[hpc-announce] CFP: The 23nd International ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC) 2014

Ioan Raicu iraicu at cs.iit.edu
Sat Dec 7 13:40:08 CST 2013

			**** CALL FOR PAPERS ****

                  The 23nd International ACM Symposium on
           High-Performance Parallel and Distributed Computing

                Vancouver, Canada - June 23-27, 2014


The ACM International Symposium on High-Performance Parallel and Distributed Computing
(HPDC) is the premier annual conference for presenting the latest research on the
design, implementation, evaluation, and application of parallel and distributed systems
for high-end computing.

In 2014, the 23nd HPDC and affiliated workshops will take place in the beautiful city
of Vancouver, Canada during June 23-27, 2014.

Abstracts Due:          January 20, 2014
Papers Due:             January 27, 2014 (no extensions)
Author Rebuttal:        March 14-18, 2014
Author Notifications:   March 28, 2014

Submissions are welcomed on high-performance parallel and distributed computing topics
including but not limited to: clouds, clusters, grids, Big Data, massively multicore,
and global-scale computing systems. New scholarly research showing empirical and
reproducible results in architectures, systems, and networks is strongly encouraged,
as are experience reports of operational deployments that can provide insights for
future research on HPDC applications and systems. All papers will be evaluated for
their originality, technical depth and correctness, potential impact, relevance to the
conference, and quality of presentation. Research papers must clearly demonstrate
research contributions and novelty, while experience reports must clearly describe
lessons learned and demonstrate impact.

In the context of high-performance parallel and distributed computing, the topics of
interest include, but are not limited to:

o	Systems, networks, and architectures for high-end computing
o	Massively multicore systems
o	Resource virtualization
o	Programming languages and environments
o	I/O, storage systems, and data management
o	Resource management and scheduling, including energy-aware techniques
o	Performance modeling and analysis
o	Fault tolerance, reliability, and availability
o	Data-intensive computing
o	Applications of parallel and distributed computing

Authors are invited to submit technical papers of at most 12 pages in PDF format,
including figures and references. Papers should be formatted in the ACM Proceedings
Style (http://www.acm.org/sigs/publications/proceedings-templates) and submitted via the
conference web site. No changes to the margins, spacing, or font sizes as specified by
the style file are allowed. Accepted papers will appear in the conference proceedings,
and will be incorporated into the ACM Digital Library. A limited number of papers will
be accepted as posters.

Papers must be self-contained and provide the technical substance required for the
program committee to evaluate their contributions. Papers should thoughtfully address
all related work, particularly work presented at previous HPDC events. Submitted
papers must be original work that has not appeared in and is not under consideration
for another conference or a journal. See the ACM Prior Publication Policy
(http://www.acm.org/publications/policies/sim_submissions) for more details.

Beth Plale, Indiana University
Matei Ripeanu, University of British Columbia

Franck Cappello, Argonne National Lab and INRIA
Dongyan Xu, Purdue University

Ioan Raicu, Illinois Institute of Technology, USA

David Abramson, University of Queensland, Australia
Gabriel Antoniu, INRIA, France
Henri Bal, Vrije Universiteit, the Netherlands
Adam Barker, University of St Andrews, UK
Michela Becchi, University of Missouri - Columbia, USA
Greg Bronevetsky, Lawrence Livermore National Laboratory, USA
Ali Butt, Virginia Tech, USA
Abhishek Chandra, University of Minnesota, USA
Andrew Chien, University of Chicago and Argonne National Laboratory, USA
Paolo Costa, Microsoft Research Cambridge, UK
Dilma Da Silva, Qualcomm Research Silicon Valley, USA
Peter Dinda, Northwestern University, USA
Dick Epema, Delft and Eindhoven University of Technology, the Netherlands
Gilles Fedak, INRIA, France
Wu-chun Feng, Virginia Tech, USA
Renato Figueiredo, University of Florida, USA
Ian Foster, University of Chicago and Argonne National Laboratory, USA
Kartik Gopalan, Binghamton University, USA
Haryadi Gunawi, University of Chicago, USA
Bingsheng He, Nanyang Technological University, Singapore
Alexandru Iosup, Delft University of Technology, the Netherlands
Shantenu Jha, Rutgers University, USA
Hai Jin	Huazhong, University of Science and Technology, China
Larry Kaplan, Cray, Inc., USA
Kate Keahey, Argonne National Laboratory, USA
Thilo Kielmann, Vrije Universiteit, the Netherlands
Charles Killian, Google, USA
Zhiling Lan, Illinois Institute of Technology, USA
John (Jack) Lange, University of Pittsburgh, USA
Minglu Li, Shanghai Jiaotong University, China
Barney Maccabe, Oak Ridge National Laboratory, USA
Naoya Maruyama, RIKEN Advanced Institute for Computational Science, Japan
Satoshi Matsuoka, Tokyo Institute of Technology, Japan
Dejan Milojicic, HP Labs, USA
Bogdan Nicolae, IBM Research, Ireland
Sangmi Pallickara, Colorado State University, USA
Manish Parashar, Rutgers University, USA
Ioan Raicu, Illinois Institute of Technology, USA
Prasenjit Sarkar, IBM Research, USA
Daniele Scarpazza, D.E. Shaw Research, USA
Karsten Schwan, Georgia Institute of Technology, USA
Martin Swany, Indiana University, USA
Michela Taufer, University of Delaware, USA
Kenjiro Taura, University of Tokyo, Japan
Douglas Thain, University of Notre Dame, USA
Bhuvan Urgaonkar, Pennsylvania State University, USA
Mustafa Uysal, VMware, Inc., USA
Jon Weissman, University of Minnesota, USA
Ming Zhao, Florida International University, USA

Henri Bal, Vrije Universiteit
Andrew A. Chien, University of Chicago
Peter Dinda, Northwestern University
Dick Epema, Delft University of Technology
Renato Figueiredo, University of Florida
Ian Foster, Univ. of Chicago and Argonne National Laboratory
Salim Hariri, University of Arizona
Thilo Kielmann, Vrije Universiteit Amsterdam
Arthur "Barney" Maccabe, Oak Ridge National Laboratory
Manish Parashar, Rutgers University
Matei Ripeanu, University of British Columbia
Karsten Schwan, Georgia Tech
Doug Thain, University of Notre Dame
Jon Weissman, University of Minnesota (Chair)

Ioan Raicu, Ph.D.
Assistant Professor, Illinois Institute of Technology (IIT)
Guest Research Faculty, Argonne National Laboratory (ANL)
Data-Intensive Distributed Systems Laboratory, CS/IIT
Distributed Systems Laboratory, MCS/ANL
Editor: IEEE TCC, Springer Cluster, Springer JoCCASA
Chair:  IEEE/ACM MTAGS, ACM ScienceCloud
Cel:      1-847-722-0876
Office:   1-312-567-5704
Email:    iraicu at cs.iit.edu
Web:      http://www.cs.iit.edu/~iraicu/
Web:      http://datasys.cs.iit.edu/
LinkedIn: http://www.linkedin.com/in/ioanraicu
Google:   http://scholar.google.com/citations?user=jE73HYAAAAAJ

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