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Power and performance aware memory-controller voting mechanism

机译:意识到功率和性能的内存控制器表决机制

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Modern System-on-Chips (SoCs) integrate a graphics unit (GPU) with many application processor cores (CPUs), communication cores (modem, WiFi) and device interfaces (USB, HDMI) on a single die. The primary memory system is fast becoming a major performance bottleneck as more and more of these units share this critical resource. An Integrated-Memory-Controller (IMC) is responsible for buffering and servicing memory requests from different CPU cores, GPU and other processing blocks that require DDR memory access. Previous work [2] was focused on appropriately prioritizing memory requests and increasing IMC/DDR memory frequency to improve system performance - which came at the expense of higher power consumption. Recent work has addressed this problem by using a demand based approach. This is accomplished by making the IMC aware of the application characteristics and then scaling its frequency based on the memory access demand [1]. This leads to lower IMC and DDR frequencies and thus lower power. The work presented here shows that instead of lowering the frequency, greater total system power savings can be achieved by increasing IMC frequency at the beginning of a use-case that has moderate GPU utilization. The primary motivation behind this approach is that it allows GPU, with its inherent ability to execute a larger number of parallel threads, to access memory faster and therefore complete its processing portion of the execution pipeline faster. This, in turn, allows relaxation of the timing requirements imposed on the CPU pipeline portion and consecutive cycles, thus saving on total system power. An algorithm for this technique, along with the silicon results on an SoC implemented in an industrial 28nm process, will be presented in this paper.
机译:现代的片上系统(SoC)将图形单元(GPU)与许多应用处理器核心(CPU),通信核心(调制解调器,WiFi)和设备接口(USB,HDMI)集成在一个裸片上。随着越来越多的主存储系统共享这一关键资源,主存储系统正迅速成为主要的性能瓶颈。集成内存控制器(IMC)负责缓冲和服务来自不同CPU内核,GPU和其他需要DDR内存访问的处理模块的内存请求。先前的工作[2]集中于适当地确定存储器请求的优先级并增加IMC / DDR存储器频率以提高系统性能-但这是以更高的功耗为代价的。最近的工作已经通过使用基于需求的方法解决了这个问题。这是通过使IMC意识到应用程序的特性,然后根据内存访问需求来缩放其频率来实现的[1]。这会导致IMC和DDR频率降低,从而降低功耗。此处介绍的工作表明,在降低GPU使用率的用例开始时,通过提高IMC频率,而不是降低频率,可以实现更大的系统总功耗节省。这种方法背后的主要动机是,它允许具有执行大量并行线程的固有能力的GPU更快地访问内存,从而更快地完成其执行管道中的处理部分。反过来,这允许放宽对CPU流水线部分和连续周期施加的时序要求,从而节省了系统总功率。本文将介绍该技术的算法以及在工业28nm工艺中实现的SoC上的硅片结果。

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