Stochastic DAG scheduling using a Monte Carlo approach
A systematic approach to solve the stochastic DAG scheduling problem using a Monte Carlo method. Extensive simulation results assessing the Monte Carlo approach using four real-world DAGs. Significant performance improvement can be achieved at a reasonable execution time cost.
dag scheduling monte carlo methods directed acyclic graphs heterogeneous computing