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[HTCondor-users] CFP: 12th Workflows in Support of Large-Scale Science (WORKS) Workshop



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********** WORKS 2017 Workshop **********
Workflows in Support of Large-Scale Science Workshop
http://works.cs.cardiff.ac.uk/
Monday 13 November 2017, Denver, Colorado, USA.
Held in conjunction with SC17, http://sc17.supercomputing.org/
Paper submission deadline: 30 July 2017

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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