WORKS 2017

From ConfIDent
Revision as of 14:26, 19 October 2022 by WikiSysop (talk | contribs) (Text replacement - "Homepage=" to "Official Website=")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Denver, Colorado, United States of America

Loading map...
              • WORKS 2017 Workshop *******

Workflows in Support of Large-Scale Science Workshop Monday, 13 November 2017, Denver, Colorado, USA. Held in conjunction with SC17, 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 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

Cookies help us deliver our services. By using our services, you agree to our use of cookies.