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PyHPC 2015 : 5th Workshop on Python for High Performance and Scientific Computing

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Link: http://www.dlr.de/sc/pyhpc2015
 
When Nov 15, 2015 - Nov 15, 2015
Where Austin, TX, USA
Submission Deadline Sep 4, 2015
Notification Due Sep 25, 2015
Final Version Due Oct 10, 2015
Categories    python   scientific computing   HPC   big data
 

Call For Papers

CALL FOR PAPERS

PyHPC2015

5th Workshop on Python for High Performance and Scientific Computing

November 17, 2014, New Orleans, USA

In cooperation with SIGHPC

Held in conjunction with SC15: The International Conference on High
Performance Computing, Networking, Storage and Analysis


http://www.dlr.de/sc/pyhpc2015


INTRODUCTION

Python is an established, high-level programming language with a large
community in academia and industry. It is a general-purpose language adopted
by many scientific applications such as computational fluid dynamics,
biomolecular simulation, artificial intelligence, statistics, data analysis,
scientific visualization etc. The use of Python for scientific, high-
performance parallel, and distributed computing has increased in recent years.
Especially, the use of Python rises for data analysis and Big Data processing.
Traditionally, system administrators are using Python a lot for automating
tasks. Since Python is extremely easy to learn with a very clean syntax, it is
well-suited for education in scientific computing, mathematics, and other
disciplines. Programmers are much more productive using Python.

The workshop will bring together researchers and practitioners from industry,
academia, and the wider community using Python in all aspects of high
performance and scientific computing. The goal is to present Python
applications from mathematics, science, and engineering, to discuss general
topics regarding the use of Python (such as language design and performance
issues), and to share experience using Python in scientific computing
education.

The main focus areas of the workshop will be on hybrid programming where
Python is combined with traditional HPC languages (e.g., Fortran or C/C++) and
on comparison with other dynamic languages that are used for HPC and technical
computing (e.g., Julia, MATLAB, or R). Another focus area is on Python
programming for modern multi-core processors and accelerators (e.g., GPUs or
Intel Xeon Phi) and for quantum computers.


CALL FOR PAPERS

Please submit papers related to Python usage in any of the following topics
and application areas as well as on broader topics in business, science,
technology, engineering, education, mathematics or multidisciplinary topics:

* Hybrid programming and integration with other programming languages
* Comparison of Python with other dynamic languages for HPC
* Python for multi-core processors and quantum computers
* Interactive parallel computing
* High-performance computing applications with Python
* Performance analysis, profiling, and debugging of Python code
* System administration
* Scientific visualization
* Problem solving environments and frameworks
* Education in scientific computing
* Big data and data analytics


SUBMISSION

We invite you to submit a paper of up to 10 pages via the submission site
(https://www.easychair.org/conferences/?conf=pyhpc2015). All papers will be
published in cooperation with SIGHPC through ACM Digital Library and IEEE
Xplore. The formatting instructions are available here:
http://www.ieee.org/conferences_events/conferences/publishing/templates.html


IMPORTANT DATES

* Full paper submission: September 5, 2015
* Notification of acceptance: September 25, 2015
* Camera-ready papers: October 10, 2015
* Workshop: November 15, 2014 (Concurrent with SC15)


PROGRAM COMMITTEE

* Lorena A. Barba, The George Washington University, USA
* Achim Basermann, German Aerospace Centre, Germany
* Yung-Yu Chen, Synopsys, Inc., Taiwan
* Samantha Foley, University of Wisconsin, USA
* Cyrus Harrison, Lawrence Livermore National Laboratory, USA
* William E. Hart, Sandia National Laboratories, USA
* Konrad Hinsen, Centre de Biophysique Moléculaire, CNRS Orléans, France
* Michael Klemm, Intel GmbH, Germany
* Andreas Klöckner, University of Illinois at Urbana-Champaign, USA
* Guy K. Kloss, Mega Ltd., New Zealand
* Maurice Ling, Nanyang Technological University, Singapore
* Stuart Mitchell, The University of Auckland, New Zealand
* Mike Müller, Python Academy, Germany
* Marc Poinot, ONERA, France
* Kurt Smith, Enthought, Inc., USA
* Matthew Turk, Columbia University, USA


WORKSHOP ORGANIZERS

* Andreas Schreiber, German Aerospace Centre (DLR), Germany
* William Scullin, Argonne National Laboratory, USA
* Bill Spotz, Sandia National Laboratories, USA
* Andy R. Terrel, Continuum Analytics, Inc., USA


CONTACT

E-Mail: pythonhpc@dlr.de
Twitter: @PythonHPC

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