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The objective of the seminar is to provide the participants with the context and background of handling problems related to real
time scientific applications. In recent times, there is high requirement & availability of higher solution data with higher frequency. This leads
to growth of data at tremendous rate and there is challenge to process and optimize the data in real time scenario to disseminate timely and useful
information for benefit of the society. Also, many
times data are complex in nature which results in
increased data volume. In scientific domain, we
have encountered many data crunching
problems.Notable applications for parallel
processing include computational astrophysics,
health diagnosis, geoprocessing (or seismic
surveying), climate modeling, agriculture
estimates, financial risk management, video color
correction, computational fluid dynamics, medical
imaging and drug discovery.

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