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: https://docs.google.com/forms/d/e/1FAIpQLSeaf5ypira79lTs1Nx7JR2YkFevxV7-4zwFCtT0SfHhDBGLUA/formResponse
(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: http://www.oscer.ou.edu/education/
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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