Parallel and Distributed Processing Symposium, International (2009)
May 23, 2009 to May 29, 2009
Frederic Vivien , INRIA, France
Matthieu Gallet , ENS Lyon, France
Loris Marchal , CNRS, France
In this paper, we focus on scheduling jobs on computing Grids. In our model, a Grid job is made of a large collection of input data sets, which must all be processed by the same task graph or workflow, thus resulting in a collection of task graphs problem. We are looking for a competitive scheduling algorithm not requiring complex control. We thus only consider single-allocation strategies. In addition to a mixed linear programming approach to find an optimal allocation, we present different heuristic schemes. Then, using simulations, we compare the performance of our different heuristics to the performance of a classical scheduling policy in Grids, HEFT. The results show that some of our static-scheduling policies take advantage of their platform and application knowledge and outperform HEFT, especially under communication-intensive scenarios. In particular, one of our heuristics, DELEGATE, almost always achieves the best performance while having lower running times than HEFT.
Frederic Vivien, Matthieu Gallet, Loris Marchal, "Efficient scheduling of task graph collections on heterogeneous resources", Parallel and Distributed Processing Symposium, International, vol. 00, no. , pp. 1-11, 2009, doi:10.1109/IPDPS.2009.5161045