National Center for Supercomputing Applications master calendar

National Center for Supercomputing Applications master calendar

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Event Detail Information

Event Detail Information

GPUs: An Enabling Force for Real-time Application Development

Speaker Pallav Kumar Baruah, associate professor, Department of Mathematics and Computer Science, Sri Sathya sai Institute of Higher Learning, Prasanthinilayam, India
Date Mar 28, 2014
Time 11:00 am  
Location Room 1030, NCSA Building, 1205 W. Clark St., Urbana, IL
Event type Seminar
Views 47
Originating Calendar NCSA events

BIO: Pallav Kumar Baruah earned a Ph.D in Mathematics (Differential Equation and Analysis) from Sri Sathya sai Institute of Higher Learning in 1994. Parallel processing on various platforms has been a focus area of his research since around 2005. His work spans areas like automatic parallelizing tools, development of MPI implementation, investigating the feasibility of using IBM CellBE for running MPI applications, study of process/processor affinity, load balancing on large clusters, data integrity, privacy & security on outsourced data using HPC tools and technique on multi & many cores including GPUs. Privacy preserving data mining is another area of interest, where HPC and GPU play an important role. He is also working on development of applications for some of the problems in bioinformatics using GPUs. Recent work also includes exploring the potential of Intel MIC, K20, K40 and trying to build a comprehensive performance model and predictive tool for such accelerators. He is the PI for a number of projects from various agencies, includuing the CUDA Research Center and CUDA Teaching Center. He can be reached at pkbaruah@sssihl.edu.in.

ABSTRACT: In this talk we will briefly discuss the feasibility of developing real time applications using GPUs. We take examples from the areas of speech processing, image/video processing. We will also present implementation of an existing compression technique tailored for DNA sequences. Also show the development of sequence alignment and pattern matching on the compressed space thereof. Also may present an exploratory work on developing a performance prediction model for the GPUs.

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