******* 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)
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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.
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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