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Optimal Task Assignment in Multithreaded Processors: A Statistical Approach

机译:多线程处理器中的最佳任务分配:一种统计方法

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The introduction of massively multithreaded (MMT) processors, comprised of a large number of cores with many shared resources, has made task scheduling, in particular task to hardware thread assignment, one of the most promising ways to improve system performance. However, finding an optimal task assignment for a workload running on MMT processors is an NP-complete problem. Due to the fact that the performance of the best possible task assignment is unknown, the room for improvement of current task-assignment algorithms cannot be determined. This is a major problem for the industry because it could lead to: (1) A waste of resources if excessive effort is devoted to improving a task assignment algorithm that already provides a performance that is close to the optimal one, or (2) significant performance loss if insufficient effort is devoted to improving poorly-performing task assignment algorithms.
机译:大规模多线程(MMT)处理器的引入,由大量具有许多共享资源的内核组成,使任务调度(尤其是任务到硬件线程分配)成为提高系统性能的最有前途的方法之一。但是,为在MMT处理器上运行的工作负载找到最佳任务分配是NP完全的问题。由于尚不清楚最佳可行任务分配的性能,因此无法确定当前任务分配算法的改进空间。这是该行业的一个主要问题,因为它可能导致:(1)如果过度努力来改进已经能够提供接近最佳性能的任务分配算法,或者(2)严重浪费资源。如果没有足够的精力专门用于改进性能较差的任务分配算法,则会降低性能。

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