[hpc-announce] Call for Papers: 2nd Workshop on Parallel Programming for Analytics Applications at PPoPP 2015

[Jose Moreira]

2nd Workshop on Parallel Programming for Analytics Applications 
at the 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel 
Programming

https://sites.google.com/site/2015ppaa/

February 7-11, 2015
San Francisco, California

Important Dates

November 24th, 2014: Paper submission deadline.
January 10th, 2015: Decision on refereed papers.
January 24th, 2015: Camera ready copies due. Accepted papers will be 
published in the ACM digital library after the workshop.
February 7th or 8th, 2015: Workshop!

Motivation and Scope

Analytics applications are scaling rapidly in terms of the size and 
variety of data analyzed, the complexity of models explored and tested, 
and the number of analytics professionals or data scientists supported 
concurrently.  Consumer behavior modeling, IT infrastructure security and 
resiliency, and fraud detection and prevention are examples of application 
areas where the scaling is stressing the computational capabilities of 
current systems.  At the same time hardware systems are embracing new 
technologies like on-chip and off-chip accelerators, vector extensions to 
the instruction sets, and solid state disks.  New programming 
methodologies and run-times to support them are emerging to facilitate the 
development of the new analytics applications, and to leverage the 
emerging systems.  This workshop provides a forum for the applications 
community, run-time and development-environment community,and systems 
community to exchange the outlook for progress in each of these areas, and 
exchange ideas on how to cross leverage the progress. Topics of interest 
include, but are not limited to:

o System and hardware support for big data analytics
  - Exploitation of GPUs, FPGAs and on-chip vector processing units for 
analytics applications
  - Efficient exploitation of the memory hierarchy, particularly solid 
state disks
  - Parallel I/O to support distributed file systems
  - System management issues for attaining the desired levels of 
reliability and performance for the above
o Parallel run-times and middleware for analytics
  - Columnar databases, large data warehouses, data cubes and OLAP engines
  - In memory analysis for real-time queries on large data
  - No-SQL databases
  - Graph databases
  - Concurrency in large tabular data analytics
  - Distributed file systems
o Parallel programming models and languages, and application development 
frameworks for analytics
  - Application Frameworks for large graph applications 
  - Computational models and programming languages for large graph 
applications
  - Domain specific languages for analytics
o Parallel algorithms for large graphs and other big data analytics 
applications
  - Algorithms to exploit the hardware, run-times, middleware and 
programming models listed above
  - Performance attainable on the hardware, run-times, middleware and 
programming models listed above
o Parallelism in Social Media and other big dataapplications
  - Applications in consumer modeling and customer behavior 
  - Financial fraud detection and intrusion detection in IT infrastructure
  - Applications in healthcare and other industries
  - Analytics applications and solutions in homeland security

Submission Guidelines

Submitted papers should be no longer than 8 pages using a 10 point font 
(single spaced). Authors are encouraged to use the ACM double column 
format found at "http://www.sigplan.org/Resources/Author/". Papers should 
be submitted in PDF format and should be legible when printed on a 
black-and-white printer. To submit, send email to: manoj1 at us.ibm.com and 
joefon at us.ibm.com with the paper included as an attachment. Accepted 
papers will be published in the ACM digital library after the workshop.

General Co-Chairs

Joefon Jann, IBM Research (joefon at us.ibm.com)
Jose Moreira, IBM Research (jmoreira at us.ibm.com)

Program Committee

Manoj Kumar - Program Chair, IBM Research (manoj1 at us.ibm.com)
Gianfranco Bilardi, University of Padua, Italy
Daniel Delling, Microsoft Research
Vijay Gadeapply, MIT Lincoln Labs
Jeremy Kepner, MIT Lincoln Labs
Ching-Yung Lin, IBM Research
Silvius Rus, Cloudera
Vivek Sarkar, Rice University
Fernando Silva, University of Porto, Portugal

José E. Moreira
Research Staff Member
Future POWER Systems Concept Team
IBM Thomas J. Watson Research Center
Yorktown Heights NY 10598-0218
phone: 1-914-945-1709, fax: 1-914-945-4425
e-mail: jmoreira at us.ibm.com
URL: http://www.research.ibm.com/people/m/moreira
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