HPC Symposium 2012

Seventh Annual HPC Workshop

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22-23 March 2012::Lehigh University::Bethlehem, PA

Lehigh HPC Symposium 2012

Together with theory and experimentation, computational methods now constitute a “third pillar” of scientific inquiry. There‚Äôs no denying the role that technology plays in sustaining scientific leadership and economic competitiveness. Advanced technologies allow researchers to build and test models of complex phenomena and then manage and analyze almost unimaginably large volumes of data. Stellar explosions, climate shifts, the effects of gene flow on ecological communities, multi-scale earthquake-induced structural stresses, and nuclear fusion—these cannot be replicated, but they certainly can be simulated.

Computational engineering and science is key to developing models of behavior and modes of scientific discovery that enable significant and often cost-effective progress in solving the grand challenges of our time. Yet the strength of computational science—its universality—is also its political weakness. More than ever, it is crucial to realize that the most scientifically important and economically promising frontiers will be conquered through advanced computational science and technologies.

Lehigh University is gathering preeminent researchers from all disciplines of science and engineering to broaden appreciation of the pervasiveness of computational methods in scientific and engineering research, and to explore related challenges and opportunities. The goal of this two-day event is to develop a network of researchers linking those who develop high-end computational systems and methodologies with those relying upon these technologies to accomplish critical tasks.

Click here to download the HPC Symposium 2012 final program in PDF format. The program also includes a map of the recommended parking locations for those traveling to the Lehigh University campus.

Keynote Speakers:

Manish Parashar, Rutgers University

Moving From Data to Insights—Addressing Data Challenges in Simulation-based Science

Steve Plimpton, Sandia National Laboratory

High-Performance Computing for Atomistic Materials Modeling

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