<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ignacio Bravo</style></author><author><style face="normal" font="default" size="100%">M.D. Santambrogio</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Design flows and system architectures for adaptive computing on reconfigurable platforms</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Systems Architecture</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2010</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Elsevier</style></publisher><volume><style face="normal" font="default" size="100%">56</style></volume><pages><style face="normal" font="default" size="100%">543-544</style></pages><language><style face="normal" font="default" size="100%">English</style></language><abstract><style face="normal" font="default" size="100%">This special issue pursues the definition of a novel computational paradigm, based on the so called reconfigurable computing, which will use innovative technological solutions able to extend the Von Neumann architecture using adaptive digital technologies. It is possible to envision for reconfigurable technologies the possibility to move from the prototyping and very specialized low volume arenas to the implementation of real world systems capable of adapting their behavior and resources thousand times a second, according to the surrounding environment evolution. Several studies have been presented to adapt the applications workloads to the computational environment with respect to a given estimation of the performance of the grid. Adaptability is provided by migrating the operations among different components regarding the predicted time with respect to the gathered execution time using monitoring and analysis tools provided by other parts of their framework.</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue><accession-num><style face="normal" font="default" size="100%">0.722</style></accession-num></record></records></xml>