[hpc-announce] ScalA at SC20 - Deadline Extension: Papers due September 8

[Engelmann, Christian]

We apologize if you receive multiple copies of this notice.
The submission deadline has been extended to September 8, 2020.

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           ScalA20: 11th Workshop on Latest Advances in
           Scalable Algorithms for Large-Scale Systems

                  held in conjunction with the
     SC20: The International Conference on High Performance
           Computing, Networking, Storage and Analysis

     in cooperation with the IEEE Computer Society Technical
        Consortium on High Performance Computing (TCHPC)

               November 12, 2020 --- Virtual Location

      <http://www.csm.ornl.gov/srt/conferences/Scala/2020>

Novel scalable scientific algorithms are needed in order to enable key
science applications to exploit the computational power of large-scale
systems. This is especially true for the current tier of leading petascale
machines and the road to exascale computing as HPC systems continue to scale
up in compute node and processor core count. These extreme-scale systems
require novel scientific algorithms to hide network and memory latency, have
very high computation/communication overlap, have minimal communication, and
have no synchronization points. With the advent of Big Data and AI in the
past few years the need of such scalable mathematical methods and algorithms
able to handle data and compute intensive applications at scale becomes even
more important.

Scientific algorithms for multi-petaflop and exa-flop systems also need to be
fault tolerant and fault resilient, since the probability of faults increases
with scale. Resilience at the system software and at the algorithmic level is
needed as a crosscutting effort. Finally, with the advent of heterogeneous
compute nodes that employ standard processors as well as GPGPUs, scientific
algorithms need to match these architectures to extract the most performance.
This includes different system-specific levels of parallelism as well as
co-scheduling of computation. Key science applications require novel
mathematical models and system software that address the scalability and
resilience challenges of current- and future-generation extreme-scale HPC
systems.

Submission Guidelines
---------------------

Authors are invited to submit manuscripts in English structured as technical
papers at a length of at least 6 letter size (8.5in x 11in) pages and not
exceeding 8 pages, including figures, tables, and references using the IEEE
format for conference proceedings. Reference style files are available at
<http://www.ieee.org/conferences_events/conferences/publishing/templates.html>.

Submitted papers must represent original unpublished research that is not
currently under review for any other conference or journal. Papers not
following these guidelines will be rejected without review and further
action may be taken, including (but not limited to) notifications sent to
the heads of the institutions of the authors and sponsors of the conference.
Submissions received after the due date, exceeding length limit, or not
appropriately structured may also not be considered. Papers should be
submitted electronically at <https://submissions.supercomputing.org>.

All manuscripts will be peer-reviewed and judged on correctness, originality,
technical strength, and significance, quality of presentation, and interest
and relevance to the workshop attendees. Accepted papers will be published
with the IEEE Computer Society as part of the SC20 workshop proceedings in
the IEEE Xplore Digital Library. At least one author of an accepted paper
must register for and present the paper at the workshop. Authors may contact
the workshop program chair, Christian Engelmann at engelmannc at ornl.gov, for
more information.

Transparency and Reproducibility Initiative
-------------------------------------------

As part of a major initiative that aims to increase the level of
reproducibility and replicability of results, ScalA20 invites authors of
technical papers to submit optional appendix information that can promote
better reproducibility of computational results. Authors are highly
encouraged to provide a 2-page Artifact Description Appendix, which will
not count toward the page limit of the submission. Notes:

- 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.

- Appendices should not be used to circumvent the page limit.

Further information about the SC Transparency and Reproducibility Initiative
can be found at <https://sc20.supercomputing.org/submit/transparency-reproducibility-initiative/>.

Important Web Sites
-------------------

- ScalA20 Website: <https://www.csm.ornl.gov/srt/conferences/Scala/2020>
- ScalA20 Submissions: <https://submissions.supercomputing.org>
- SC20 website: <http://sc20.supercomputing.org/>

SC20 Going Virtual
------------------

The Planning Committee has announced that SC20 will be a fully virtual
conference. More details can be found here: <https://sc20.supercomputing.org/2020/07/27/sc20-virtual-event-announced-by-general-chair-christine-e-cuicchi>.

Important Dates
---------------

- Full paper submission: September 8, 2020 (extended, firm)
- Notification of acceptance: October 1, 2020
- Final paper submission (firm): October 11, 2020
- Workshop/conference early registration: TBD
- Workshop: November 12, 2020 (virtual location, 10AM-6:30PM EST, Track 8)

Topics of interest include, but are not limited to:
---------------------------------------------------

- Novel scientific algorithms that improve performance, scalability,
  resilience, and power efficiency
- Porting scientific algorithms and applications to many-core and
  heterogeneous architectures
- Performance and resilience limitations of scientific algorithms and
  applications at scale, including Data Science approaches in dealing
  with Big Data
- Crosscutting approaches (system software and applications) in addressing
  scalability challenges
- Scientific algorithms that can exploit extreme concurrency (e.g. 1 billion
  for exascale by 2023)
- Naturally fault tolerant, self-healing, or fault oblivious scientific
  algorithms
- Programming model and system software support for algorithm scalability
  and resilience (including ones enabling Big Data processing)

Workshop Chairs
---------------

- Vassil Alexandrov, Hartree Centre, Science and Technology Facilities
  Council, UK
- Al Geist, Oak Ridge National Laboratory, USA
- Jack Dongarra, University of Tennessee, Knoxville, USA

Workshop Program Chair
----------------------

- Christian Engelmann, Oak Ridge National Laboratory, USA
  Contact at engelmannc at ornl.gov

Program Committee
-----------------

- Hartwig Anzt, University of Tennessee, Knoxville, USA
- Rick Archibald, Oak Ridge National Laboratory, USA
- Marco Berghoff, Karlsruhe Institute of Technology, Germany
- Hans-Joachim Bungartz, Technical University of Munich, Germany
- Florina M. Ciorba, University of Basel, Switzerland
- James Elliott, Sandia National Laboratories, USA
- Nahid Emad, University of Versailles SQ, France
- Wilfried Gansterer, University of Vienna, Austria
- Yasuhiro Idomura, Japan Atomic Energy Agency, Japan
- Kirk E. Jordan, IBM T.J. Watson Research, USA
- Dieter Kranzlmueller, Ludwig-Maximilians-University Munich, Germany
- Sriram Krishnamoorthy, Pacific Northwest National Laboratory, USA
- Paul Lin, Lawrence Berkeley National Laboratory, USA
- Kengo Nakajima, RIKEN, Japan
- Yves Robert, ENS Lyon, France
- Stuart Slattery, Oak Ridge National Laboratory, USA
- Valerie Taylor, Argonne National Laboratory, USA

--

Christian Engelmann, Ph.D.

Senior R&D Staff Scientist
Computer Science Research Group
Computer Science and Mathematics Division
Oak Ridge National Laboratory

Mail: P.O. Box 2008, Oak Ridge, TN 37831-6173, USA
Phone: +1 (865) 574-3132 / Fax: +1 (865) 576-5491
e-Mail: engelmannc at ornl.gov / Home: www.christian-engelmann.info