FREE Opportunity: Supercomputing in Plain English

Supercomputing in Plain English (SiPE), Spring 2018: Available live in person and live via videoconferencing

When: Tuesdays starting Jan 23 2018 (through Tue May 1 2018): 1:30pmET/12:30pmCT/11:30amMT/10:30amPT/9:30amAT/8:30amHT

  • Live in person on the University of Oklahoma Norman campus
  • Live via videoconferencing worldwide
  • (Details of both to be announced.)

Registration is open! Register Here:

(You only need to register once for the whole semester, not for every week.)


  • 1 semester of programming experience and/or coursework in any of
    Fortan, C, C++ or Java, recently

Please feel free to share this with anyone who may be interested and appropriate.

See previous editions at:

About SiPE

So far, the SiPE workshops have reached over 2000 people at 362 institutions, agencies, companies and organizations in 51 US states and territories and 17 other countries:

  • 251 academic institutions;
  • 44 government agencies;
  • 49 private companies;
  • 18 non-governmental/not-for-profit organizations.

SiPE is targeted at an audience of not only computer scientists but especially scientists and engineers, including a mixture of undergraduates, graduate students, postdocs, faculty, staff and professionals.

These workshops focus on fundamental issues of High Performance Computing (HPC) as they relate to Computational and Data-enabled Science & Engineering (CDS&E), including:

  • overview of HPC;
  • the storage hierarchy;
  • instruction-level parallelism;
  • high performance compilers;
  • shared memory parallelism (e.g., OpenMP);
  • distributed parallelism (e.g., MPI);
  • HPC application types and parallel paradigms;
  • multicore optimization;
  • high throughput computing;
  • accelerator computing (e.g., GPUs);
  • scientific and I/O libraries;
  • scientific visualization.

The key philosophy of the SiPE workshops is that HPC-based software should be maintainable, extensible and, most especially, portable across platforms, and should be sufficiently flexible that it can adapt to, and adopt, emerging HPC paradigms.


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