FPGA placement by thermodynamic combinatorial optimization

In this paper, the placement problem on FPGAs is faced using thermodynamic combinatorial optimization (TCO). TCO is a new combinatorial optimization method based on both thermodynamics and information Theory. In TCO two kinds of processes are considered: microstate and macrostate transformations. Applying the Shannon´s definition of entropy to microstate reversible transformations, a probability of acceptance based on Fermi-Dirac statistics is derived On the other hang applying thermodynamic laws to reversible macrostate transformations, an efficient annealing schedule is provided TCO has been compared with simulated annealing (SA) on a set of benchmark circuits for the FPGA placement problem. TCO has achieved large time reductions with respect to SA, while providing interesting adaptive properties