Abstract
Mixed-parallelism, the combination of data- and task-parallelism, is a powerful way of increasing the scalability of entire classes of parallel applications on platforms comprising multiple compute clusters. While multi-cluster platforms are predominantly heterogeneous, previous work on mixed-parallel application scheduling targets only homogeneous platforms. In this paper we develop a method for extending existing scheduling algorithms for task-parallel applications on heterogeneous platforms to the mixed-parallel case.
An extended version of this paper is given by [13].
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Suter, F., Desprez, F., Casanova, H. (2004). From Heterogeneous Task Scheduling to Heterogeneous Mixed Parallel Scheduling. In: Danelutto, M., Vanneschi, M., Laforenza, D. (eds) Euro-Par 2004 Parallel Processing. Euro-Par 2004. Lecture Notes in Computer Science, vol 3149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27866-5_30
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DOI: https://doi.org/10.1007/978-3-540-27866-5_30
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