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2012
J. Youl Choi, Abbasi, H., Pugmire, D., Klasky, S., Qiu, J., Fox, G., and Parashar, M., Mining Hidden Mixture Context With ADIOS-P To Improve Predictive Pre-fetcher Accuracy, Proceedings of the Eighth International Conference on eScience (eScience 2012). IEEE, Chicago, IL, 2012.PDF icon 26. Mining Hidden Mixture Context With ADIOS-P To Improve Predictive Pre-fetcher Accuracy.pdf (1.7 MB)
M. Parashar, Proceedings of the 41st International Conference on Parallel Processing , ICPP 2012. IEEE, Pittsburgh, PA, 2012.
M. Parashar, Kaushik, D., Rana, O., and Samtaney, R., Proceedings of the 5th International Conference on Contemporary Computing , IC3 2012, vol. 306. Springer, 2012.
L. Moser, Parashar, M., and Hung, P., Proceedings of the 9th IEEE International Conference on Cloud Computing (CLOUD 2012) IEEE Computer Society Press, CLOUD 2012. IEEE, 2012.
T. Dohi, Parashar, M., Apduhan, B. O., Ishida, K., and Wolter, K., Proceedings of the 9th International Conference on Autonomic and Trusted Computing, ATC 2012. IEEE, 2012.
T. Jin, Zhang, F., Parashar, M., Klasky, S., Podhorszki, N., and Abbasi, H., A Scalable Messaging System for Accelerating Discovery from Large Scale Scientific Simulations, Proceedings of 19th Annual International Conference on High Performance Computing (HiPC 2012). IEEE , Pune, India, 2012.PDF icon 23 A Scalable Messaging System for Accelerating Discovery from Large Scale Scientific Simulations.pdf (633.71 KB)
J. Logan, Klasky, S., Abbasi, H., Liu, Q., Ostrouchov, G., Parashar, M., Podhorszki, N., Tian, Y., and Wolf, M., Understanding I/O Performance using I/O Skeletal Applications, Proceedings of the Euro-Par 2012 Conference. Rhodes Island, Greece, 2012.PDF icon 28. Understanding I O Performance Using I O Skeletal Applications.pdf (1.16 MB)
2011
K. Elangovan, Rodero, I., Parashar, M., Guim, F., and ., H., Adaptive Memory Power Management Techniques for HPC Workloads, Proceedings of the 18th IEEE International Conference on High Performance Computing (HiPC) 2011. Bangaluru, India, 2011.PDF icon 33. Adaptive Memory Power Management Techniques for HPC Workloads.pdf (559.15 KB)
M. Parashar, Addressing the Petascale Data Challenge using In-Situ Analytics. 2011.PDF icon 10. Addtrdding the petascale data challenge using in-situ analytics.pdf (409.24 KB)
X. Qi, Kim, H., Xing, F., Parashar, M., Foran, D., and Yang, L., The analysis of image texture feature robustness using CometCloud, in Proceedings of the 14th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Toronto, Canada, 2011.
S. Hegde, Autonomic Cloudbursting for MapReduce framework using a Deadline based Scheduler, Rutgers, The State University of New Jersey, New Brunswick, 2011.
S. A. Coe, Principato, E., Rizwan, O., and Ye, K., Autonomic Data Center Thermal Management, NJ Governor's School of Engineering and Technology 2011. Piscataway, NJ, USA, 2011.
H. Kim, el-Khamra, Y., Rodero, I., Jha, S., and Parashar, M., Autonomic Management of Application Workflow on Hybrid Computing Infrastructure, Scientific Programming Journal, vol. 19. pp. 75-89, 2011.
H. Kim, Parashar, M., Quiroz, A., and Gnanasambandam, N., Autonomic Workflow Management in Dynamically Federated, Hybrid Cloud Infrastructures using CometCloud, in Cloud Computing: Methodology, Systems, and Applications, CRC, Taylor & Francis Group, 2011.
H. Kim, Parashar, M., Buyya, R., Broberg, J., and Goscinski, A., CometCloud: An Autonomic Cloud Engine, in Cloud Computing: Principles and Paradigms, John Wiley & Sons, 2011, pp. 275-297.PDF icon cometcloud.pdf (497.45 KB)
M. Parashar, Klie, H., Kurc, T., Catalyurek, U., Saltz, J., and Wheeler, M. F., Dynamic Decision and Data-Driven Strategies for the Optimal Management of Subsurface Geo-systems, Journal of Algorithms & Computational Technology, vol. 5, no. No.4, pp. 645 – 665, 2011.
F. Zhang, Docan, C., Parashar, M., and Klasky, S., Enabling Multi-Physics Coupled Simulations within the PGAS Programming Framework, in Proceedings of the 11th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid 2011), Newport Beach, CA, USA, 2011.
H. Viswanathan, Lee, E. K., Rodero, I., Pompili, D., Parashar, M., and Gamell, M., Energy-Aware Application-Centric VM Allocation for HPC Workloads, in Proceedings of the Workshop on High-Performance Grid and Cloud Computing, a workshop at the 25th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2011), Anchorage, Alaska, USA, 2011.PDF icon HPGC_2011.pdf (207.54 KB)
K. Moreland, Oldfield, R., Marion, P., Jourdain, S., Podhorszki, N., Docan, C., Parashar, M., Hereld, M., Papka, M. E., and Klasky, S., Examples of In Transit Visualization, Proceedings of the Workshop on Petascale Data Analytics: Challenges and Opportunities (PDAC-11), in conjunction with ACM/IEEE SC11 . Seattle, WA, USA, 2011.PDF icon 35. Examples of In Transit Visualization.pdf (2.38 MB)
H. Kim, el-Khamra, Y., Jha, S., and Parashar, M., Exploring the Use of Hybrid HPC-Grids/Clouds Infrastructure for Science and Engineering, in Cloud Computing: Methodology, Systems, and Applications, CRC, Taylor & Francis Group, 2011.
L. Yang, Kim, H., Parashar, M., and Foran, D., High Throughput Landmark Based Image Registration Using Cloud Computing, in 14th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Toronto, Canada, 2011.
S. Klasky, Abbasi, H., Logan, J., Parashar, M., Schwan, K., Shoshani, A., Wolf, M., Ahern, S., Altintas, I., Bethel, W., Chacon, L., Chang, C. S., Chen, J., Childs, H., Cummings, J., Ethier, S., Grout, R., Lin, Z., Liu, Q., Ma, X., Moreland, K., Pascucci, V., Podhorszki, N., Samatova, N., Schroeder, W., Tchoua, R., Wu, K. J., and Yu, W., In situ data processing for extreme scale computing, SciDAC Conference. Denver, CO, 2011.
S. Klasky, Abbasi, H., Logan, J., Parashar, M., Schwan, K., Shoshani, A., Wolf, M., Ahern, S., Altintas, I., and Bethel, W., In situ data processing for extreme-scale computing, Scientific Discovery through Advanced Computing Program (SciDAC’11), 2011.PDF icon 12. In situ data processing for extreme scale computing.pdf (728.26 KB)
H. Gadre, Investigating MapReduce Framework Extensions for Efficient Processing of Geographically Scattered Datasets, 2011.
C. Docan, Parashar, M., Cummings, J., and Klasky, S., Moving the Code to the Data -- Dynamic Code Deployment using ActiveSpaces, in Proceedings of the 25th IEEE International Parallel and Distributed Processing Symposium (IPDPS'11), Anchorage, Alaska, USA, 2011.

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