(CALL FOR PAPERS) PAW-ATM: Parallel Applications Workshop, Alternatives To MPI+

I saw an announcement for this conference. I am not involved, but it may be interesting to the Julia community.


                 Call for Papers

                  PAW-ATM 2021:

         Parallel Applications Workshop,
             Alternatives To MPI+X

    Held in conjunction with SC21, St. Louis, MO




 Architectural hierarchy and heterogeneity makes programming

challenging. In practice, HPC applications tend to be written
using a mix of
programming models—like C++, MPI, CUDA, and/or OpenMP—each of which is
becoming more complex over time. This negatively impacts the costs of
developing, maintaining, and porting HPC applications.

 Meanwhile, alternative HPC programming models strive to improve

things by
raising the level of abstraction; incorporating modern features; and/or
leveraging the respective strengths of programmers, compilers, and
These alternatives take the form of new languages (e.g., Chapel,
XcalableMP), frameworks for large-scale data science (e.g.,
Arkouda, Dask,
Spark), or extensions to existing languages (e.g., Charm++, COMPSs,
Legion, UPC++).

 PAW-ATM is a forum for discussing HPC applications written in

alternatives to
MPI+X. Its goal is to bring together application experts and
proponents of
high-level languages to present concrete example uses of such
describing their benefits and challenges.

 Scope and Aims

 The PAW-ATM workshop aims to serve as a forum for exhibiting parallel
 applications developed using high-level parallel programming models

that serve
as alternatives to MPI+X-based programming. We encourage the
submission of
papers and talks from the community detailing practical
applications written using alternatives to MPI+X, including
characterizations of
scalability and performance, expressiveness and programmability, as
well as any
downsides or areas for improvement in such models. In doing so,
our hope is to
create a setting in which application authors, language designers, and
architects can present and discuss the state of the art in
alternative scalable
programming models while also wrestling with how to increase their
and adoption. Beyond well-established HPC scientific simulations,
we also
encourage submissions exploring artificial intelligence, big data
machine learning, and other emerging application areas.

 Topics of interest include, but are not limited to:

 * Novel application development using high-level parallel

programming languages
and frameworks.

 * Examples that demonstrate performance, compiler optimization,

error checking,
and reduced software complexity.

 * Applications from artificial intelligence, data analytics,

bioinformatics, and
other novel areas.

 * Performance evaluation of applications developed using

alternatives to MPI+X
and comparisons to standard programming models.

 * Novel algorithms enabled by high-level parallel abstractions.

 * Experience with the use of new compilers and runtime environments.

 * Libraries using or supporting alternatives to MPI+X.

 * Benefits of hardware abstraction and data locality on algorithm

 Papers that include description of applications that demonstrate

the use of
alternative programming models will be given higher priority.


 Submissions are solicited in two categories:

 1) Full-length papers presenting novel research results:

   * Full-length papers will be published in the workshop

proceedings (+).
Submitted papers must describe original work that has not
appeared in, nor is
under consideration for, another conference or journal. Papers
shall be eight
(8) pages minimum and not exceed ten (10) including text,
appendices, and
figures. Appendix pages related to the reproducibility initiative
dependencies, namely the Artifact Description (AD) and Artifact
(AE), are not included in the page count.

   + The specific publisher of the proceedings is TBA pending

acceptance of our
proposal to the proceedings publisher.

 2) Extended abstracts summarizing preliminary/published results:

   * Extended abstracts will be evaluated separately and will not be

included in
the published proceedings; they are intended to propose timely
of novel work that will be formally submitted elsewhere at a
later stage,
and/or of already published work that would be of interest to the
audience in terms of topic and timeliness. Extended abstracts
shall not
exceed four (4) pages.

 When deciding between submissions with similar merit, submissions

whose focus
relates more directly to the key themes of the workshop
(application studies,
computing at scale, high-level alternatives to MPI+X) will be given
over those that don’t. In addition, full-length paper submissions
will be given
preference over extended abstracts.

 Submissions shall be submitted through Linklings:

 Submissions must use 10pt font in the IEEE format:
 PAW-ATM follows the reproducibility initiative of SC21.  For more
 information, please refer to:

The 5th Annual Parallel Applications Workshop, Alternatives To MPI+X (PAW-ATM) by sourceryinstitute

 * Karla Morris - Sandia National Laboratories

 * Rosa M. Badia - Barcelona Supercomputing Center
 * Michael Ferguson - Hewlett Packard Enterprise

 * Bill Long - Hewlett Packard Enterprise
 * Sean Treichler - NVIDIA

 * Vicenç Bertran - Barcelona Supercomputing Center
 * Dan Bonachea - Lawrence Berkeley National Laboratory
 * Peter Braam - University of Oxford
 * Harold Castro - Los Andes University (Colombia)
 * Bradford L. Chamberlain - Hewlett Packard Enterprise
 * John Feo - Pacific Northwest National Laboratory
 * Michael Ferguson - Hewlett Packard Enterprise
 * Salvatore Filippone - University of Rome Tor Vergata
 * Fernanda Foertter - The BioTeam, Inc.
 * Max Grossman - Georgia Institute of Technology
 * Hideto Iwashita - HPFPC
 * Daniel S. Katz - University of Illinois, Urbana-Champaign
 * Wonchan Lee - Stanford University
 * Daniele Lezzi - Barcelona Supercomputing Center
 * Bill Long - Hewlett Packard Enterprise
 * Karla Morris - Sandia National Laboratories
 * Irene Moulitsas - Cranfield University
 * Mitsuhisa Sato - RIKEN Advanced Institute for Computational Science
 * Sean Treichler - NVIDIA

 * Bradford L. Chamberlain - Hewlett Packard Enterprise
 * Damian W. I. Rouson - Sourcery Institute
 * Katherine A. Yelick - Lawrence Berkeley National Laboratory