• Call For Papers (Final deadline extension: September 6, 2020)

    From hoangnguyen177@gmail.com@21:1/5 to All on Sat Sep 5 14:35:48 2020
    Call For Papers (Final deadline extension: September 6, 2020)

    15th Workshop on Workflows in Support of Large-Scale Science (WORKS20)

    to be held in conjunction with SC 2020 and in cooperation with IEEE TCHPC November 11, Online event

    https://works-workshop.org ========================================================================

    Important Dates
    Full paper deadline: September 6, 2020 Paper acceptance notification: September 30, 2020 E-copyright registration completed by authors: October 5, 2020 Camera-ready deadline: October 5, 2020 Workshop: November 11, 2020 – Online event

    Submission Guidelines:
    Submissions are limited to 8 pages in the IEEE format (see https://www.ieee.org/conferences/publishing/templates.html). The 8-page limit includes figures, tables, appendices, and references. WORKS papers this year will be published in cooperation with
    TCHPC and will be available from IEEE digital repository.

    All submitted papers will undergo a rigorous review process and each will have at least three reviews by members of the program committee. Papers will be accepted based on their technical contributions.

    Workshop Description:

    Scientific workflows have been almost universally used across scientific domains and have underpinned some of the most significant discoveries of the past several decades. Workflow management systems (WMSs) provide abstraction and automation which enable
    a broad range of researchers to easily define sophisticated computational processes and to then execute them efficiently on parallel and distributed computing systems. As workflows have been adopted by a number of scientific communities, they are
    becoming more complex and require more sophisticated workflow management capabilities. A workflow now can analyze terabyte-scale data sets, be composed of one million individual tasks, require coordination between heterogeneous tasks, manage tasks that
    execute for milliseconds to hours, and can process data streams, files, and data placed in object stores. The computations can be single core workloads, loosely coupled computations, or tightly all within a single workflow, and can run in dispersed
    computing platforms.

    This workshop focuses on the many facets of scientific 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: scientific workflows representation and enactment; workflow scheduling techniques to optimize the execution of the workflow on heterogeneous 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.

    WORKS20 will be held in conjunction with the SuperComputing (SC20).


    WORKS20 welcomes original submissions in a range of areas, including but 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
    * In Situ Data Analytics Workflows
    * Interactive workflows (including workflow steering)
    * Workflow fault-tolerance and recovery techniques
    * Workflow user environments, including portals
    * Workflow applications and their requirements
    * Workflow optimizations (including scheduling and energy efficiency)
    * Performance analysis of workflows
    * Workflow debugging
    * Workflow provenance
    * Machine Learning workflows

    Papers should present original research and should provide sufficient background material to make them accessible to the broader community.


    Organizing Committee
    - Rafael Ferreira da Silva, University of Southern California, USA
    - Rosa Filgueira, University of Edinburgh, UK

    General Chair
    - Ian Taylor, Cardiff University, UK, University of Notre Dame, USA

    Steering Committee
    - David Abramson, University of Queensland, Australia
    - Malcolm Atkinson, University of Edinburgh, UK
    - Ewa Deelman, University of Southern California, USA
    - Michela Taufer, University of Tennessee

    Publicity Chair
    - Hoang Anh Nguyen, University of Queensland, Australia

    Program Committee
    - Pinar Alper – King's College London, UK
    - Ilkay Altintas – SDSC, USA
    - Khalid Belhajjame Universit. Paris-Dauphine, France
    - Ivona Brandic – TU Wien, Austria
    - Silvina Caino-Lores - University of Tennessee, USA
    - Henri Casanova – University of Hawaii at Manoa, USA
    - Thomas Fahringer - University of Innsbruck
    - Rafael Ferreira da Silva – USC/ISI, USA
    - Daniel Garijo – USC/ISI, USA
    - Sandra Gesing – University of Notre Dame, USA
    - Tristan Glatard – Concordia University, Canada
    - Daniel Katz – UIUC, USA
    - Anirban Mandal – RENCI, USA
    - Maciej Malawski, AGH, Poland
    - Marta Mattoso – UFRJ, Brazil
    - Loic Pottier - USC/ISI, USA
    - Radu Prodan – University of Klagenfurt, Austria
    - Ivan Rodero – Rutgers University, USA
    - Rizos Sakellariou – University of Manchester, UK
    - Renan Souza – IBM Research, Brazil
    - Frédéric Suter – CNRS, France
    - Domenico Talia – University of Calabria, Italy
    - Douglas Thain – University of Notre Dame, USA
    - Chase Wu – NJ Institute of Technology, USA

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