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'''''We moved all developments to our new [http://cKnowledge.org Collective Knowledge Framework] in 2015!'''''
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'''cTuning.org - free, open source, collaborative repository and tools for program and architecture characterization and optimization.'''
 
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{{Reference}}
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It may not always be visible to the IT users, but developing and optimizing current and emerging computing systems using available technology is excessively inefficient, time consuming and costly. During last several decades, many research papers have been published with suggestions about how to easily solve all these problems! Unfortunately, we often struggled replicating those results in realistic environments or finding stable practical tools based on these research papers. Therefore, [http://fursin.net/research Dr. Grigori Fursin] created this collaborative Collective Tuning wiki-based portal based on his past R&D to continue developing free common open-source extensible collaborative infrastructure, benchmarks and collective optimization repository based on multiple research techniques and production tools to parametrize, abstract, automate, simplify and systematize program, compiler and architecture design and optimization using collective tuning, run-time adaptation, statistical and machine learning techniques. It enables sharing of benchmarks, datasets, optimization cases through unified web-services and tools with common APIs to be able to predict better optimizations or architecture designs provided there is enough information collected in the repository from multiple users. This technology minimizes repetitive time consuming tasks and human intervention: even though there is still a lot to be done, we are glad to see it helping several companies, end users and researchers to improve execution time, code size, power consumption, reliability and other important characteristics of the available computing systems ranging from supercomputers to mobile systems automatically.  
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It may not be always visible to the end-users, but developing and optimizing emerging computer systems using current methodology and tools is excessively inefficient, time consuming and costly. During past decades, many research papers have been published about how to design and optimize computer systems. However, most of the time, we struggle to reproduce their results in realistic environments, or to find common open-source tools based on these research papers. Therefore, we created this collaborative tuning center with a public optimization repository to share data about behavior of computer systems, share free open-source code, benchmarks, data sets, and models from these tools, and let the community improve predictive models that correlate behavior of computer systems with various properties and characteristics of computer systems. cTuning technology is used to help academia and industry to collaboratively improve execution time, code size, power consumption, reliability and other important characteristics of emerging computer systems from HPC to mobile devices.  
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<div style="color:red; font-weight:bold">cTuning web-site and infrastructure is totally free and maintained by end-users (basically by you). It is an on-going project, so please be patient or join the effort by sharing optimization data, extending tools, exchanging ideas, referencing this work, etc. We created cTuning.org because we believe in the power of collaborative and open R&D, and because we would like to change sad trends in academic research where a number of published papers is often more important than usefulness, reproducibility and reusability of results including code, data and models!</div>
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* After long thinking and discussions with cTuning community, we may expect to get a new version of cTuning in Fall, 2011. Please, stay tuned  through Grigori Fursin's [http://twitter.com/grigori_fursin twitter] or [[Community|cTuning mailing lists]].
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* 2 new reference journal publications with more scientific aspects/details on cTuning.org are now available online: [http://fursin.net/wiki/index.php5?title=Research:Dissemination#FT2010 collective optimization (ACM TACO'10)] and [http://fursin.net/wiki/index.php5?title=Research:Dissemination#FKMP2011 machine learning enabled self-tuning compiler for multi-objective optimizations (IJPP'11)]
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* '''Open calls for papers: [http://exadapt.org EXADAPT 2011] (at PLDI 2011/FCRC 2011)'''
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<div style="color:red; font-weight:bold">cTuning web-site and infrastructure is totally free and is now maintained and extended collaboratively and voluntarily by its users (basically by you). It is an on-going project, so please be patient or join the effort by sharing optimization data, extending tools, exchanging ideas, referencing this work, etc. We created cTuning.org because we believe in collaborative and public nature of R&D and because we would like to change trends in academic IT research intended to publish myriads of similar papers often non-reproducible results, without releasing open source tools and data.</div>
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'''Current design of our Collective Optimization Framework''':
'''Current design of our Collective Optimization Framework''':
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We developed [http://cTuning.org/cdatabase Collective Optimization Database] to continuously collect a large number of optimization cases from the community to learn how to correlate program features, program and system behavior and good optimizations between multiple programs, datasets, compilers, operating systems and architectures. This repository is also intended to improve the quality of academic research by avoiding costly duplicate experiments and providing reproducible results.
We developed [http://cTuning.org/cdatabase Collective Optimization Database] to continuously collect a large number of optimization cases from the community to learn how to correlate program features, program and system behavior and good optimizations between multiple programs, datasets, compilers, operating systems and architectures. This repository is also intended to improve the quality of academic research by avoiding costly duplicate experiments and providing reproducible results.
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cTuning open-source infrastructure is still far from solving all optimization problems but we hope that it already opens up some interesting collaborative R&D opportunities to the community to develop intelligent self-tuning adaptive computing systems. We hope that cTuning-like technology will one day eventually improve production compilers that we use including [http://gcc.gnu.org GCC], [http://llvm.org LLVM], [http://rosecompiler.org Rose source-to-source tool], [http://www.open64.net Open64], IBM [http://www-01.ibm.com/software/awdtools/fortran XL] and [http://j9tr.blogspot.com Testarossa], [http://www.caps-entreprise.com/fr/page/index.php?id=49&p_p=36 HMPP directive based compiler for hybrid multicore systems], [http://software.intel.com/en-us/intel-compilers Intel] compiler suites, and operating systems including [http://moblin.org Moblin], [http://www.android.com Android], standard desktop/server Linux distributions, [http://www.microsoft.com/WINDOWS Windows], cloud/distributed operating systems and so on. We would like to thank all [[Community:People|cTuning colleagues and users]] who are or have been helping with this project.
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cTuning open-source infrastructure is still far from solving all optimization problems but we hope that it already opens up some interesting collaborative R&D opportunities to the community to develop intelligent self-tuning adaptive computing systems. We hope that cTuning-like technology will one day eventually improve production compilers that we use including [http://gcc.gnu.org GCC], [http://llvm.org LLVM], [http://rosecompiler.org Rose source-to-source tool], [http://www.open64.net Open64], IBM [http://www-01.ibm.com/software/awdtools/fortran XL] and [http://j9tr.blogspot.com Testarossa], [http://www.caps-entreprise.com/fr/page/index.php?id=49&p_p=36 HMPP directive based compiler for hybrid multicore systems], [http://software.intel.com/en-us/intel-compilers Intel] compiler suites, and operating systems including [http://moblin.org Moblin], [http://www.android.com Android], standard desktop/server Linux distributions, [http://www.microsoft.com/WINDOWS Windows], cloud/distributed operating systems and so on. We would like to thank all [[Community:People|cTuning colleagues and users]] who have been helping with this project.
'''''Note:''' cTuning is an ongoing evolving project - please be patient and tolerant to the community. You are warmly welcome to [[Join|join cTuning community]] to help us parametrize and automate code, compiler and architecture design and optimization!''  
'''''Note:''' cTuning is an ongoing evolving project - please be patient and tolerant to the community. You are warmly welcome to [[Join|join cTuning community]] to help us parametrize and automate code, compiler and architecture design and optimization!''  
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'''We are participating in the following collaborative activities:'''
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'''We have been participating in the following collaborative activities since 2006:'''
* Develop common open-source tools with unified APIs (universal compilers adaptable to any heterogeneous multi-core architecture, computer architecture simulators, adaptive run-time systems) to optimize programs and architectures collectively using iterative compilation, statistical and machine learning techniques. <div align="right">''More information is available at [[CTools|cTools page]].''</div>  
* Develop common open-source tools with unified APIs (universal compilers adaptable to any heterogeneous multi-core architecture, computer architecture simulators, adaptive run-time systems) to optimize programs and architectures collectively using iterative compilation, statistical and machine learning techniques. <div align="right">''More information is available at [[CTools|cTools page]].''</div>  
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Example of complex optimization search spaces for susan_c (including optimization space frontier for multi-objective optimizations) from [[CTools:CBench|Collective Benchmark]] after using [[CTools:CCC|CCC framework]] (that has some similarities with the useful [http://www.coyotegulch.com/products/acovea ACOVEA tool] but also allows automatic sharing of optimization knowledge with the community in the [[CDatabase|Collective Optimization Database]] and uses plugins to implement various search techniques besides genetic algorithms) and [[CTools:CTuningCC|cTuning CC]]/[[CTools:MilepostGCC|MILEPOST GCC 4.4.x]]:
Example of complex optimization search spaces for susan_c (including optimization space frontier for multi-objective optimizations) from [[CTools:CBench|Collective Benchmark]] after using [[CTools:CCC|CCC framework]] (that has some similarities with the useful [http://www.coyotegulch.com/products/acovea ACOVEA tool] but also allows automatic sharing of optimization knowledge with the community in the [[CDatabase|Collective Optimization Database]] and uses plugins to implement various search techniques besides genetic algorithms) and [[CTools:CTuningCC|cTuning CC]]/[[CTools:MilepostGCC|MILEPOST GCC 4.4.x]]:
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<div align="center">http://unidapt.org/images/fig_opt_case_susan_c_1.gif http://ctuning.org/wiki/images/fig_opt_case_susan_c_2.gif</div>
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<div align="center">http://ctuning.org/wiki/images/fig_opt_case_susan_c_1.gif http://ctuning.org/wiki/images/fig_opt_case_susan_c_2.gif</div>
Example of program similarities using [[CTools:MilepostGCC:StaticFeatures|static program features]] and based on best found program optimizations continuously collected in the [[CDatabase|cTuning optimization repository]] that improve execution time (as well as code size, compilation time, etc):
Example of program similarities using [[CTools:MilepostGCC:StaticFeatures|static program features]] and based on best found program optimizations continuously collected in the [[CDatabase|cTuning optimization repository]] that improve execution time (as well as code size, compilation time, etc):
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<div align="center">http://unidapt.org/images/img_influence_features.gif http://unidapt.org/images/img_influence_optimizations.gif</div>.
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<div align="center">http://ctuning.org/wiki/images/img_influence_features.gif http://ctuning.org/wiki/images/img_influence_optimizations.gif</div>.
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[[CTools:CTuningCC|cTuning CC]]/[[CTools:MilepostGCC|MILEPOST GCC 4.4.x]] helps to correlate program features and optimizations using various machine learning techniques to quickly predict good optimizations for a previously unseen program.
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[[CTools:CTuningCC|cTuning CC]]/[[CTools:MilepostGCC|MILEPOST GCC]] uses online machine learning and prediction plugins to correlate program features and optimizations on the fly and quickly predict profitable optimizations for a previously unseen program and for multiple user objectives (balancing execution time, code size, compilation time, etc).
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[[CMind|Collective Mind]] framework and repository is the latest development by [http://cTuning.org/lab/people/gfursin Grigori Fursin] that aggregates all his past R&D to deliver new universal plugin-based framework to systematize and automate computer engineering using crowdsourcing and machine learning.
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* '''2011.February.25''' - '''Call for papers:''' [http://exadapt.org EXADAPT 2011] (co-located with PLDI/FCRC 2011): 1st International Workshop on Adaptive Self-Tuning Computing Systems for the Exaflop Era. Paper submission deadline: ''March 27, 2011''.
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cTuning foundation (non-profit association run by the community) is the outcome of the [http://ctuning.org/project-milepost EU FP6 MILEPOST project (2006-2009)]!
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* '''2011.January.21''' - In case, someone is interested, 2 new reference journal publications related to [http://cTuning.org cTuning.org], [http://cTuning.org/milepost-gcc MILEPOST GCC] and [http://cTuning.org/ctuning-cc cTuning CC] are now available online: {{Ref2|FT2010|collective optimization (ACM TACO'10)}} and {{Ref2|FKMP2011|machine learning enabled self-tuning compiler for multi-objective optimizations (IJPP'11)}}.
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* '''2010.December.31''' - Dear all, we wish you very nice and relaxing holidays and super-exciting, productive and successful New Year ;) !..
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* '''2010.December.25''' - The website for SMART'2011 workshop (co-located with CGO'2011) is now finalized and the submission website is open! Please, follow this [http://cTuning.org/workshop-smart2011 link], submit your best papers ;) and spread the word!
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* '''2010.December.20''' - Extended variant of our paper on "Collective Optimization" will appear in December issue of the ACM Transactions on Architecture and Code Optimization (TACO). PDF and BIB are now available here: {{Ref|FT2010}}.
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* '''2010.October.31''' - Paper about practical aggregation of semantical program properties for machine learning based optimization by M.Namolaru et al from CASES'10 is now available on-line [http://unidapt.org/index.php/Dissemination#MCFP2010 here]. It describes mechanisms of feature extraction inside [http://cTuning.org/ctuning-cc MILEPOST GCC/cTuning CC].
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* '''2010.October.26''' - SMART'11 will be co-located with the [http://www.cgo.org/cgo2011 CGO'11] conference. More information will be following soon!
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* '''2010.October.25''' - [http://www.exascale-computing.eu Exascale Computing Research Center (France)] (former EXATEC Lab) has been finally officially inaugurated!
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* '''2010.September.10''' - The CFP for the [http://grow2011.inria.fr 3rd International Workshop on GCC Research Opportunities (GROW 2011)] co-located with [http://www.cgo.org/cgo2011 CGO 2010] (early April 2011, Chamonix, France) is now available [http://grow2011.inria.fr on-line]. Please, follow our announcements about GROW 2011 and submit your best papers!..
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* '''2010.August.24''' - Congratulations to Mircea et al for the paper [http://unidapt.org/index.php/Dissemination#MCFP2010 Practical Aggregation of Semantical Program Properties for Machine Learning Based Optimization] accepted to [http://www.public.asu.edu/~ashriva6/esweek2010/cases2010 CASES 2010]. This work has been integrated with [http://cTuning.org/milepost-gcc MILEPOST GCC] and [http://cTuning.org/ctuning-cc cTuning CC].
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* '''2010.August.16''' - Submissions are now open for [http://www.cgo.org/cgo2011 CGO 2011].
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* '''2010.June.30''' - Call for papers: [http://www.cgo.org/cgo2011/CGO-2011-CFP.pdf CGO'11].
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* '''2010.June.9''' - Finally, we recovered all cTuning website and services after physical hard drive failure. However, if you still experience some problems or abnormal behavior, please report that to the [http://groups.google.com/group/ctuning-discussions cTuning discussions mailing list]! Thanks and sorry for any inconvenience!
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* '''2010.May.22''' - Pre-release of [[CTools:CTuningCC|cTuning CC V2.5]] is now available. cTuning CC is a free, open source compiler collection that combines multiple tools and techniques including [[CTools:MilepostGCC|MILEPOST GCC]], [[CTools:ICI|ICI]], [[CTools:CCC|CCC framework]], [[CDatabase|cTuning web-services and Collective Optimization Database]] and [[CTools:CBench|cBench]] as the first practical step toward self-tuning, adaptive computing systems based on industrial tools, empirical techniques, transparent collective optimization, statistical analysis and machine learning. cTuning CC is a wrapper around any compiler such as [http://gcc.gnu.org GCC], [http://llvm.org LLVM], [http://www.open64.net Open64], [http://www.pathscale.com Path64], etc that can transparently invoke machine learning mode to correlate program features of a compiled program with the ones stored in the [http://cTuning.org/cdatabase Collective Optimization Database] and suggest better optimizations for multi-objective criteria such as improving execution time, compilation time, code size, etc (using optimization space frontier detection).
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* '''2010.May.14''' - Call for papers: [http://asplos11.cs.ucr.edu ASPLOS 2011].
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* '''2010.April.28''' - List of all projects accepted for Google Summer of Code 2010 is now [http://socghop.appspot.com/gsoc/program/list_projects/google/gsoc2010 available on-line]. There are many projects related to [http://gcc.gnu.org/wiki/SummerOfCode GCC], LLVM, MONO, etc.<BR>Discussion page about GCC as a research compiler [[Dissemination:Workshops:GROW10:GCC_as_a_research_compiler|has been updated]].<BR>Diego Novillo started a proposal to [http://gcc.gnu.org/wiki/ModularGCC modularize GCC].
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* '''2010.April.14''' - Long awaited GCC 4.5 has been [http://gcc.gnu.org/gcc-4.5 released]! It features new plugin framework with some parts of [http://cTuning.org/ici ICI] to continue GCC modularization and parametrization, simplify pass manipulation and reordering, and enable better integration with [http://cTuning.org cTuning]/[http://cTuning.org/milepost-gcc MILEPOST] tools to automate optimization space exploration and prediction of profitable combinations of program transformations during multi-objective optimizations (balancing execution time, code size, compilation time, etc) for a given program/dataset/architecture.
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* '''2010.March.17''' - We pre-released all tools including [[CTools:MilepostGCC|MILEPOST GCC]], [[CTools:CCC|CCC framework]], [[CTools:CBench|cBench]] and [[CDatabase|cDatabase]]. It's a major update of cTuning tools including changes behind  to support transparent optimizations of programs and libraries, better multi-objective optimization (including balancing of execution time, code size and compilation time), bug fixes in averaging multiple optimization cases, C++ support in MILEPOST GCC, support of all version of GCC 4.4, new static features in MILEPOST GCC, extended documentation, etc. Feedback and comments are welcome [http://groups.google.com/group/ctuning-discussions/browse_thread/thread/c22a6109d57905f7 here].
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* '''2010.March.01''' - CGO'10 program is available [http://www.cgo.org/cgo2010/program.html on-line].
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* '''2010.February.10''' - Accepted papers for PLDI'10 are now available [http://www.cs.stanford.edu/pldi10/PLDI2010Papers.html on-line].
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* '''2010.January.28''' - Proceedings and slides from [[Dissemination:Workshops:GROW10:Program|GROW'10]] and [[Dissemination:Workshops:SMART10:Program|SMART'10]] are now available online.
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* '''2010.January.25''' - We added [http://www.prism.uvsq.fr/~touati/sw/ST Speedup Test beta plugin] to [http://cTuning.org/cdatabase cTuning collective optimization database] to enable precise and rigorous statistical analysis of the performance of benchmarks.
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* '''2010.January.4''' - Call for participation: GROW'10 and SMART'10 workshops will be held on the 23rd and 24th of January in Pisa, Italy co-located with the [http://www.hipeac.net/conference/pisa/program HiPEAC conference]. Preliminary programs are available: [http://ctuning.org/wiki/index.php/Dissemination:Workshops:SMART10:Program SMART'10 program] and [http://ctuning.org/wiki/index.php/Dissemination:Workshops:GROW10:Program GROW'10 program].
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:::::: ''[http://groups.google.com/group/ctuning-announce News archive]''
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Current revision

We moved all developments to our new Collective Knowledge Framework in 2015! 


cTuning.org is based on the following reference publications: GCC Summit'09, CPE'04, HiPEAC'05, PhD thesis'04, SMART'09, PLDI'10, HiPEAC'09, IJPP'11

It may not be always visible to the end-users, but developing and optimizing emerging computer systems using current methodology and tools is excessively inefficient, time consuming and costly. During past decades, many research papers have been published about how to design and optimize computer systems. However, most of the time, we struggle to reproduce their results in realistic environments, or to find common open-source tools based on these research papers. Therefore, we created this collaborative tuning center with a public optimization repository to share data about behavior of computer systems, share free open-source code, benchmarks, data sets, and models from these tools, and let the community improve predictive models that correlate behavior of computer systems with various properties and characteristics of computer systems. cTuning technology is used to help academia and industry to collaboratively improve execution time, code size, power consumption, reliability and other important characteristics of emerging computer systems from HPC to mobile devices.

cTuning web-site and infrastructure is totally free and maintained by end-users (basically by you). It is an on-going project, so please be patient or join the effort by sharing optimization data, extending tools, exchanging ideas, referencing this work, etc. We created cTuning.org because we believe in the power of collaborative and open R&D, and because we would like to change sad trends in academic research where a number of published papers is often more important than usefulness, reproducibility and reusability of results including code, data and models!

Current design of our Collective Optimization Framework:

ctuning.gif

We developed Collective Optimization Database to continuously collect a large number of optimization cases from the community to learn how to correlate program features, program and system behavior and good optimizations between multiple programs, datasets, compilers, operating systems and architectures. This repository is also intended to improve the quality of academic research by avoiding costly duplicate experiments and providing reproducible results.

cTuning open-source infrastructure is still far from solving all optimization problems but we hope that it already opens up some interesting collaborative R&D opportunities to the community to develop intelligent self-tuning adaptive computing systems. We hope that cTuning-like technology will one day eventually improve production compilers that we use including GCC, LLVM, Rose source-to-source tool, Open64, IBM XL and Testarossa, HMPP directive based compiler for hybrid multicore systems, Intel compiler suites, and operating systems including Moblin, Android, standard desktop/server Linux distributions, Windows, cloud/distributed operating systems and so on. We would like to thank all cTuning colleagues and users who have been helping with this project.

Note: cTuning is an ongoing evolving project - please be patient and tolerant to the community. You are warmly welcome to join cTuning community to help us parametrize and automate code, compiler and architecture design and optimization!

We have been participating in the following collaborative activities since 2006:

  • Develop common open-source tools with unified APIs (universal compilers adaptable to any heterogeneous multi-core architecture, computer architecture simulators, adaptive run-time systems) to optimize programs and architectures collectively using iterative compilation, statistical and machine learning techniques.
    More information is available at cTools page.
  • Share interesting optimization cases from the community for programs/libraries/OS (compiler optimizations/architecture configurations to improve execution time, code size, architecture size, power consumption, etc) in the Collective Optimization Database to help users optimize their systems, enable replicable collaborative research and enable further analysis using statistical and machine learning techniques.
    More information is available at cDatabase page.
  • Enable collaborative research using cTools to automate and simplify the process of developing and optimizing new computer architectures, compilers, operating systems and programming environments using statistical analysis, machine learning, dynamic adaptation and bio-inspired techniques. We believe that our adaptive approaches are critical to overcome the complexity of computing systems and improve their performance, power consumption, system size and fault-tolerance automatically while reducing their cost and time to market.
    More information is available at cResearch page.

Motivation example:

Example of complex optimization search spaces for susan_c (including optimization space frontier for multi-objective optimizations) from Collective Benchmark after using CCC framework (that has some similarities with the useful ACOVEA tool but also allows automatic sharing of optimization knowledge with the community in the Collective Optimization Database and uses plugins to implement various search techniques besides genetic algorithms) and cTuning CC/MILEPOST GCC 4.4.x:

fig_opt_case_susan_c_1.gif fig_opt_case_susan_c_2.gif

Example of program similarities using static program features and based on best found program optimizations continuously collected in the cTuning optimization repository that improve execution time (as well as code size, compilation time, etc):

img_influence_features.gif img_influence_optimizations.gif
.

cTuning CC/MILEPOST GCC uses online machine learning and prediction plugins to correlate program features and optimizations on the fly and quickly predict profitable optimizations for a previously unseen program and for multiple user objectives (balancing execution time, code size, compilation time, etc).

Collective Mind framework and repository is the latest development by Grigori Fursin that aggregates all his past R&D to deliver new universal plugin-based framework to systematize and automate computer engineering using crowdsourcing and machine learning.

cTuning foundation (non-profit association run by the community) is the outcome of the EU FP6 MILEPOST project (2006-2009)!

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