posted by user: paralllri || 5095 views || tracked by 17 users: [display]

HCW 2010 : HCW 2010: 19th Heterogeneity in Computing Workshop in conjunction with IPDPS 2010

FacebookTwitterLinkedInGoogle

Link: http://graal.ens-lyon.fr/~abenoit/hcw2010
 
When Apr 19, 2010 - Apr 19, 2010
Where Atlanta, Georgia, U.S.A
Submission Deadline Dec 14, 2009
Categories    HPC   distributed system   fault tolerance   parallel computing
 

Call For Papers

-----------------------------------------------------------------------------
HCW 2010: 19th Heterogeneity in Computing Workshop
in conjunction with IPDPS 2010 (www.ipdps.org)
Atlanta, Georgia, U.S.A., April 19, 2010

Sponsored by the IEEE Computer Society, through the Technical Committee on
Parallel Processing (TCPP), and by the U.S. Office of Naval Research (ONR).

http://graal.ens-lyon.fr/~abenoit/hcw2010
-----------------------------------------------------------------------------
Paper submission deadline (5-pages summary): December 14, 2009
-----------------------------------------------------------------------------

Today, most computing systems have elements of heterogeneity. Heterogeneity
springs from the richness of environments where diversity and resource
abundance prevail. Recognizing, capturing, and efficiently exploiting this
diversity in an integrated and coherent manner are key goals of heterogeneous
computing.

Heterogeneous computing systems are those with a range of diverse computing
resources that can be on a chip, within a computer, or on a local or
geographically distributed network. The development of heterogeneous
multi-core
chips and the pervasive use of networks by all segments of society mean that
the number and types of heterogeneous computing resources are growing rapidly.
This growth creates the need and opportunity for new research to effectively
utilize these resources in innovative and novel ways. For example, cluster
computing, grid computing, peer-to-peer computing, and cloud computing all
involve elements of heterogeneity. The effective implementation of efficient
applications in these environments, however, requires that a host of issues be
addressed that simply do not occur in homogeneous systems.

Whereas many researchers and practitioners that use computers have a
peripheral
awareness of heterogeneity in their respective fields, few critically approach
their fields from the heterogeneous perspective. This is not particularly
surprising, because each field has its own unique challenges and imperatives
that propel investigations in search of solutions to pressing problems.
Addressing computing problems from the heterogeneous perspective offers at
least three advantages: (i) the design and development of more advanced
high-performance computing platforms, (ii) insight into new solution
approaches, and (iii) exposure to new research opportunities and relationships
among distinct research areas. HCW encourages the examination of both hardware
and software systems from the perspective of heterogeneity.

With the increasing number of components in heterogeneous parallel and
distributed systems, failure is becoming a critical factor that impacts
application performance. In recent years, there also has been an increasing
interest in robust design in parallel and distributed computing systems that
must operate in an environment full of uncertainties. These uncertainties
could
include task execution times varying with data input sets and resources
dynamically joining and leaving the system. This year, HCW is specifically
encouraging submissions that explore the capabilities of robust and
fault-tolerant systems, paradigms, algorithms, and techniques for
heterogeneous computing.

Areas or research interest include, but are not limited to, heterogeneity
aspects of:
- Robust resource allocation and scheduling
- Fault tolerance
- Control and use of multi-cores
- Computer architectures
- Parallel and distributed computing
- Programming paradigms and tools
- Resource discovery and management
- Task and communication scheduling
- Task coordination and workflow
- Performance evaluation and management
- Cluster computing
- Grid computing
- Cloud computing
- Peer-to-peer computing
- Ubiquitous computing
- Application case studies


IMPORTANT DATES
---------------

Paper submission: December 14, 2009.
Author notification: January 15, 2010.
Camera-ready: February 1, 2010.
Workshop: April 19, 2010.

Updated HCW 2010 information can be found on the workshop webpage:
http://graal.ens-lyon.fr/~abenoit/hcw2010
and also from the workshops link of the IPDPS 2010 web site:
http://www.ipdps.org


HCW 2010 PEOPLE
---------------

GENERAL CHAIR
David A. Bader, Georgia Institute of Technology, U.S.A.

PROGRAM CHAIR
Anne Benoit, Ecole Normale Superieure de Lyon, France

VICE PROGRAM CHAIR for "Robust Scheduling and Fault-Tolerant Techniques"
Qin Zheng, Institute of High Performance Computing, Singapore

STEERING COMMITTEE
H. J. Siegel, Colorado State University, Chair
John K. Antonio, University of Oklahoma
Francine Berman, Rensselaer Polytechnic Institute
Jack Dongarra, University of Tennessee
Jerry Potter, Colorado State University
Viktor K. Prasanna, University of Southern California
Yves Robert, Ecole Normale Superieure de Lyon, France
Arnold Rosenberg, Colorado State University
Vaidy Sunderam, Emory University

PROGRAM COMMITTEE (to be confirmed)
Kento Aida, Tokyo Institute of Technology, Japan
Shoukat Ali, Intel, U.S.A.
Mark Baker, University of Reading, U.K.
Ioana Banicescu, Mississippi State University, U.S.A.
Rajkumar Buyya, University of Melbourne and Manjrasoft, Australia
Shuvra S. Bhattacharyya, University of Maryland, U.S.A.
Wentong Cai, Nanyang Technological University, Singapore
Yves Caniou, ENS Lyon, France
Eddy Caron, ENS Lyon, France
Ralph Castain, Los Alamos National Labs. U.S.A.
Rick Goh, Institute of High Performance Computing, Singapore
Terence Hung, Institute of High Performance Computing, Singapore
Hai Jin, Huazhong University of Science and Technology, China
Zbigniew Kalbarczyk, University of Illinois at Urbana-Champaign, U.S.A.
Alexey Kalinov, Cadence Design Systems, Russia
Tahar Kechadi, University College Dublin, Ireland
Jong-Kook Kim, Korea University, South Korea
Zhiling Lan, Illinois Institute of Technology, U.S.A.
Alexey Lastovetsky, University College Dublin, Ireland
Malcolm Low, Nanyang Technological University, Singapore
Tony Maciejewski, Colorado State University, U.S.A.
John P. Morrison, University College, Cork, Ireland
Kai Nan, Chinese Academy of Sciences, China
Dana Petcu, Western University of Timisoara, Romania
Xiao Qin, Auburn University, U.S.A.
Ioan Raicu, Northwestern University, U.S.A.
Omer Rana, Cardiff University, U.K.
Alistair Rendell, Australian National University, Australia
Uwe Schwiegelshohn, University of Dortmund, Germany
Stephen L. Scott, Oak Ridge National Laboratory, U.S.A.
Martin Swany, University of Delaware, U.S.A.
Gary Toth, Office of Naval Research, U.S.A.
Denis Trystram, IMAG, France
Putchong Uthayopas, Kasetsart University, Thailand
Carlos Varela, Rensselaer Institute, U.S.A.
Bharadwaj Veeravalli, National University of Singapore, Singapore
Cho-Li Wang, Hong Kong University, Hong Kong
Cheng-Zhong Xu, Wayne State University, U.S.A.

Related Resources

CCVPR 2024   2024 International Joint Conference on Computer Vision and Pattern Recognition (CCVPR 2024)
ISPDC 2024   23rd International Symposium on Parallel and Distributed Computing
IPDPS 2024   International Parallel and Distributed Processing Symposium
OpenSuCo @ ISC HPC 2017   2017 International Workshop on Open Source Supercomputing
PCDS 2024   The 1st International Symposium on Parallel Computing and Distributed Systems
ICBICC 2024   2024 International Conference on Big Data, IoT, and Cloud Computing (ICBICC 2024)
PPAM 2024   15th International Conference on Parallel Processing & Applied Mathematics
CCBDIOT 2024   2024 3rd International Conference on Computing, Big Data and Internet of Things (CCBDIOT 2024)
ISCMI 2024   2024 11th International Conference on Soft Computing & Machine Intelligence (ISCMI 2024)
WAML-HPC 2024   2nd Workshop on Applications of Machine Learning and Artificial Intelligence in High-Performance Computing