【實用教育app】Collective Mind Node|最夯免費app-綠色工廠好玩App

Tuning applications for rapidly evolving hardware or improving optimization heuristic of a new compiler is becoming complex, ad-hoc, costly and error prone due to an enormous number of available optimization choices combined with the complex interactions between all software and hardware components.

Our idea is to crowdsource such auto-tuning and make it practical using Collective Mind infrastructure and repository (http://sourceforge.net/projects/c-mind). In this approach, multi-objective codelet, program and architecture tuning to balance performance, power consumption, compilation time, code size and any other important metric is distributed among multiple participants.

We hope that our approach will help to automatically improve default optimization heuristics of latest compilers including GCC, LLVM, Open64 and any other, or predict optimizations for new programs using collected knowledge and machine learning to maximize utilization of modern computer devices. Interestingly, we also hope that it will help to improve academic research and switch focus from publishing numerous non-reproducible papers to sharing research material and experimental results that can be collaboratively validated and improved by the community.

This application, supported by non-profit cTuning foundation, is currently a research proof-of-concept to support and validate our idea. It helps us collect various performance statistics from participants to validate machine learning techniques. This is an on-going project, so please be patient! Feedback and suggestions are welcome!

More info:

* Vision publication: https://hal.inria.fr/hal-01054763

* Community website: http://cTuning.org

* Live Repository: http://c-mind.org/repo

* Related workshop (TRUST 2014 @ PLDI 2014): http://c-mind.org/events/trust2014

* Our related artifact evaluation service for conferences and journals (CGO,PPoPP): http://ctuning.org/event/ae-cgo2015/

* Author page: http://cTuning.org/lab/people/gfursin

We are currently looking for more funding/sponsorship (for example, via non-profit cTuning foundation) to continue this project and related public research activities. If you are interested, do not hesitate to contact Grigori Fursin (gfursin@gmail.com) for mor details!