The Collective Tuning Initiative is a community-driven initiative started by Grigori Fursin to develop free and open-source research tools with a unified API for collaborative characterization, optimization and co-design of computer systems.
[1][2] Using common research-and-development tools should help to improve the quality and reproducibility of computer systems' research and development and accelerate innovation in this area.
This approach helped establish Reproducibility Initiatives and Artifact Evaluation at several ACM-sponsored conferences to encourage sharing of artifacts and validation of experimental results from accepted papers.
The Collective Optimization Database is an open repository to enable sharing of benchmarks, data sets and optimization cases from the community, provide web services and plugins to analyze optimization data and predict program transformations or better hardware designs for multi-objective optimizations based on statistical and machine learning techniques provided there is enough information collected in the repository from multiple users.
The Collective Optimization Database is an important part of the Collective Tuning Initiative[1][2] which is developing open-source R&D tools for collaborative and reproducible computing systems research.