Abstract
Many modern computing platforms, including “aggressive” multicore architectures, proposed exascale architectures, and many modalities of Internet-based computing are “task hungry”—their performance is enhanced by always having as many tasks eligible for allocation to processors as possible. The AREA-Oriented scheduling (AO-scheduling) paradigm for computations with intertask dependencies—modeled as dags—was developed to address the “hunger” of such platforms, by executing an input dag so as to render tasks eligible for execution quickly. AO-scheduling is a weaker, but more robust, successor to IC-scheduling. The latter renders tasks eligible for execution maximally fast—a goal that is not achievable for many dag s. AO-scheduling coincides with IC-scheduling on dags that admit optimal IC-schedules—and optimal AO-scheduling is possible for all dag s. The computational complexity of optimal AO-scheduling is not yet known; therefore, this goal is replaced here by a multi-phase heuristic that produces optimal AO-schedules for series-parallel dags but possibly suboptimal schedules for general dags. This paper employs simulation experiments to assess the computational benefits of AO-scheduling in a variety of scenarios and on a range of dags whose structure is reminiscent of ones encountered in scientific computing. The experiments pit AO-scheduling against a range of heuristics, from lightweight ones such as FIFO scheduling to computationally more intensive ones that mimic IC-scheduling’s local decisions. The observed results indicate that AO-scheduling does enhance the efficiency of task-hungry platforms, by amounts that vary according to the availability patterns of processors and the structure of the dag being executed.
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Cordasco, G., De Chiara, R., Rosenberg, A.L. (2011). Assessing the Computational Benefits of AREA-Oriented DAG-Scheduling. In: Jeannot, E., Namyst, R., Roman, J. (eds) Euro-Par 2011 Parallel Processing. Euro-Par 2011. Lecture Notes in Computer Science, vol 6852. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23400-2_18
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