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Performance of hierarchical processor scheduling in shared-memory multiprocessor systems

机译:共享内存多处理器系统中分层处理器调度的性能

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Processor scheduling policies for multiprocessor systems can be broadly divided into space-sharing and time-sharing policies. Space-sharing policies divide the system processors into a number of partitions and each partition is exclusively allocated to a single job. In time-sharing policies, processors are temporally shared by jobs. Several space-sharing and time-sharing policies have been proposed for small-scale shared-memory systems and require a central run queue and/or central scheduler. The central queue scheduler poses serious scalability problems for large-scale multiprocessor systems. Furthermore, space-sharing and time-sharing policies have their advantages and disadvantages. In this paper, we propose a new multiprocessor scheduling policy that eliminates contention for the central queue/scheduler. Our hierarchical scheduling policy (HSP) is a self-scheduling policy and uses a hierarchical run queue organization to facilitate processor allocation to jobs. We show that the HSP policy is considerably better than purely space-sharing and purely time-sharing policies over a wide range of system and workload parameters of interest.
机译:多处理器系统的处理器调度策略可以大致分为空间共享策略和时间共享策略。空间共享策略将系统处理器划分为多个分区,每个分区专门分配给一个作业。在分时策略中,处理器在时间上由作业共享。对于小型共享内存系统,已经提出了几种共享空间和共享时间的策略,这些策略需要中央运行队列和/或中央调​​度程序。中央队列调度程序对大规模多处理器系统提出了严重的可伸缩性问题。此外,空间共享和时间共享策略有其优点和缺点。在本文中,我们提出了一种新的多处理器调度策略,该策略消除了中央队列/调度程序的争用。我们的分层调度策略(HSP)是一种自调度策略,它使用分层运行队列组织来促进处理器分配给作业。我们表明,在感兴趣的各种系统和工作负载参数上,HSP策略比纯空间共享和纯时间共享策略要好得多。

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