I am solving a life-cycle model of human capital accumulation with elastic labor supply. Solving the model requires me to search over a state-space of (ability, human capital, assets). It takes quite some time for optimizing each period. I tried to use Numba for faster loops, but it still takes about 12 minutes to solve for the optimal decision rules. I want to know whether I can parallelize the for loops to make it faster (my machine has 8 cores). I tried @njit(parallel=True), but it did not make a difference. Any suggestions?