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Formalin: Architectural Support for Power Performance Aware GPU

机译:福尔马林:电力与绩效意识到GPU的建筑支持

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This paper presents a control strategy for managing the performance and power consumption of a graphics processing unit (GPU). GPUs are an attractive target for control because they have ample sources of feedback and support multiple actuators. The key challenge is that GPUs are increasingly tasked with running general purpose computations and it is extremely difficult to build a single model that captures all possible workloads' responses to available actuators. To overcome this challenge we propose a hierarchical control structure. During GPU application execution, a global controller sets performance goals for individual application components (or kernels). A local controller then ensures that those goals are met for the kernel while respecting the power budget. The local controller relies on an integral control strategy that can explore actuator response online. We implement this strategy and observe that it meets performance and power goals with low error while saving energy compared to commonly used heuristic strategies.
机译:本文介绍了管理图形处理单元(GPU)性能和功耗的控制策略。 GPU是一个有吸引力的控制目标,因为它们具有充足的反馈来源并支持多个执行器。关键挑战是GPU越来越担任运行通用计算,并且非常困难地构建一个模型,该模型捕获到可用执行器的所有可能的工作负载的响应。为了克服这一挑战,我们提出了分层控制结构。在GPU应用程序执行期间,全局控制器为各个应用程序组件(或内核)设置性能目标。然后,本地控制器确保在致电电源预算的同时为内核满足这些目标。本地控制器依赖于可以在线探索执行器响应的积分控制策略。我们实施此策略并遵守它符合低错误的性能和电源目标,同时节省能源与常用的启发式策略相比。

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