Making computer engineering a science;
Systematizing program and system analysis and optimization using auto-tuning, machine learning and social networking.
|Powered by||Latest version||Development years||Current status||Public access|
|cTuning3 repository aka Collective Mind (cM)||beta||2012-cur.||Active agile development; plugin-based framework; NoSQL based repository; json internal representation; powerful ElasticSearch indexing; universal auto-tuning and data mining; support for practically any Unix and Windows-based desktops, laptops, supercomputers, cloud servers, and even tablets and mobile phones with ARM,Intel,ST,Loongson,AMD,NVidia and other chips; powerful graph capabilities; BSD-style and LGPL license.||
Since 2013, it is available on demand. Currently being tested and improved with several academic partners, and licensed to several industrial partners. Will be open for public at some point in 2013. Contact Grigori Fursin for more info.
|cTuning1 platform (and CCC)||2.5||2006-2010||Stable, MySQL and NoSQL based. Development finished. Will be merged with cM. Used in multiple international collaborative projects including MILEPOST to develop the first machine learning enabled compiler.||Link|
|cTuning2 repository aka CTI||2010-2011||Grigori Fursin and his group developed this repository for Intel Exascale Lab in 2010-2011 as presented at our BOF at SC'2011.||Not available yet (mostly internal Lab/Intel use). Will have a very limited public access. Focus on Intel tools and architectures.|
|FCO repository||2003-2007||Stable, NoSQL based. Discontinued for CCC framework. Used in several collaborative projects (tuning Open64-based compilers for Loongson processor in collaboration with ICT, China).||Discontinued for cTuning1/CCC framework.|
|EOS repository||2.2||1999-2006||Stable, NoSQL based. Discontinued for EOS framework. Used in MHAOTEU project.||Discontinued for FCO framework.|
|SCS (SuperComputer Web Services) repository||1.3||1996-1999||Beta, MySQL based. Discountinued for EOS framework.||Discontinued for EOS framework.|
With our background in physics and AI, and a practical need to get efficient computer systems to solve our tasks, we are shocked by the current state of computer engineering. It is rare to find publications with reproducible and statistically meaningful results, systematized knowledge, open-source data and tools. One of the main reason is that sharing of data and tools simply doesn't pay off while the main focus is to publish as many papers as possible and to share as little data or tools as possible to avoid competition. However, since our aim to build efficient computer systems in terms of performance, power and reliability is to continue innovation in science, since 1996 we started a long-term and painful process of systematization of knowledge about design and optimization of computer systems through collaborative open-source tools and repositories. The first public repository have been used to enable machine learning self-tuning compiler - users ('crowd') have been searching effective predictive models to explain the behavior of computer systems preserved in the cTuning database. These models have been integrated with the MILEPOST GCC compiler or could be used as plugins for dynamic program adaptation (UNIDAPT framework).