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A spatially triggered dissipative resource distribution policy for SMT processors

机译:SMT处理器的空间触发耗散资源分配策略

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Programs take on changing behavior at runtime in a simultaneous multithreading (SMT) environment. How reasonably common resources are distributed among the threads significantly determines the throughput and fairness performance in SMT processors. Existing resource distribution methods either mainly rely on the front-end fetch policy, or make distribution decisions according to the limited information from the pipeline. It is difficult for them to efficiently catch the various resource requirements of the threads. This work presents a spatially triggered dissipative resource distribution (SDRD) policy for SMT processors. Its two parts, the self-organization mechanism that is driven by the real-time instructions per cycle (IPC) performance and the introduction of chaos that tries to control the diversity of trial resource distributions, work together to supply sustaining resource distribution optimization for changing program behavior. Simulation results show that SDRD with fine-grained diversity controlling is more effective than that with a coarse-grained one. And SDRD benefits much from its two well-coordinated parts, providing potential fairness gains as well as good throughput gains. Meanings and settings of important SDRD parameters are also discussed.
机译:程序在同时多线程(SMT)环境中的运行时更改行为。在线程中分配了如何合理的共同资源,显着决定了SMT处理器的吞吐量和公平性能。现有资源分发方法主要依赖于前端获取策略,或根据管道中的有限信息进行分发决策。它们很难有效地捕获线程的各种资源要求。这项工作介绍了SMT处理器的空间触发的耗散资源分布(SDRD)策略。它的两部分,由每个周期的实时指令驱动的自组织机制(IPC)性能以及尝试控制试验资源分布的多样性的混沌,共同提供维持资源分配优化以进行更换程序行为。仿真结果表明,具有细粒度多样性控制的SDRD比用粗粒粒度更有效。和SDRD从两种协调的零件中得到了很多好处,提供潜在的公平性收益以及良好的吞吐量。还讨论了重要SDRD参数的含义和设置。

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