-------- Weitergeleitete Nachricht --------
Betreff: [computational.science] CFP: 12th Workflows in Support of Large-Scale Science (WORKS) Workshop
Datum: Tue, 6 Jun 2017 11:38:38 +0300
Von: Ilia Pietri <ipietri@di.uoa.gr>
An: computational.science@lists.iccsa.org


******* WORKS 2017 Workshop *******

Workflows in Support of Large-Scale Science Workshop

Monday, 13 November 2017, Denver, Colorado, USA.

Held in conjunction with SC1 <http://sc17.supercomputing.org/>7, The
International Conference for High Performance Computing, Networking,
Storage and Analysis

http://works.cs.cardiff.ac.uk/

Paper submission deadline: 30 July 2017
*************************************



Call For Papers



Data-intensive workflows (a.k.a. scientific workflows) are routinely used
in most scientific disciplines today, especially in the context of
high-performance, parallel and distributed computing. They provide a
systematic way of describing a complex scientific process and rely on
sophisticated workflow management systems to execute on a variety of
parallel and distributed resources. With the dramatic increase of raw data
volume in every domain, they play an even more critical role to assist
scientists in organizing and processing their data and to leverage HPC or
HTC resources, being at the interface between end-users and computing
infrastructures.



This workshop focuses on the many facets of data-intensive workflow
management systems, ranging from actual execution to service management and
the coordination and optimization of data, service and job dependencies.
The workshop covers a broad range of issues in the scientific workflow
lifecycle that include: data-intensive workflows representation and
enactment; designing workflow composition interfaces; workflow mapping
techniques to optimize the execution of the workflow for different
infrastructures; workflow enactment engines that need to deal with failures
in the application and execution environment; and a number of computer
science problems related to scientific workflows such as semantic
technologies, compiler methods, scheduling and fault detection and
tolerance.



The topics of the workshop include but are not limited to:

       Big Data analytics workflows

       Data-driven workflow processing (including stream-based workflows)

       Workflow composition, tools, and languages

       Workflow execution in distributed environments (including HPC,
clouds, and grids)

       Reproducible computational research using workflows

       Dynamic data dependent workflow systems solutions

       Exascale computing with workflows

       Workflow fault-tolerance and recovery techniques

       Workflow user environments, including portals

       Workflow applications and their requirements

       Adaptive workflows

       Workflow optimizations (including scheduling and energy efficiency)

       Performance analysis of workflows

       Workflow debugging

       Workflow provenance

       Interactive workflows (including workflow steering)


*************************************

Paper Submission


Important Dates

       Papers Due: 30 July 2017

       Notifications of Acceptance: 9 September 2017

       E-copyright registration completed by authors: 1 October 2017

       Final Papers Due: 1 October, 2017



The paper must be at most 10 pages long. The proceedings should be
formatted according to http://www.acm.org/publications/proceedings-template.
WORKS papers this year will be published in collaboration with SIGHPC and
will be available from both ACM and IEEE digital repositories.


*************************************

WORKS 2017 Organizing Committee



– PC Chairs

   Sandra Gesing, University of Notre Dame, USA

   Rizos Sakellariou, University of Manchester, UK



– General Chairs

   Johan Montagnat, French National Center for Scientific Research (CNRS),
Sophia Antipolis, France

   Ian Taylor, Cardiff University, UK and University of Notre Dame, USA



– Steering Committee

   David Abramson, University of Queensland, Australia

   Malcolm Atkinson, University of Edinburgh, UK

   Ewa Deelman, USC, USA

   Michela Taufer, University of Delaware, USA



– Publicity Chairs

   Rafael Ferreira da Silva, USC, USA

   Ilia Pietri, University of Athens, Greece


*************************************

WORKS 2017 Program Committee



Pinar Alper, King's College London, UK

Ilkay Altintas, San Diego Supercomputer Center, USA

Khalid Belhajjame, Université Paris-Dauphine, France

Adam Belloum, University of Amsterdam, the Netherlands

Ivona Brandic, TU Wien, Austria

Kris Bubendorfer, Victoria University of Wellington, New Zealand

Jesus Carretero, Universidad Carlos III de Madrid, Spain

Henri Casanova, University of Hawaii at Manoa, USA

Ewa Deelman, USC Information Sciences Institute, USA

Rafael Ferreira Da Silva, USC Information Sciences Institute, USA

Daniel Garijo, USC Information Sciences Institute, USA

Sandra Gesing, University of Notre Dame, USA

Tristan Glatard, CNRS, France

Daniel Katz, University of Illinois Urbana-Champaign, USA

Tamas Kiss, University of Westminster, UK

Dagmar Krefting, HTW Berlin, Germany

Maciej Malawski, AGH University of Science and Technology, Poland

Anirban Mandal, Renaissance Computing Institute, USA

Marta Mattoso, Federal Univ. Rio de Janeiro, Brazil

Andrew Stephen Mcgough, Newcastle University, UK

Paolo Missier, Newcastle University, UK

Jarek Nabrzyski, University of Notre Dame, USA

Daniel de Oliveira, Fluminense Federal University, Brazil

Ilia Pietri, University of Athens, Greece

Radu Prodan, University of Innsbruck, Austria

Omer Rana, Cardiff University, UK

Ivan Rodero, Rutgers University, USA

Rizos Sakellariou, University of Manchester, UK

Domenico Talia, University of Calabria, Italy

Rafael Tolosana-Calasanz, Universidad de Zaragoza, Spain

Chase Wu, New Jersey Institute of Technology, USA
_______________________________________________
computational.science mailing list
computational.science@lists.iccsa.org
https://lists.iccsa.org/mailman/listinfo/computational.science

Hosted by Sardina Systems: Hyper-Efficient OpenStack Cloud