John Urbanic is Parallel Computing Scientist 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. He now leads the Big Data efforts which involve such things as graph analytics, machine learning and interesting filesystems. John frequently teaches workshops and classes on all of the above and is most visible as the lead for the NSF XSEDE Monthly Workshop Series, the Summer Boot Camp and the International HPC Summer School on HPC Challenges in Computational Sciences.
John graduated with Physics degrees from Carnegie Mellon University (BS) and Pennsylvania State University (MS) and still appreciates working on applications that simulate real physical phenomena. He is an honored recipient of the Gordon Bell Prize, but still enjoys working on small embedded systems and real-time applications for various ventures.
Diversity Equity Inclusion (DEI)
Education and Training and Outreach
HPC Training and Education
Parallel Programming Languages and Models