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Scheduling Heterogeneous Processors Isn't As Easy As You Think

机译:调度异构处理器并不像您认为的那么容易

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We consider preemptive online scheduling algorithms to minimize the total weighted/unweighted flow time plus energy for speed-scalable heterogeneous multiprocessors. We show that the well-known priority scheduling algorithms Highest Density First, Weighted Shortest Elapsed Time First, and Weighted Late Arrival Processor Sharing, are not O(1)-speed O(1)-competitive for the objective of weighted flow even in the special case of fixed variable speed processors (aka the related machines setting). This illustrates that scheduling heterogeneous multiprocessors is a different, and algorithmically more challenging problem, than scheduling homogeneous multiprocessors. We then show that a variation of the non-clairvoyant algorithm Late Arrival Processor Sharing coupled with a non-obvious speed scaling algorithm is scalable for the objective of unweighted flow plus energy on speed-scalable multiprocessors. This is the first provably scalable non-clairvoyant algorithm on heterogeneous multiprocessors, even in the related machines setting, for the objective of total (unweighted) flow time.
机译:我们考虑先发售的在线调度算法,以最小化速度可伸缩的异构多处理器的总加权/未加权流量加能。我们表明,众所周知的优先级调度算法最高密度首先,加权最短经过的时间首先,并加权后退处理器共享,而不是O(1) - 即使在加权流动的目标中竞争特殊情况的固定变速处理器(AKA相关机器设置)。这示出了调度异构多处理器是与调度均匀多处理器不同的和算法上更具挑战性的问题。然后,我们表明,与非明显的速度缩放算法耦合的非Clairvoyant算法的变化是与非明显的速度缩放算法耦合的,对于速度可伸缩多处理器上的未加权流量加能的目的是可扩展的。这是在相关机器设置中的第一种超均匀多处理器上的第一种可扩展可扩展的非批量算法,其目的是总共(未加权)流动时间。

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