Abstract
This paper studies the influence that job placement may have on scheduling performance, in the context of massively parallel computing systems. A simulation-based performance study is carried out, using workloads extracted from real systems logs. The starting point is a parallel system built around a k-ary n-tree network and using well-known scheduling algorithms (FCFS and backfilling). We incorporate an allocation policy that tries to assign to each job a contiguous network partition, in order to improve communication performance. This policy results in severe scheduling inefficiency due to increased system fragmentation. A relaxed version of it, which we call quasi-contiguous allocation, reduces this adverse effect. Experiments show that, in those cases where the exploitation of communication locality results in an effective reduction of application execution time, the achieved gains more than compensate the scheduling inefficiency, therefore resulting in better overall performance.
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Pascual, J.A., Navaridas, J., Miguel-Alonso, J. (2009). Effects of Topology-Aware Allocation Policies on Scheduling Performance. In: Frachtenberg, E., Schwiegelshohn, U. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 2009. Lecture Notes in Computer Science, vol 5798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04633-9_8
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DOI: https://doi.org/10.1007/978-3-642-04633-9_8
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