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Scope of the workshop:
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Call for papers:
PABS 2017
(http://ripsac.web2labs.net/
3rd International Workshop on Performance Analysis of
Big data Systems (PABS)
April 22, 2017
L’AQUILA, Italy
to be held in conjunction with
International conference on Performance Engineering (ICPE)-2017
(http://ripsac.web2labs.net/
3rd International Workshop on Performance Analysis of
Big data Systems (PABS)
April 22, 2017
L’AQUILA, Italy
to be held in conjunction with
International conference on Performance Engineering (ICPE)-2017
Scope of the workshop:
The workshop on performance analysis
of big data systems (PABS) aims at providing a platform for scientific
researchers, academicians and practitioners to discuss techniques, models,
benchmarks, tools, case studies and experiences while dealing with performance
issues in traditional and big data systems. The primary objective is to
discuss performance bottlenecks and improvements during big data analysis
using different paradigms, architectures and big data technologies. We
propose to use this platform as an opportunity to discuss systems, architectures,
tools, and optimization algorithms that are parallel in nature and hence
make use of advancements to improve the system performance. This workshop
shall focus on the performance challenges imposed by big data systems and
on the different state-of-the-art solutions proposed to overcome these
challenges. The accepted papers shall be published in ACM proceedings and
digital library.
Topics
=====-----=====-----=====Topics
All novel performance
analysis or prediction techniques, benchmarks, architectures, models and
tools for data-intensive computing system for optimizing application performance
on cutting-edge high performance solutions are of interest to the workshop.
Examples of topics include but not limited to:
· Performance analysis and optimization of Big data systems and technologies.
· Big data analytics using machine learning
· In-memory analysis of big data
· Performance Assured migration of traditional systems to Big data platforms
· Deployment of Big Data technology/application on High performance computing architectures.
· Case studies/ Benchmarks to optimize/evaluate performance of Big data applications/systems and Big data workload characterizations.
· Tools or models to identify performance bottlenecks and /or predict performance metrics in Big data
· Performance analysis while querying, visualization and processing of large network datasets on clusters of multicore, many core processors, and accelerators.
· Performance issues in heterogeneous computing for Big data architectures.
· Analysis of Big data applications in science, engineering, finance, business, healthcare and telecommunication etc.
· Data structure and algorithms for performance optimizations in Big data systems.
· Data intensive computing
· Tools for big data analytics and management
Important Dates
· January 17, 2017 - Submissions due
· February 10, 2017 - Notification of acceptance
· February 17, 2017 - Camera-ready copies due
· April 22, 2017 - Workshop date
· Performance analysis and optimization of Big data systems and technologies.
· Big data analytics using machine learning
· In-memory analysis of big data
· Performance Assured migration of traditional systems to Big data platforms
· Deployment of Big Data technology/application on High performance computing architectures.
· Case studies/ Benchmarks to optimize/evaluate performance of Big data applications/systems and Big data workload characterizations.
· Tools or models to identify performance bottlenecks and /or predict performance metrics in Big data
· Performance analysis while querying, visualization and processing of large network datasets on clusters of multicore, many core processors, and accelerators.
· Performance issues in heterogeneous computing for Big data architectures.
· Analysis of Big data applications in science, engineering, finance, business, healthcare and telecommunication etc.
· Data structure and algorithms for performance optimizations in Big data systems.
· Data intensive computing
· Tools for big data analytics and management
Important Dates
· January 17, 2017 - Submissions due
· February 10, 2017 - Notification of acceptance
· February 17, 2017 - Camera-ready copies due
· April 22, 2017 - Workshop date
Submission details
Submissions describing original, unpublished recent results related to the workshop theme, upto 6
pages in standard ACM format can be submitted through the easychair conference system, following
this link: https://easychair.org/
available on ICPE 2017 web page. Accepted technical papers will be published in the ICPE 2016
Proceedings. In case of any difficulty please contact rekha.singhal@tcs.com or d.chahal@tcs.com.
The submissions must be in pdf format.
Program Co-Chairs:
· Rekha Singhal, TCS Research, India (rekha.singhal@tcs.com)
· Dheeraj Chahal, TCS Research, India (d.chahal@tcs.com)
Technical Program committee:
· Amy Apon, Clemson University, USA
· Dhableshwar Panda, Ohio State University , USA
· Gautam Shroff, TCS Innovation Lab, India
· Kishor Trivedi, Duke University, USA
· Rajesh Mansharamani, Consultant, India
· Jeff Ullman, Stanford University and Gradiance, USA
· Saumil Merchant, Shell, India
· Sebastien Goasguen, Citrix, Switzerland
· Steven J Stuart, Clemson University, USA
· Vikram Goyal, IIIT, India
· Tilmann Rabl, DIMA, Toronto, Canada
Thanks and Regards,
Dheeraj Chahal, PhD
Sr. Scientist,
Tata Consultancy Services Research,
Akruti Business Port, Road No. 13,
MIDC, Andheri East
Mumbai - 400093,Maharashtra
India
Submissions describing original, unpublished recent results related to the workshop theme, upto 6
pages in standard ACM format can be submitted through the easychair conference system, following
this link: https://easychair.org/
available on ICPE 2017 web page. Accepted technical papers will be published in the ICPE 2016
Proceedings. In case of any difficulty please contact rekha.singhal@tcs.com or d.chahal@tcs.com.
The submissions must be in pdf format.
Program Co-Chairs:
· Rekha Singhal, TCS Research, India (rekha.singhal@tcs.com)
· Dheeraj Chahal, TCS Research, India (d.chahal@tcs.com)
Technical Program committee:
· Amy Apon, Clemson University, USA
· Dhableshwar Panda, Ohio State University , USA
· Gautam Shroff, TCS Innovation Lab, India
· Kishor Trivedi, Duke University, USA
· Rajesh Mansharamani, Consultant, India
· Jeff Ullman, Stanford University and Gradiance, USA
· Saumil Merchant, Shell, India
· Sebastien Goasguen, Citrix, Switzerland
· Steven J Stuart, Clemson University, USA
· Vikram Goyal, IIIT, India
· Tilmann Rabl, DIMA, Toronto, Canada
Thanks and Regards,
Dheeraj Chahal, PhD
Sr. Scientist,
Tata Consultancy Services Research,
Akruti Business Port, Road No. 13,
MIDC, Andheri East
Mumbai - 400093,Maharashtra
India
Notice: The information contained in this e-mail
message and/or attachments to it may contain
confidential or privileged information. If you are
not the intended recipient, any dissemination, use,
review, distribution, printing or copying of the
information contained in this e-mail message
and/or attachments to it are strictly prohibited. If
you have received this communication in error,
please notify us by reply e-mail or telephone and
immediately and permanently delete the message
and any attachments. Thank you
******************************
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