Collective Tuning Initiative  The Collective Tuning Initiative is a community-driven initiative started by Grigori Fursin to develop free collaborative open-source research tools with unified API for code and architecture characterization, optimization and co-design. This enables the sharing of benchmarks, data sets and optimization cases from the community in the open optimization repository through unified web services to predict better optimizations or architecture designs (provided there is enough information collected in the repository from multiple users). Using common research-and-development tools should help to improve the quality and reproducibility of research into code, architecture design and optimization, encouraging innovation in this area. This approach helped establish Artifact Evaluation at several ACM-sponsored conferences to encourage sharing of artifacts and validation of experimental results from accepted papers. The tools and repository include:  A new version of these open-source tools to support collaborative and reproducible experimentation (Collective Knowledge) was released in 2015. 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 also intended to improve the quality and reproducibility of the research on code and architecture design, characterization and optimization. It includes an online machine learning-based program optimization predictor  that can suggest profitable optimizations to improve program execution time, code size, or compilation time, based on similarities between programs. The Collective Optimization Database is an important part of the Collective Tuning Initiative which is developing open-source R&D tools for collaborative and reproducible computing systems research.