John Urbanic is Parallel Computing Specialist at the Pittsburgh Supercomputing Center where he spends as much time as possible implementing extremely scalable code on interesting machines. These days that means a lot of MPI, OpenMP and OpenACC. John also enjoys Big Data challenges which involve such things as graph analytics, SPARQL and novel architectures. John graduated with Physics degrees from Carnegie Mellon University (BS) and Pennsylvania State University (MS) and still appreciates working on applications that simulate physical phenomena.
John teaches workshops and classes on the above as much as possible and particularly likes meeting others with challenging new problems for HPC, so please introduce yourself and let him know what you are working on.
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Researchers should cite this work as follows:
New York University, New York, NY
University of Illinois at Urbana-Champaign
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