Apologies if you receive multiple copies of this call.
******************************************************************************** CALL FOR PARTICIPATION 4th Workshop on Statistical and Machine learning approaches to ARchitecture and compilaTion (SMART'10)January 24, 2010, Pisa, Italy
Keynote speaker: Prof. Keith Cooper Rice University, USA
(co-located with HiPEAC 2010 Conference)
****************************************************************************EARLY REGISTRATION DEADLINE: JAN. 6th, 2010
********************************************************************************We invite you to participate in SMART'10 to be held in Pisa, Italy on January 24, 2010, along with the conference on High-Performance Embedded Architectures and Compilers (HiPEAC).
The Workshop Program includes presentations of 5 selected papers and a keynote talk by Prof. Keith Cooper, Rice University, USA on "Moving adaptation into industrial optimizations".
The Workshop Program is now available on-line at:
The rapid rate of architectural change and the large diversity of architecture features has made it increasingly difficult for compiler writers to keep pace with microprocessor evolution. This problem has been compounded by the introduction of multicores. Thus, compiler writers have an intractably complex problem to solve. A similar situation arises in processor design where new approaches are needed to help computer architects make the best use of new underlying technologies and to design systems well adapted to future application domains.
Recent studies have shown the great potential of statistical machine learning and search strategies for compilation and machine design. The purpose of this workshop is to help consolidate and advance the state of the art in this emerging area of research. The workshop is a forum for the presentation of recent developments in compiler techniques and machine design methodologies based on space exploration and statistical machine learning approaches with the objective of improving performance, parallelism, scalability, and adaptability.
Topics of interest include (but are not limited to):
Machine Learning, Statistical Approaches, or Search applied to
- Empirical Automatic Performance Tuning
- Iterative Feedback-Directed Compilation
- Self-tuning Programs, Libraries and Language Extensions
- Dynamic Optimization/Split Compilation/Adaptive Execution
- Adaptive Parallelization
- Low-power Optimizations
- Adaptive Virtualization
- Performance Modeling
- Performance Portability
- Adaptive Processor and System Architecture
- Architecture Simulation and Design Space Exploration
- Collective Optimization
- Self-tuning Computing Systems
- Other Topics relevant to Intelligent and Adaptive Compilers/ Architectures/OS
**************************************************************************** Program Chair: David Whalley, Florida State University, USA
Organizers: Grigori Fursin, INRIA, France John Cavazos, University of Delaware, USA
Steering Committee: Francois Bodin, CAPS Entreprise, France John Cavazos, University of Delaware, USA Lieven Eeckhout, Ghent University, Belgium Grigori Fursin, INRIA, France Michael O'Boyle, University of Edinburgh, UK David Padua, UIUC, USA Olivier Temam, INRIA, France Richard Vuduc, Georgia Tech, USA
Program Committee: Denis Barthou, University of Versailles, France Chun Chen, University of Utah, USA Bruce Childers, University of Pittsburgh, USA Rudolf Eigenmann, Purdue University, USA Bjorn Franke, University of Edinburgh, UK Maria Garzaran, UIUC, USA Sabine Glesner, TU Berlin, Germany Engin Ipek, Microsoft Research, USA Prasad Kulkarni, University of Kansas, USA Xiaoming Li, University of Delaware, USA Peter Marwedel, TU Dortmund, Germany Bilha Mendelson, IBM Haifa, Israel Kathryn McKinley, University of Texas, USA Boyana Norris, Argonne National Laboratory, USA Yunheung Paek, Seoul National University, Korea Markus Puschel, Carnegie Mellon University, USA Apan Qasem, Texas State University, USA Martin Schulz, LLNL, USA Xipeng Shen, College of William & Mary, USA Linda Torczon, Rice University, USA R. Clint Whaley, UTSA, USA Chengyong Wu, ICT, China Qing Yi, UTSA, USA