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UNIversal aDAPTation Framework (UNIDAPT) is the hybrid static/dynamic framework to enable low-overhead run-time adaptation, optimization and scheduling for unicore and heterogeneous multi-core architectures (GPGPU, CELL, etc) based on static function cloning (with explicit memory transfers if needed), dynamic monitoring routines and run-time decision trees based on static and dynamic program and dataset features. We are implementing this framework in GCC 4.4/4.5 combined with ICI (though maybe source-to-source adaptation framework can still be useful) within Google Summer of Code'09 program. We also hope to provide a unified view of heterogeneous architectures (CPU/GPU, CELL-like, FPGA, accelerators), optimizations and data movement/partitioning with a high-level abstraction layer (architectures, compilers, run-time systems) to automate and simplify program development and optimization for heterogeneous multi-core systems.
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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 based on statistical analysis, machine learning, program and dataset features and run-time decision trees together with CAPS Entreprise. They plan to add new optimization cases to the Collective Optimization Database in Autumn, 2009.
- 2009.July.22 - Grigori Fursin is a co-organizer of SMART'10 and GROW'10 workshops that 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.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.21 - Several projects to enable automatic fine-grain program optimization and run-time adaptation in GCC using iterative compilation and machine learning (based on 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.
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