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Formalin: Architectural Support for Power Performance Aware GPU

机译:Formalin:对功耗和性能感知GPU的架构支持

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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:本文提出了一种控制策略,用于管理图形处理单元(GPU)的性能和功耗。 GPU是吸引人的控制目标,因为它们具有充足的反馈源并支持多个执行器。关键的挑战是,越来越多的GPU承担着运行通用计算的任务,并且要构建一个能够捕获所有可能的工作负载对可用执行器响应的模型非常困难。为了克服这一挑战,我们提出了一种分级控制结构。在GPU应用程序执行期间,全局控制器为单个应用程序组件(或内核)设置性能目标。然后,本地控制器确保在满足内核功率预算的同时满足功耗目标。本地控制器依靠可以在线浏览执行器响应的整体控制策略。我们实施了该策略,并观察到与常用的启发式策略相比,它在降低能耗的同时满足了性能和功耗目标。

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