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PyHPC 2017 : 7th Workshop on Python for High-Performance and Scientific Computing

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Link: http://bit.ly/pyhpc2017
 
When Nov 12, 2017 - Nov 12, 2017
Where Denver, CO
Submission Deadline Sep 1, 2017
Notification Due Sep 18, 2017
Final Version Due Oct 9, 2017
Categories    HPC   python   data science   big data
 

Call For Papers

CALL FOR PAPERS

PyHPC2017

7th Workshop on Python for High-Performance and Scientific Computing

November 12, 2017, Denver, CO, USA

In cooperation with SIGHPC

Held in conjunction with SC17: The International Conference on High
Performance Computing, Networking, Storage and Analysis


http://www.dlr.de/sc/pyhpc2017


INTRODUCTION

The high-level programming language Python is well established with a
large community in academia and industry. It is a general-purpose
language adopted by many scientific applications. Examples are
computational fluid dynamics, bio molecular simulation, machine
learning, finance, or scientific visualization. Scientists, engineers,
and educators use Python for data science, high-performance computing,
and distributed computing. Traditionally, system administrators use
Python for system management and automating administration tasks.
Python is extremely easy to learn due to its very clean syntax and
great readability. Therefore developers love Python as it facilitates
writing sustainable and maintainable software systems. For the same
reasons, Python is well suited for education at all levels.

The workshop will bring together researchers and practitioners 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, and to share experiences using Python in scientific computing
education.

The overarching theme of the workshop is productivity vs. performance
in HPC and scientific programming. While Python is extremely strong in
supporting human productivity as well reproducible science, it still
lacks in computational performance compared to ‘traditional’ HPC
languages such as Fortran or C. For the workshop, we encourage authors
to submit novel research in improving performance of Python
applications as well as research on productivity of development with
Python.

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, or education:

* Big Data and Data Science with Python
* 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 HPC applications using Jupyter
* High performance computing applications with Python
* Performance analysis, profiling, and debugging of Python code
* Administration of large HPC systems with Python
* Scientific and interactive visualization with Python
* Problem solving environments and frameworks
* Diversity and education in HPC and scientific computing

SUBMISSION

We invite you to submit a paper of up to 10 pages via the submission
site: https://easychair.org/conferences/?conf=pyhpc2017

The formatting instructions are available here: http://www.ieee.org/co
nferences_events/conferences/publishing/templates.html.

You can also use the template online on Overleaf:
https://www.overleaf.com/latex/templates/ieee-demo-template-for-computer-society-conferences/hzzszpqfkqky


IMPORTANT DATES

* Full paper submission: September 1, 2017
* Notification of acceptance: September 18, 2016
* Camera-ready papers: October 9, 2016
* Workshop: November 12, 2017 (Concurrent with SC17)


PROGRAM COMMITTEE

* Achim Basermann, German Aerospace Center, Germany
* Yung-Yu Chen, Synopsys, Inc., Taiwan
* Cyrus Harrison, Lawrence Livermore National Laboratory, USA
* Konrad Hinsen, Centre de Biophysique Moléculaire, CNRS Orléans, France
* Michael Klemm, Intel, Inc., Germany
* Guy K. Kloss, Qrious Ltd., New Zealand
* Maurice Ling, Nanyang Technological University, Singapore
* Sergey Maidanov, Intel, Inc., USA
* Karen Ng, Intel, Inc., USA
* Shilpika, Argonne National Laboratory, USA
* Mike Müller, Python Academy, Germany
* Massimo Di Pierro, DePaul University, USA
* Matthew Turk, Columbia University, USA
* Jake VanderPlas, University of Washington, USA

WORKSHOP ORGANIZERS

* Andreas Schreiber, German Aerospace Center (DLR), Germany
* William Scullin, Argonne National Laboratory, USA
* Bill Spotz, Sandia National Laboratories, USA
* Rollin Thomas, Lawrence Berkeley National Laboratory, USA


CONTACT

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

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