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

[Jose Moreira]

CALL FOR PAPERS

2nd Workshop on Parallel Programming for Analytics Applications 
to be held during the 20th 
ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
February 7-11, 2015
San Francisco, California

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

Important Dates

Nov 24th, 2014: Paper submission deadline.
Jan 10th, 2015: Decision on refereed papers.
Jan 24th, 2015: Camera ready copies due. Accepted papers will be published 
in the ACM digital library after the workshop.
Feb 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:

* 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
* 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
* 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
* 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
* 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 here. 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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