In this thesis we have demonstrated methods of representing some parallel ap- plications that exposes its inherent parallelism better on heterogeneous proces- sors. Using this new representation, we present task mapping algorithms using meta-heuristic solutions that offer significant improvements in the quality of the solutions. We have also discussed in depth the poor definition of critical paths for applications on heterogeneous processors and established that the critical path cannot exist independent of its partial schedule. To this end, we have developed a polynomial time algorithm that runs inO(P2e), whereP is the number of different
classes of processors and e is the total number of edges in the application graph. Based on our experiments, we show that the critical path lengths produced by our algorithm is always at least as long as the ones produced by CPOP for the conven- tional workloads. We also extend our critical path finding algorithm into a DAG scheduling algorithm (CEFT-CPOP) by using the path found by our algorithm (with its corresponding partial assignment) in conjunction with the critical path on a processor (CPOP) algorithm, with a running cost of O(p2e), where p is the
number of processors. We compare the efficacy of our algorithm mainly against CPOP through the use of makespan related comparison metrics like: schedule length ratio (SLR), speedup and slack. We find that our algorithm outperforms CPOP even as a scheduling algorithm, in nearly all aspects.
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