorithms on Hybrid CPU-GPU Machines." To appear in Parallel Computing. April 2013.
     
  3. K. Wang, Y. Huai, R. Lee, F. Wang, X. Zhang, and Joel H. Saltz. "Accelerating Pathology Image Data Cross Comparison on CPU/GPU Hybrid Systems," accepted to the 38th International Conference on Very Large Databases (VLDB 2012), Istanbul, Turkey, August 27 – 31.
     
  4. G. Teodoro, T. Kurc, T. Pan, L. Cooper, J. Kong, P. Widener, and J. Saltz, "Accelerating Large Scale Image Analyses on Parallel, CPU-GPU Equipped Systems,'' in 26th IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2012.
     
  5. Pooya Zandevakili, Ming Hu, Zhaohui Qin: "GPUmotif: An Ultra-Fast and Energy-Efficient Motif Analysis Program Using Graphics Processing Units," PLoS ONE 7(5): e36865. May 25, 2012.
     
  6. Cooper, L.A.D.; Saltz, J.H.; Catalyurek, U.; Kun Huang; "Acceleration of Two Point Correlation Function Calculation for Pathology Image Segmentation," Healthcare Informatics, Imaging and Systems Biology (HISB), 2011 First IEEE International Conference on , vol., no., pp.174-181, 26-29 July 2011.
     
  7. Cooper, L.; Kun Huang; Ujaldon, M.; "Parallel Automatic Registration of Large Scale Microscopic Images on Multiprocessor CPUs and GPUs," Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on , vol., no., pp.1367-1376, 16-20 May 2011.
     
  8. Fusheng Wang, Jun Kong, Lee Cooper, Tony Pan, Tahsin Kurc, Wenjin Chen, Ashish Sharma, Cristobal Niedermayr, Tae W. Oh, Daniel Brat, Alton B. Farris, David Foran, Joel Saltz, “A Data Model and Database for High-resolution Pathology Analytical Image Informatics,” Journal of Pathology Informatics, Vol. 2, Issue 1, pp. 32-40, 2011.
     
  9. F. Wang, J. Kong, J. Gao, C. Vergara-Niedermayr, D. Adler, L. Cooper, W. Chen, T. Kurc, and J. Saltz, “High Performance Analytical Pathology Imaging Database for Algorithm Evaluation,” Proceedings of the Workshop on High Performance and Distributed Computing for Medical Imaging HP-MICCAI/MICCAI-DCI, Toronto, Canada, September, 2011.
     
  10. M. Parashar, H. Klie, T. Kurc, U. Catalyurek, J. Saltz, and M. Wheeler, "Dynamic Decision and Data-Driven Strategies for the Optimal Management of Subsurface Geo-Systems," Journal of Algorithms and Computational Technology, Vol. 5, No. 4, pp. 645-665, 2011.
     
  11. Fusheng Wang, Tahsin Kurc, Patrick Widener, Tony Pan, Jun Kong, Lee Cooper, David Gutman, Ashish Sharma, Sharath Cholleti, Vijay Kumar and Joel Saltz,  “High-performance Systems for In Silico Microscopy Imaging Studies," The 7th International Conference on Data Integration in the Life Sciences, Gothenburg, Sweden, August 2010.
     
  12. V.S. Kumar, T. Kurc, V. Ratnakar, J. Kim, G. Mehta, K. Vahi, Y.L. Nelson, P. Sadayappan, E. Deelman, Y. Gil, M. Hall and J. Saltz, ”Parameterized Specication, Conguration and Execution of Data-Intensive Scientic Workows”, Cluster Computing: the Journal of Networks, Software Tools and Applications, Special Issue on High Performance Distributed Computing, Vol. 13(3), pp. 315-333, 2010.
     
  13. N. Vydyanathan, S. Krishnamoorthy, G.M. Sabin, U.V. Catalyurek, T. Kurc, P. Sadayappan, J. Saltz, ”An Integrated Approach to Locality-Conscious Processor Allocation and Scheduling of Mixed-Parallel Applications”, IEEE Trans. Parallel Distrib. Syst., Vol. 20(8), pp. 1158-1172, 2009.
     
  14. V.S. Kumar, T. Kurc, J. Saltz, G. Abdulla, S. Kohn, and C. Matarazzo, "Architectural Implications for Spatial Object Association Algorithms," the 23rd IEEE International Parallel and Distributed Processing Symposium (IPDPS 09), Rome, Italy, May, 2009.
     
  15. S. Narayanan, U. Catalyurek, T. Kurc, and J. Saltz, ”Parallel Materialization of Large ABoxes”, the 24th Annual ACM Symposium on Applied Computing (SAC 2009), Hawaii, USA, March, 2009.
     
  16. D.J. Foran, L. Yang, O. Tuzel, W. Chen, J. Hu, T. Kurc, R. Ferreira, J. Saltz, ”A caGrid-Enabled, Learning Based Image Segmentation Method for Histopathology Specimens”, ISBI 2009: 1306-1309, 2009.

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