Roadmap
cTuningCC (Collective Tuning Compiler Collection)
cTuning CC is a free, open source compiler collection that combines multiple tools and techniques including MILEPOST GCC, Interactive Compilation Interface (ICI), Continuous Collective Compilation framework (CCC), cTuning web-services and Collective Optimization Database and cBench to enable R&D toward self-tuning, adaptive computing systems based on industrial tools, empirical techniques, transparent collecti
MILEPOST GCC with Interactive Compilation Interface
MILEPOST GCC is an open collaborative plugin infrastructure intended to transform popular, stable, production-quality GCC into a powerful R&D tool. MILEPOST GCC is composed of the Interactive Compilation Interface and a static program feature extractor.The Interactive Compilation Interface (or 'ICI' for short) is a plugin system with a high-level compiler-independent and low-level compiler-dependent API to transform current compilers into collaborative open modular interactive toolsets.
Collective Benchmark
Collective Benchmark is a collection of open-source programs with multiple datasets assembled by the community to enable realistic benchmarking, performance evaluation and research on program and architecture optimization. This benchmark can work directly with the Continuous Collective Compilation Framework and Collective Optimization Database to automate iterative feedback-directed compilation, DSE and enable statistical collective optimization.
Collective Optimization Database
Collective Optimization Database (cDatabase) is a collaborative repository with open API to share, reuse and reference useful/profitable optimization cases from the community including compiler optimizations and architecture configurations to improve code execution time, code and architecture size, compilation time, power consumption among others. Special web-services, plugins and cTools are provided/being developed to automate/predict program optimization, compiler tuning and architecture design using empirical iterative compilation, statistical analysis and machine learning techniques. cDatabase is intended to improve the quality of academic research by avoiding costly duplicate experiments and providing reproducible referable results.
