(apologies for cross-postings)
DEADLINE: PDSEC-16: papers due Jan 08
The 17th IEEE International Workshop on Parallel and Distributed Scientific
and Engineering Computing, May 27, 2016, Chicago USA
to be held in conjunction with IPDPS 2016. http://cse.stfx.ca/~pdsec16
Scope and Interests:
The technological trends of HPC systems imposes more burdens to
application developers to manage unprecedented complexity of the
systems and their performance characteristics. The existing
application code may not perform well on these systems without large
modifications. A complete rewrite may be required to utilize
multiple levels of parallelism, novel I/O technology, power capping
and system-wide temporal/spatial performance heterogeneity. The HPC
community has developed new programming models, algorithms,
libraries and tools to meet these new challenges to accommodate
productive code development and effective system use. However, the
application community still needs to identify the benefit through
practical evaluations. This year, we will shift the focus of PDSEC
to methodologies and experiences of scientific and engineering
applications and algorithms to identify sustainable code development
for better productivity and application performance.
In particular we will focus on the following topics in parallel and
distributed scientific and engineering applications, but not limited
to:
* Code modernization methodologies and experiences for adapting the
changes in future computing systems such as porting of legacy
simulation code and libraries/tools to facilitate porting and code
refactoring.
* Application and algorithm development of various parallel and
distributed programming models/framework such as CAF, UPC, Chapel,
X10, Charm++, HPX, Uintah, Legion, etc. We appreciate the
experiences of early adaptors of new programming models and
platforms.
* Experience in new tools and libraries for effective application
development, including performance tools, application development
frameworks, Domain Specific Languages (DSL), etc.
* Use cases of enterprise distributed computing technology (such as
MapReduce, Data Analytics and Machine-learning tools) in scientific
and engineering applications
* Tools and techniques to support spatial/temporal performance
heterogeneity and resiliency for emerging extreme-scale systems.
* Large-scale parallel and distributed algorithms supporting
science and engineering applications.
* Methodologies and experiences in developing large-scale applications.
Important Dates:
Paper submission due . . . . . . . . . . . . . . January 08, 2016
Notification of Acceptance . . . . . . . . . . . February 17, 2016
Final camera-ready paper . . . . . . . . . . . . TBA
General Chairs
Peter Strazdins, Australian National University, Australia
Raphael Couturier, University of Franche-Comte, France
Program Chairs
Keita Teranishi, Sandia National Laboratories, USA
Alan Gray, University of Edinburgh, United Kingdom
Steering Committee
Thomas Rauber, University of Bayreuth, Germany
Gudula Runger, Chemnitz University of Technology, Germany
Laurence T. Yang (Chair), St. Francis Xavier University, Canada
--
Regards, Peter
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Peter Strazdins, PhD
Research School of Computer Science
ANU College of Engineering and Computer Science
CSIT Building 108, North Rd
The Australian National University, Canberra ACT 2601 AUSTRALIA
T: +61 2 6125 5140 F: +61 2 6125 0010
W: http://cs.anu.edu.au/~Peter.
E: Peter.Strazdins@cs.anu.edu.au
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