[hpc-announce] Deadline Extended: CFP: 12th Workflows in Support of Large-Scale Science (WORKS) Workshop

Rafael Ferreira da Silva rafsilva at isi.edu
Thu Jul 27 13:28:10 CDT 2017


******* WORKS 2017 Workshop *******
Workflows in Support of Large-Scale Science Workshop
Monday, 13 November 2017, Denver, Colorado, USA.
Held in conjunction with SC17, The International Conference for High Performance Computing, Networking, Storage and Analysis
http://works.cs.cardiff.ac.uk/
Paper submission deadline: 13 August 2017 (EXTENDED)
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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)

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Paper Submission

Important Dates
        Papers Due: 13 August 2017 (EXTENDED)
        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.

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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

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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


--
Rafael Ferreira da Silva, Ph.D.
Research Assistant Professor, USC Computer Science Department
Computer Scientist, USC Information Sciences Institute
http://rafaelsilva.com


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