Towards a profound analysis of bags-of-tasks in parallel systems and their performance impact

Abstract

The Bag-of-Tasks (BoT) behaviour has recently drawn the attention of scheduling researchers [2, 36, 37] and seems to be very common in workloads of parallel systems (up to 70% of jobs [27]) and grids (up to 96% of the total CPU time is consumed by BoTs [11]). To enable a reliable evaluation of BoT-oriented scheduling algorithms, researchers require realistic workload models that take BoTs into account. Regrettably, very few such models are available in the liturature. To our best knowledge, there are only two studies on modeling that incorporate BoTs into their models to generate synthetic workloads for parallel systems [27] and grids [12]. However, these models only focus on fitting the marginal distributions and neglect several other statistical properties of BoTs such as periodicity, autocorrelation and cross-correlation among BoT attributes. We believe that these crucial characteristics deserve to be taken into account in modeling research. Therefore in this paper, we will focus on characterising the BoT behaviour to further improve researchers' understanding of this well-known behaviour in parallel system workloads. In addition, we also study how BoTs affect parallel system performance. Our experimental results indicate that the presence of BoTs leads to a considerable performance degradation, but it is interesting that a realistic association between job arrivals and job runtimes helps BoTs to improve the performance of parallel systems. Moreover, we also show the necessity of using workloads with BoTs in scheduling evaluation to obtain reliable results.