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Power and Energy Characterization of an Open Source 25-Core Manycore Processor

机译:开源25核Manycore处理器的功率和能量表征

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The end of Dennard's scaling and the looming power wall have made power and energy primary design goals for modern processors. Further, new applications such as cloud computing and Internet of Things (IoT) continue to necessitate increased performance and energy efficiency. Manycore processors show potential in addressing some of these issues. However, there is little detailed power and energy data on manycore processors. In this work, we carefully study detailed power and energy characteristics of Piton, a 25-core modern open source academic processor, including voltage versus frequency scaling, energy per instruction (EPI), memory system energy, network-on-chip (NoC) energy, thermal characteristics, and application performance and power consumption. This is the first detailed power and energy characterization of an open source manycore design implemented in silicon. The open source nature of the processor provides increased value, enabling detailed characterization verified against simulation and the ability to correlate results with the design and register transfer level (RTL) model. Additionally, this enables other researchers to utilize this work to build new power models, devise new research directions, and perform accurate power and energy research using the open source processor. The characterization data reveals a number of interesting insights, including that operand values have a large impact on EPI, recomputing data can be more energy efficient than loading it from memory, on-chip data transmission (NoC) energy is low, and insights on energy efficient multithreaded core design. All data collected and the hardware infrastructure used is open source and available for download at http://www.openpiton.org.
机译:Dennard扩展规模的终结和隐约的功率壁已经成为现代处理器的功耗和能源设计的主要目标。此外,诸如云计算和物联网(IoT)的新应用继续需要提高性能和能效。 Manycore处理器显示出解决其中一些问题的潜力。但是,许多核心处理器上几乎没有详细的功率和能量数据。在这项工作中,我们仔细研究了25核现代开放源代码学术处理器Piton的详细功率和能量特性,包括电压与频率缩放,每条指令能量(EPI),存储系统能量,片上网络(NoC)能量,热特性以及应用程序性能和功耗。这是在硅中实现的开源多核设计的首次详细功率和能量表征。处理器的开放源代码性质提供了更高的价值,从而能够针对仿真验证详细的特性,并能够将结果与设计和寄存器传输级别(RTL)模型相关联。此外,这使其他研究人员能够利用这项工作来构建新的功率模型,设计新的研究方向,并使用开源处理器执行准确的功率和能量研究。表征数据揭示了许多有趣的见解,包括操作数值对EPI的影响很大,与从存储器加载数据相比,重新计算数据的能源效率更高,片上数据传输(NoC)能量较低,并且对能量的了解高效的多线程核心设计。收集的所有数据和使用的硬件基础结构都是开源的,可以从http://www.openpiton.org下载。

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