From cTuning.org

Revision as of 19:37, 8 April 2012

HiPEAC₃ thematic session: Collective characterization, optimization and design of computer systems

Organizer

• Grigori Fursin, INRIA, France

Description

Continuing innovation in science and technology is vital for our society and requires ever increasing computational resources. However, delivering such resources became intolerably complex, ad-hoc, costly and error prone due to an enormous number of available design and optimization choices combined with the complex interactions between all software and hardware components, and a large number of incompatible analysis and optimization tools.

As a result, understanding and modeling of the overall relationship between end-user algorithms, applications, compiler optimizations, hardware designs, data sets and run-time behavior, essential to provide better solutions and computational resources, became simply infeasible as confirmed by many recent long-term international research visions about future computer systems.

Based on our interdisciplinary background, we propose to radically change research and development methodology as well as publication model in computer engineering that favors collaborative discovery, systematization, sharing and reuse of knowledge. Motivated by physics, biology and AI sciences, we developed the first version of public repository and infrastructure (cTuning.org) to allow researchers share data (applications, data sets, codelets and architecture descriptions), modules (classification, predictive modeling, run-time adaptation) and statistics about behavior of computer systems manually or automatically.

Having common infrastructure and repository allows users to quickly reproduce and validate existing results, and focus their effort on novel approaches combined with with data mining, classification and predictive modeling rather than spending considerable effort on building new tools with already existing functionality or using some ad-hoc tuning heuristics. It will also allow conferences and journals to favor publications that can be collaboratively validated by the community.

The first version of cTuning infrastructure released in 2009 helped to develop adaptive, machine learning based compiler and statistical collective tuning methodology for mobiles and data centers. We are now preparing next generation of cTuning collaborative research platform and plan to release it in summer 2012.

Expectations

This session is intended to bring together researchers and developers interested in collaborative and interdisciplinary computer engineering methodology with a current focus on the following topics:

• Decomposition of large, complex applications into codelets
• Program auto-tuning and architecture design space exploration
• Run-time adaptation combined with static multi-visioning
• Data mining, classification and predictive modeling
• Common interfaces for compilers and run-time systems

Program

Registration