Before revision:  This optimization is non-trivial because the evaluation of cost/performance functions is computationally expensive , typically involving simulation of long benchmark programs on a cycle-accurate model of the system . Further, algorithms for optimization over discrete parameters do not scale well with the number of parameters.
After revision:  This optimization is non-trivial because the evaluation of cost/performance functions is computationally expensive , typically involving simulation of long benchmark programs on a cycle-accurate system simulation. If the discrete parameter space can be embedded into a larger continuous parameter space, then continuous space techniques can, in principle, be applied to the system optimization problem. Such continuous space techniques often scale well with the number of parameters.