000084925 001__ 84925
000084925 005__ 20190812204927.0
000084925 02470 $$2ISI$$a000238973400003
000084925 037__ $$aCONF
000084925 245__ $$aA hybrid genetic algorithm for constrained hardware- software partitioning
000084925 260__ $$c2006
000084925 269__ $$a2006
000084925 336__ $$aConference Papers
000084925 520__ $$aIn this article, we propose a novel partitioning method for hardware-software codesign based on a genetic algorithm that has been enhanced for this specific task. Given a high- level program and an area constraint, our software considers different granularities levels to discover the most interesting blocks to be implemented in ad hoc functional units that can then be used as new instructions in a Move processor. Various optimizations are conducted to obtain a clean, very fast (in the order of a few seconds) and efficient partitioning on programs ranging from a few to several hundreds of lines of code.
000084925 6531_ $$aGenetic algorithm
000084925 6531_ $$aTTA processor
000084925 6531_ $$aConstrained Hardware-Software partitioning
000084925 700__ $$0241106$$g118636$$aMudry, Pierre-André
000084925 700__ $$aZufferey, Guillaume
000084925 700__ $$aTempesti, Gianluca$$g103907$$0241511
000084925 7112_ $$dApril 18-21$$cPrague$$aDDECS'06
000084925 773__ $$tProceedings of the 2006 IEEE Workshop on Design and Diagnostics of Electronic Circuits and Systems (DDECS'06)$$q3-8
000084925 8564_ $$zURL$$uhttp://ddecs06.felk.cvut.cz/
000084925 8564_ $$zn/a$$uhttps://infoscience.epfl.ch/record/84925/files/hybrid-ga-camera.pdf$$s905967
000084925 909C0 $$pCARG$$0252191
000084925 909C0 $$pBIOROB$$0252049$$xU12165
000084925 909CO $$qGLOBAL_SET$$pconf$$pSTI$$ooai:infoscience.tind.io:84925
000084925 937__ $$aCARG-CONF-2006-007
000084925 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000084925 980__ $$aCONF