Managing and processing large volumes of data, or “Big Data”, and gaining meaningful insights is a significant challenge facing the distributed computing community; as a consequence, many business are demanding large scale streaming data analytics. This has significant impact in a wide range of domains including health care, bio-medical research, Internet search, finance and business informatics, and scientific computing.
Despite considerable advancements on high performance, large storage, and high computation power, there are challenges in identifying, clustering, classifying, and interpreting of a large spectrum of information.
The purpose of this workshop is to provide a fertile ground for collaboration between research institutions and industries and in analytics, machine learning, and high performance computing.
Topics of interest
High performance data analytics
Machine and deep learning
Data search and representation
Architecture and system design
Cloud-based big data solutions
Authors are invited to submit full papers to the workshop. Full papers must be submitted through the workshop submission site. Full papers should not exceed six double-column pages in ACM SIG alternate style. These limits include figures, tables, and references.
Accepted papers will be published in the workshop proceedings and in the ACM Digital Library (note that authors of these works retain their copyright rights to publish more complete versions later). As per ACM guidelines, at least one of the authors of accepted papers is required to register for the workshop.
Submission Deadline: February 10, 2016
Decision Notification: March 11, 2016
Camera-Ready Copy: March 25, 2016
Roberta Piscitelli, EGI.eu (organizer)
Alessandro Morari, PNNL, US
Efstratios Gavves, University of Amsterdam, NL
Emiliano Mancini, University of Amsterdam, NL
Giovanni Mariani, IBM Research, NL
Marily Nika, Google, UK
Leandro Fiorin, IBM Research, NL
Vito Castellana, PNNL, US
Abhinav Vishnu, PNNL, US
Mahantesh Halappanaver, PNNL, US
Giovanni Beltrame, Ecole Politechnique of Montreal, CA
Reggie Cushing, University of Amsterdam, NL