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/
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@us.ibm.com and joefon@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@us.ibm.com)
Jose Moreira, IBM Research (jmoreira@us.ibm.com)
Program Committee
Manoj Kumar - Program Chair, IBM Research (manoj1@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@us.ibm.com
URL: http://www.research.ibm.com/
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/
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@us.ibm.com and joefon@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@us.ibm.com)
Jose Moreira, IBM Research (jmoreira@us.ibm.com)
Program Committee
Manoj Kumar - Program Chair, IBM Research (manoj1@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@us.ibm.com
URL: http://www.research.ibm.com/
No comments:
Post a Comment