[python-hpc] Call for Papers: 8th Workshop on Python for High-Performance and Scientific Computing (PyHPC 2018)

Andreas.Schreiber at dlr.de Andreas.Schreiber at dlr.de
Sun Jul 8 05:55:33 EDT 2018



8th Workshop on Python for High-Performance and Scientific Computing

November 12, 2018, Dallas, TX, USA

In cooperation with TCHPC

Held in conjunction with SC18: The International Conference on High
Performance Computing, Networking, Storage and Analysis



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 and education. While Python is extremely
strong in supporting human productivity as well reproducible science,
pure Python 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.

Please submit papers related any of the following topics:

 * High-Performance Computing, Big Data, and Data Science with Python
 * Hybrid programming and integration with other programming languages
 * Python compared to other languages for HPC and Data Science
 * Python for emerging computing paradigms (e.g., quantum computing, 
   neuromorphic computing, probabilistic and stochastic computing)
 * Interactivity and reproducibility in HPC using Python
 * Performance analysis, profiling, and debugging
 * Administration of large HPC systems
 * Scientific and interactive visualization
 * Problem solving environments and frameworks
 * Diversity and education in HPC and scientific computing


We invite you to submit a paper with at least 8 pages (including
references) via the submission site:

All papers will be published in cooperation with IEEE TCHPC through 
ACM Digital Library and IEEE Xplore.

The formatting instructions are available here: 

You can also use the template online on Overleaf:


For PyHPC 2018, we adopt the following reproducibility approach
according to the model of SC18:

Authors are encouraged to submit an appendix of up to two pages
describing artifacts and any steps taken to increase the trustworthiness
of their results. A paper cannot be disqualified based on information
provided or not provided in this appendix, nor if the appendix is not
available. The availability and quality of an appendix can be used in
ranking a paper. In particular, if two papers are of similar quality,
the existence and quality of the appendices can be part of the
evaluation process.


 * Full paper submission: August 24, 2018
 * Notification of acceptance: September 14, 2018
 * Camera-ready papers: October 5, 2018
 * Workshop: November 12, 2018 (Concurrent with SC18)


 * 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


E-Mail: andreas.schreiber at dlr.de
Twitter: @PythonHPC

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