Registrations for the Petascale Computing Institute are now open!

Organized by SciNet and other supercomputing facilities, the training event will take place from Aug 19-23

Toronto, April 22, 2019: The Petascale Computing Institute, a week-long training event for those using high-performance computing (HPC), announced its registrations are now open. Set to take place from Aug 19-23, 2019, the training program is targeted towards individuals who would like to scale their data analysis programs and computational codes to leadership-class computing systems. The Petascale Computing Institute is an online training event which will broadcast its content and sessions live to all the host sites via a two-way conference. It is designed for individuals conducting research across disciplines, students, educators, and practitioners in academia, industry and government agencies.

The Petascale Computing Institute is free and open to everyone and is organized by SciNet and other supercomputing facilities in the U.S. who will also host the classes at their respective sites. The program is designed to enable computational and data-enabled discovery across all verticals of study by educating researchers and HPC users. Those interested in undergoing the training will need to create an XSEDE account to register and can choose to view the webcast at any of there host sites here –

The Institute will start with a keynote session by HPC pioneer Gordon Bell who will speak on “Man vs. Machine: The Challenge of Engineering Programs for HPC” and will also host sessions on MPI, OpenMP, OpenACC, CUDE, HPC Python, Best Practices, Visualization, Code Optimization among others. Participants are expected to have familiarity with programming in Fortran, C, C++, Python or a comparable language, Linux, and with the use of clusters and/or HPC systems.

Organizing Partners
Argonne National Laboratory (ANL), the Blue Waters project at NCSA, the National Energy Research Scientific Computing Center (NERSC), Oak Ridge Leadership Computing Facility (OLCF), Pittsburgh Supercomputing Center, SciNet at the University of Toronto, and the Texas Advanced Computing Center (TACC).

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