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- | *'''2009.August.05''' - The colleagues from the [http://unidapt.org UNIDAPT Group] started investigating the use of [http://ctuning.org cTuning]/[http://www.milepost.eu MILEPOST] technology and the [http://ctuning.org/unidapt 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 | + | *'''2009.August.05''' - The colleagues from the [http://unidapt.org UNIDAPT Group] started investigating the use of [http://ctuning.org cTuning]/[http://www.milepost.eu MILEPOST] technology and the [http://ctuning.org/unidapt UNIDAPT framework] to predict good optimization and parallelization schemes for hybrid heterogeneous CPU/GPU-like architectures together with [http://www.caps-entreprise.com 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 ({{Ref|FT2009}}, {{Ref|LCWP2009}}, {{Ref|Fur2009}}, {{Ref|JGVP2009}}, {{Ref1|TWFP2009}}, {{Ref|FMTP2008}}, {{Ref|LFF2007}}, {{Ref|FCOP2005}}). They plan to add new optimization cases to the [http://ctuning.org/cdatabase Collective Optimization Database] in Autumn, 2009. |
*'''2009.July.27''' - The paper "Portable Compiler Optimization Across Embedded Programs and Microarchitectures using Machine Learning" ({{Ref|DJBP2009}}) has been accepted for the [http://www.microarch.org/micro42 42nd IEEE/ACM International Symposium on Microarchitecture (MICRO)]. The research has been led by the colleagues from the University of Edinburgh - congratulations! | *'''2009.July.27''' - The paper "Portable Compiler Optimization Across Embedded Programs and Microarchitectures using Machine Learning" ({{Ref|DJBP2009}}) has been accepted for the [http://www.microarch.org/micro42 42nd IEEE/ACM International Symposium on Microarchitecture (MICRO)]. The research has been led by the colleagues from the University of Edinburgh - congratulations! |
Revision as of 11:09, 7 August 2009
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Universal Adaptation Framework |
Statically enabling run-time optimization and adaptation |
Navigation: cTuning.org > CTools 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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You are welcome to join us and participate in discussions, developments or provide feedback and suggestions to extend UNIDAPT Framework.