High Performance Computing

Python at SC12

by onyame on November 4, 2012

Fortunately, the major supercomputing conference SC12 in Salt Lake City will feature a number of Python related events. It is by far the most mentioned programming language in the conference schedule. See the list of events:

The workshop PyHPC 2012 has the following talks this year:

  • EasyBuild: Building Software With Ease by Kenneth Hoste, Jens Timmerman, Andy Georges and Stijn De Weirdt (Ghent University)
  • Efficient Dynamic Derived Field Generation on Many-Core Architectures Using Python by Cyrus Harrison (Lawrence Livermore National Laboratory), Paul Navratil (Texas Advanced Computing Center), Maysam Moussalem (University of Texas at Austin), Ming Jiang (Lawrence Livermore National Laboratory) and Hank Childs (Lawrence Berkeley National Laboratory)
  • A complete Python HPC framework: PyTrilinos, ODIN, and Seamless by Kurt Smith (Enthought, Inc.), William Spotz (Sandia National Laboratories) and Sean Ross-Ross (Enthought, Inc.)
  • Mrs: MapReduce for Scientific Computing in Python by Andrew McNabb, Jeffrey Lund and Kevin Seppi (Brigham Young University)

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Second international workshop on Python for High Performance and Scientific Computing collocated with the 25th Supercomputing Conference (SC12) in Salt Lake City, USA.

Workshop homepage and Call for PapersWorkshop Python for High Performance and Scientific Computing.

Important dates:

Full paper submission: September 14, 2012

Notification of acceptance: October 1, 2012

Camera-ready papers: October 29, 2012

Workshop: November 16, 2011, 8:30 am – 12:00 pm

 

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International Symposium on Grids & Clouds 2012 (ISGC 2011), Taipei, Taiwan, 26 February – 02 March 2012

Abstract:

Python is an accepted high-level scripting language with a growing community in academia and industry. It is used in many scientific applications in many different scientific fields and in more and more industries (for example, in engineering or life science). In all fields, the use of Python for high-performance and parallel computing is increasing. Several organizations and companies are providing tools or support for Python development. This includes libraries for scientific computing, parallel computing, and MPI. Python is also used on many core architectures and GPUs, for which specific Python interpreters are being developed. Also, Python is used for Grid- and Cloud-aware applications. Many existing libraries support Python developers for that. Python especially is used by scientists and engineers. The talk describes, why Python is used, as well as the specific advantages and current drawbacks of Python for scientific applications. And predictions of future uses of Python are presented, combined with hints and best practices to the get major improvements in the development of distributed and HPC applications.

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Birds-of-a-Feather Session on Python for High Performance Computing at SC11 (November 17, 2011, Seattle, WA).

Time and location: Thursday, Nov 17, 2011, 5:30pm – 7pm, room TCC 305

Session leaders: Andreas Schreiber, William R. Scullin, and Andy R. Terrel.

The Python for High Performance Computing BoF is a forum for presenting products, projects, ideas, and problems related to Python as short lightning talks (5 minutes each). The goal is to get in contact with other colleagues for further discussion and joint activities. All presentations should be related to Python in some way, for example: introduction of existing software using Python as an implementation language for HPC applications, experience reports with advantages or drawbacks of Python for HPC, announcements of events related to Python and HPC, proposals for projects where Python plays a role, or request for collaboration and search for partners.

Talks:

  • Python Tools for Visual Studio (Pamela Vagata, Microsoft)
  • Distributed itertools (Pamela Vagata, Microsoft)
  • PyClaw (Aron Ahmadia, KAUST)
  • fwrap (Kurt Smith, Enthought, Inc.)
  • HPC Python distribution (Chris Kees, US Army ERDC)
  • Python DSL ROFL (Jon Riehl, Resilient Science, Inc.)
  • Python / ArBB VM implementation (Michael McCool, Intel)
  • GA4py (Jeff Daily, PNNL)
  • Code generation in Python (Andy Terrel, TACC)
  • Disussion (all)

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