Using Genetic Algorithms for Hardware Core Placement and Mapping in NoC-Based Reconfigurable Systems

Algorithm 1

Pseudocode of a GA for reconfigurable placement and mapping in NoCs.

(1) best_solution =

(2) population = generate_random_population(PZ)

(3) population, fitness = 1/comm_cost

(4) while generation ≤ NG do

(5)  while ≤ PZ do

(6)   cr_sel1, cr_sel2 = roulette(population, fitness)

(7)   if (crossover) then

(8)    Offspring() = Crossover(cr_sel1, cr_sel2)

(9)    Offspring() = Crossover(cr_sel2, cr_sel1)

(10)  else

(11)    Offspring() = cr_sel1

(12)   Offspring() = cr_sel2

(13)  end if

(14)  if (mutation) then

(15)   Offspring() = mutate(cr_sel1)

(16)   Offspring() = mutate(cr_sel2)

(17)   end if

(18)   for , do

(19)    if offspring().maps then

(20)    fitness = 1/comm_cost

(21)   else

(22)    fitness = 0

(23)   end if

(24)   end for

(25)  end while

(26)  population = offspring

(27)  if fittest(generation) < best_solution then

(28)   best_solution = fittest(generation)

(29)  end if

(30)  generation++

(31) end while

(32) return best_solution