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Managing distributed memory to meet multiclass workload response time goals

机译:管理分布式内存以满足多类工作负载响应时间目标

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In this paper we present an online method for managing a goal-oriented buffer partitioning in the distributed memory of a network of workstations. Our algorithm implements a feedback mechanism which dynamically changes the sizes of dedicated buffer areas and thereby the buffer hit rate for the different classes in such a way that user-specified response time goals are satisfied. The aggregated size of the buffer memory across all network nodes remains constant and only the partitioning is changed. The algorithm is based on efficiently approximating the trajectory of the per-class response time curves as a function of the available buffer. Changes in the workload that would lead to violation of response time goals are counteracted by accordingly adjusting the buffer allocation. For local replacement decisions, we integrate a cost-based buffer replacement algorithm to fit into our goal-oriented approach. We have implemented our algorithm in a detailed simulation prototype and we present first results obtained from this prototype.
机译:在本文中,我们提出了一种在线方法,用于在工作站网络的分布式内存中管理面向目标的缓冲区分区。我们的算法实现了一种反馈机制,该机制可以动态改变专用缓冲区的大小,从而可以满足用户指定的响应时间目标,从而改变不同类的缓冲区命中率。所有网络节点上缓冲存储器的聚合大小保持不变,并且仅更改分区。该算法基于根据可用缓冲区有效地近似每类响应时间曲线的轨迹。通过相应地调整缓冲区分配,可以抵消可能导致违反响应时间目标的工作负载变化。对于本地替换决策,我们集成了基于成本的缓冲区替换算法,以适合我们的面向目标的方法。我们已经在详细的仿真原型中实现了我们的算法,并展示了从该原型获得的第一批结果。

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