Shantenu Jha

2020

Eugen Hruska, Vivekanandan Balasubramanian, Hyungro Lee, Shantenu Jha, and Cecilia Clementi (2020): Extensible and Scalable Adaptive Sampling on Supercomputers, Journal of Chemical Theory and Computation, American Chemical Society, Vol 16, Num 12, pp7915-7925

2019

E. A. Huerta, Roland Haas, Shantenu Jha, Mark Neubauer, and Daniel S. Katz (2019): Supporting High-Performance and High-Throughput Computing for Experimental Science, Computing and Software for Big Science, Springer International Publishing, Vol 3, Num 1, pp5

2018

Jumana Dakka, Kristof Farkas-Pall, Matteo Turilli, David W. Wright, Peter V. Coveney, and Shantenu Jha (2018): Concurrent and Adaptive Extreme Scale Binding Free Energy Calculations, Institute of Electrical & Electronics Engineers, 2018 IEEE 14th International Conference on e-Science (e-Science), pp189-200, Amsterdam, Netherlands

2019

Shantenu Jha, Cecilia Clementi, Eugen Hruska (2019): Extensible and Scalable Adaptive Sampling to Fold Proteins on Supercomputers, 2019 Blue Waters Annual Report, pp222-223

2018

Shantenu Jha (2018): RADICAL-Cybertools: A Building-Blocks Approach to Harnessing the Power of Many, 2018 Blue Waters Annual Report, pp190-191

Saurabh Jha: A Study of Network Congestion in Two Supercomputing High-Speed Interconnects


26th IEEE Annual Symposium on High-Performance Interconnects (HOTI), Santa Clara, California, U.S.A., Aug 16, 2019

Shantenu Jha: The Power of Many: The Next Frontier


Blue Waters Symposium 2019, Jun 4, 2019

Shantenu Jha, J. Dakka, D. Wright, M. Turilli, and K. Farkas-Pall: Enabling Trade-offs Between Accuracy and Computational Cost: Adaptive Algorithms to Reduce Time to Clinical Insight


11th IEEE International Scalable Computing Challenge (SCALE 2018) at the IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid) 2018; Washington D.C., U.S.A., May 3, 2018

Jumana Dakka, Matteo Turilli, David W. Wright, Stefan J. Zasada, Vivek Balasubramanian, Shunzhou Wan, Peter V. Coveney, and Shantenu Jha: High-throughput Binding Affinity Calculations at Extreme Scales


Computational Approaches for Cancer workshop at the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '17); Denver, Colorado, U.S.A., Nov 17, 2017

Research group uses supercomputing to target the most promising drug candidates from a daunting number of possibilities


May 15, 2019

Shantenu Jha of the Department of Energy's (DOE's) Brookhaven National Laboratory and Rutgers University leads a team trying to streamline computational methods so that supercomputers can take on some of this immense workload. They've found a new strategy to tackle one part: differentiating how drug candidates interact and bind with a targeted protein.


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What’s New in HPC Research: October (Part 2)


Oct 15, 2018

In this paper, written by a team from the National Center for Supercomputing Applications and Rutgers University, the researchers argue that the (traditionally separate) HPC and HTC infrastructures must be integrated and unified.


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Software framework designed to accelerate drug discovery wins IEEE International Scalable Computing Challenge


Jul 31, 2018

This year's winner, "Enabling Trade-off Between Accuracy and Computational Cost: Adaptive Algorithms to Reduce Time to Clinical Insight," is the result of a collaboration between chemists and computational and computer scientists at the U.S. Department of Energy's (DOE) Brookhaven National Laboratory, Rutgers University, and University College London.


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