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Big Data Challenges in Simulation-based Science (Canceled)

April 28, 2014

CANCELED 

Date: Tuesday, April 29
Time: 
11:00am - noon
Room:
 Mechanical Engineering (ME) room 218

Abstact

Data-related challenges are quickly dominating computational and data-enabled sciences, and are limiting the potential impact of scientific applications enabled by current and emerging high-performance distributed computing environments. These data-intensive application workflows involve dynamic coordination, interactions and data coupling between multiple application process that run at scale on different resources, and with services for monitoring, analysis and visualization and archiving. In this talk I will explore data grand challenges in simulation-based science and investigate how solutions based on data sharing abstractions, managed data pipelines, in-memory data-staging, in-situ placement and execution, and in-transit data processing can be used to address these data challenges at extreme scales.

Bio

Manish Parashar is Professor of Electrical and Computer Engineering at Rutgers University. He is the founding Director of the Rutgers Discovery Informatics Institute (RDI2) and site Co-Director of the NSF Cloud and Autonomic Computing Center (CAC). Manish received a BE degree from Bombay University, India, and MS and Ph.D. degrees from Syracuse University. His research interests are in the broad areas of Parallel and Distributed Computing and Computational and Data-Enabled Science and Engineering. A key focus of his research is on addressing the complexity or large-scale systems and applications through programming abstractions and systems. Manish serves on the editorial boards and organizing committees of a large number of journals and international conferences and workshops, and has deployed several software systems that are widely used. He has also received a number of awards and is Fellow of AAAS, Fellow of IEEE/IEEE Computer Society and Senior Member of ACM. For more information please visit http://parashar.rutgers.edu/.