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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 too time consuming and costly. Collective Optimization Database stores useful optimization cases from the community to help optimize available computing systems (ranging from supercomputers to embedded systems) and enable development of the emerging intelligent self-tuning adaptive computing systems based on collective optimization, run-time adaptation, statistical and machine learning techniques.
 Collective Optimization Database (cDatabase or COD) provides a common global repository with data analysis plugins to share, analyze and reference useful program/architecture optimization cases. It has been developed to help users optimize programs, libraries, kernels and the whole systems (compiler optimizations/architecture configurations to improve execution time, code size, architecture size, power consumption, etc). It is intended to simplify and automate the design and optimization of programs, compilers, run-time systems and architectures based on recent statistical and machine learning techniques (FT2009, FMTP2008, ABCP2006, MILEPOST, UNIDAPT). We also hope that it will also be useful for adaptive parallelization and scheduling for the emerging and future heterogeneous multi-core systems including current CPU/GPU and CELL architectures (LCWP2009). Finally, it is intended to improve the quality of academic research by avoiding costly duplicate experiments and providing replicable referable results. It can provide detailed performance analysis and comparison of different programs, datasets, compilers and architectures. It can be used to optimize programs on-the-fly when using cloud computing services.
We currently keep information about architectures and their configurations, software environments, programs, datasets, compilers (such as GCC, Open64, ICC, PathScale and plan to add dynamic compilers such as LLVM, IBM Testerossa, etc), compiler flags for program and architecture optimizations, compiler ICI optimization passes, fine-grain program optimizations, execution time, code size, profiling statistics, program static and dynamic features (hardware counters), parallelization schemes, etc.
cDatabase is an evolving project driven by the community and industry demands - you are welcome to join the project, extend the database and data analysis plugins, provide feedback and add your optimization data to help the community. If you want to use database directly, you can find more info about cDatabase API and web-services in cDatabase documentation. You can also communicate with cTuning community through our mailing lists.
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- 2009.August.05 - The colleagues from the UNIDAPT Group started investigating the use of cTuning/MILEPOST technology and the UNIDAPT framework to predict good optimization and parallelization schemes for hybrid heterogeneous CPU/GPU-like architectures together with CAPS Entreprise based on run-time adaptation and profiling, empirical iterative compilation, statistical analysis, machine learning, program and dataset features and run-time decision trees (FT2009, LCWP2009, Fur2009, JGVP2009, TWFP2009, FMTP2008, LFF2007, FCOP2005). They plan to add new optimization cases to the Collective Optimization Database in Autumn, 2009.
- 2009.July.22 - cTuning-related CFP: SMART'10 and GROW'10 workshops will be co-located with HiPEAC'10 conference in Pisa, Italy at the end of January, 2009. You are warmly invited to submit your novel research results and developments to our workshops! At the websites of these workshops you can find all information about topics, PC, deadlines and submission procedures.
- 2009.July.08 - The preprint of a paper "Collective Tuning Initiative: automating and accelerating development and optimization of computing systems" describing cTuning infrastructure is now available online (Fur2009).
- 2009.June.29 - Stable MILEPOST GCC 4.4.0 has been released. Follow further community developments at cTuning GCC ICI page and cTuning development mailing list.
Next, we plan to use MILEPOST/cTuning technology to enable realistic adaptive parallelization, data partitioning and scheduling for heterogeneous multi-core systems using statistical and machine learning techniques.
- 2009.June.26 - The pdf of the paper that describes Collective Tuning Infrastructure and cTuning concept (presented at the GCC Summit'09) will be available in a few weeks here.
- 2009.June.10 - Extended version of the "Collective Optimization" paper (FT2009) describing collective tuning concept has been accepted for ACM Transactions on Architecture and Code Optimization (TACO).
- 2009.June.03-10 - We gave several talks/demos/tutorials about cTuning at the HiPEAC Computing week (Infineon, Munich, Germany) and GCC Summit (Montreal, Canada).
- 2009.June.01 - After nearly 1 year of developments we released/updated all our open-source collaborative R&D tools:
- fully redesigned and documented Interactive Compilation Interface v2.0 for GCC 4.4.0 synchronized with the official plugin GCC branch - transforming compilers into plugin-enabled research toolsets
- MILEPOST GCC 4.4.0 pre-release version at SVN - automating program optimization and compiler optimization heuristic tuning using machine learning
- Continuous Collective Compilation Framework v2.0 - enabling automatic collaborative program optimization based on statistical and machine learning techniques
- Collective Benchmark/MiDataSets v1.0 - enabling realistic program optimization research and benchmarking using multiple open-source programs/datasets.
We also updated Collective Optimization Database with various optimization cases for Intel and AMD processors and comparison of different compilers including GCC, LLVM, Open64, Intel, etc - enabling sharing and reuse of optimization knowledge.
We would like to thank cTuning community for feedback, help and support! You are welcome to join this community effort to automate program optimization and compiler/architecture design.
- 2009.April.27 - We gave a talk at the University of Illinois at Urbana-Champaign about Collective Tuning Initiative and tools and MILEPOST project ("Collective Optimization, run-time adaptation and machine learning"). Presentation is available here. We would like to thank all the UIUC colleagues for a very interesting and useful feedback.
- 2009.April.23 - First version of optimization predictor based on static program features is now available on-line. It is an on-going project, so please be patient. Comments are welcome!
- 2009.April.21 - Several projects to enable automatic fine-grain program optimization and run-time adaptation in GCC using iterative compilation and machine learning (based on our cTuning/UNIDAPT/ICI/MILEPOST technology) have been accepted by the Google Summer of Code. You are welcome to join cTuning community and follow or participate in the developments using our dedicated mailing lists.
- 2009.January.20 - We went off-line to move to a new hosting and a new Mediawiki platform.
- 2008.October.17 - First public version of cDatabase is ready.
- 2007.March.03 - cDatabase has been extended for the MILEPOST project.
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