The 23rd International Heterogeneity in Computing Workshop

In conjunction with the 28th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2014)

May 19, 2014

Phoenix, Arizona USA

Sponsored by the IEEE Computer Society, through the Technical Committee
on Parallel Processing (TCPP)


Heterogeneity is an important property of most modern computing systems. It is a consequence of the richness of current computing environments with their pronounced diversity in resources and requirements. Recognizing and efficiently exploiting this diversity in an integrated and coherent manner are key goals of heterogeneous computing.

On the one hand, heterogeneous computing systems have a range of diverse hardware resources that can be on a chip, within a computer, or on a local or geographically distributed network. Due to the rapid development of heterogeneous multi-core chips and the pervasive use of networks by all segments of society, 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. On the other hand, computing systems are often characterized by a variety of software resources that may or may not be coupled with specific hardware carriers. The effective implementation of efficient applications in these environments requires that a host of new concerns be addressed as these issues 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. However, 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.

Topics

Areas of interest include, but are not limited to:

*Parallel algorithms for heterogeneous and hierarchical systems, including manycores and hardware accelerators (FPGAs, GPUs, etc.)
*Parallel algorithms for efficient problem solving on heterogeneous platforms
*Performance models and their use in the design of parallel and distributed algorithms for heterogeneous platforms
*Programming paradigms and tools for heterogeneous systems
*Paradigms, algorithms, and techniques for failure management in high performance heterogeneous computing systems and applications
*Resource management in heterogeneous systems including allocation and scheduling
*Heterogeneity in computer architectures
*Performance evaluation and management of heterogeneous systems and applications
*Different computing paradigms: Cluster, Grid, Cloud, and Peer-to-peer computing
*Ubiquitous computing with heterogeneous systems
*Application case studies
*Task coordination and workflow issues in heterogeneous systems
*Confluence of big data and heterogeneity, including big data for heterogeneous data sets, and exploitation of heterogeneity in data-intensive computing for analytics
*Interoperability of heterogeneous software systems

Important Dates

Paper submission: December 20, 2013
Author notification: February 7, 2014
Camera-ready paper: March 7, 2014

Paper Submissions

Please visit the HCW 2014 website (hcw.wsu.edu) for instructions on how to submit.

Workshop Organization

General Chair:

Uwe Schwiegelshohn, TU Dortmund University, Germany

Program Chair:

Shoukat Ali, Elastica, San Jose, CA.

Steering Committee:

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

Program Committee:

Francisco Almeida, University of La Laguna, Spain
Ioana Banicescu, Mississippi State University, U.S.A.
Olivier Beaumont, INRIA, France
Anne Benoit, ENS-Lyon, France
George Bosilca, University of Tennessee, U.S.A.
Ron Brightwell, Sandia National Laboratories, USA
Ali R Butt, Virginia Tech, USA
Eddy Caron, ENS-Lyon, France
Christian Engelmann, Oak Ridge National Laboratory
Kurt Ferreira, Sandia National Laboratories, USA
Domingo Gimenez, University of Murcia, Spain
Alexey Kalinov, Cadence Design Systems, Russia
Jong-Kook Kim, Korea University, South Korea
Alexey Lastovetsky, University College Dublin, Ireland
Victor Lee, Parallel Computing Lab, Intel, USA
Tony Maciejewski, Colorado State University, U.S.A.
John P. Morrison, University College Cork, Ireland
Dana Petcu, Western University of Timisoara, Romania
Mustafa Rafique, IBM Research, Ireland
Rolf Riesen, IBM Research, Ireland
Enrique Quintana, University of Jaume I of Castellon, Spain
Gudula Runger, TU Chemnitz, Germany
Stephen L. Scott, Tennessee Tech University & Oak Ridge National Laboratory, U.S.A.
Leonel Sousa, Technical University of Lisbon, Portugal
Achim Streit, KIT, Karlsruhe, Germany
Stanimire Tomov, University of Tennessee, U.S.A.
Denis Trystram, IMAG, France
Carlos Varela, Rensselaer Polytechnic Institute, U.S.A.

Questions may be sent to the program chair at shoukat.ali@elastica.co.