From:  gfursin@gmail.com
Date:  09 Sep 2006 13:05:05 Hong Kong Time
Newsgroup:  news.alt119.net/comp.ai
Subject:  

CFP: HiPEAC Workshop on Statistical and Machine learning approaches applied to ARchitectures and compilaTion (SMART'07) (Ghent, Belgium, Jan 07)

NNTP-Posting-Host:  128.250.20.3

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                                CALL FOR PAPERS

         First Workshop on Statistical and Machine learning approaches
                     applied to ARchitectures and compilaTion
                                  (SMART '07)
                     http://www.hipeac.net/smart-workshop.html

                        January 28, 2007, Ghent, Belgium

                    (co-located with HiPEAC 2007 Conference)

********************************************************************************


The rapid rate of architectural change has placed enormous stress on
compiler
writers to keep pace with microprocessor evolution.  This problem is
compounded by the current trend to have multi-cores and multi-threading
which
makes such systems increasingly difficult to target.  Also,  current
methods
of designing computer systems will no longer be feasible in 10-15 years
time;
what is needed are new innovative approaches to architecture design
that scale
both with advances in underlying technology and with future application
domains.

In recent years, several papers have been published showing great
potential in
constructing compilers and architectures using approaches such as
machine
learning and search.

The purpose of this workshop is to promote new ideas and to present
recent
developments in compiler and architecture design using machine
learning,
statistical approaches, and search in order to enhance their
performance,
scalability, and adaptability.

Topics of Interest (but not limited to):

Machine Learning, Statistical Approaches, or Search applied to

* Feedback-Directed Compilation
* Iterative Compilation
* Dynamic Compilation/Adaptive Execution
* Parallel Compiler Optimizations
* Low-power Optimizations
* Simulation
* Performance Models
* Processor and System Architecture
* Design Space Exploration
* Other Topics relevant to Intelligent and Adaptive
Compilers/Architectures

**** Paper Submission Guidelines ****

We invite two kinds papers:

* Research papers with new results (15 page limit)
* Short position/experience papers  (5 page limit)

NOTE: Important ammendment to publication procedure:

In order to increase the importance of this workshop, we will host all
accepted papers on the workshop website.

Papers must be submitted in the PDF (preferably) or postscript formats.
Email
your submissions to jcavazos@inf.ed.ac.uk.  We suggest to use LNCS
LaTeX
templates that can be found at http://www.springeronline.com/lncs
(go to "For Authors" and then "Information for LNCS Editors/Authors")

Proceedings:
An informal collection of the papers to be presented will be
distributed at
the workshop. Questions regarding the workshop proceedings should be
forwarded to jcavazos@inf.ed.ac.uk .

****  Important Dates ****

Deadline for submission: October 20, 2006
Decision notification: December 4, 2006
Workshop: January 28, 2007

**** Organizing Committee ****

Workshop Organizers
John Cavazos, University of Edinburgh, UK
Grigori Fursin, INRIA Futurs, France

Program Committee
Matthew Arnold, IBM T.J. Watson Research Center, USA
Francois Bodin, IRISA, France
Calin Cascaval, IBM T.J. Watson Research Center, USA
John Cavazos, Edinburgh University, UK
Albert Cohen, INRIA Futurs, France
Lieven Eeckhout, Ghent University, Belgium
Ari Freund, IBM Haifa Research Lab, Israel
Grigori Fursin, INRIA Futurs, France
Peter Knijnenburg, University of Amsterdam, Netherlands
Sally McKee, Cornell University, USA
Eliot Moss, University of Massachusetts (Amherst), USA
Michael O'Boyle, Edinburgh University, UK
David Padua, University of Illinois at Urbana-Champaign, USA
Devika Subramanian, Rice University, USA
Olivier Temam, INRIA Futurs, France
Matthew J. Thazhuthaveetil, Indian Institute of Science, India
Richard Vuduc, Lawrence Livermore National Laboratory, USA
Chris Williams, Edinburgh University, UK
Ayal Zaks, IBM Haifa Research Lab, Israel

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