@MASTERSTHESIS{ 2016:887265623,
 	title = {An evolutionary approach for the task mapping problem},
 	year = {2016},
 	url = "http://tede2.pucrs.br/tede2/handle/tede/8439",
 	abstract = "This works has the goal to implement an Evolutionary Algorithm, based on the classical Differential Evolution, to solve the Task Mapping onto NoC problem. Our variant implemented a changing on the genetic operator of recombination, that started to reward individuals containing a pre-select condition that indicates when most communicating tasks are allocated near to each other onto the NoC. Our implementation was subject to the NASA Numerical Aerodynamic Simulation (NASA NAS) benchmark and results have shown that our variant is feasible and competitive. When compared to the CAFES Framework, our DE variant presented superior results on two of five tested applications, reaching equivalent quality on one of the applications and getting worst results in two of them.",
 	publisher = {Pontif?cia Universidade Cat?lica do Rio Grande do Sul},
 	scholl = {Programa de P?s-Gradua??o em Ci?ncia da Computa??o},
 	note = {Escola Polit?cnica}
}