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JetsonLEAP: A framework to measure power on a heterogeneous system-on-a-chip device

机译:JetsonLEAP:一种用于测量异构片上系统设备上的功率的框架

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Computer science marches towards energy-aware practices. This trend impacts not only the design of computer architectures, but also the design of programs. However, developers still lack affordable and accurate technology to measure energy consumption in computing systems. The goal of this paper is to mitigate such problem. To this end, we introduce JetsonLEAP, a framework that supports the implementation of energy-aware programs. JetsonLEAP consists of an embedded hardware, in our case, the NVIDIA Jetson TK1 development board, a circuit to control the flow of energy, of our own design, plus a library to instrument program parts. We discuss two different circuit setups. The most precise setup lets us reliably measure the energy spent by 225,000 instructions, the least precise, although more affordable setup, gives us a window of 975,000 instructions. To probe the precision of our system, we use it in tandem with a high-precision, high-cost acquisition system, and show that results do not differ in any significant way from those that we get using our simpler apparatus. Our entire infrastructure - board, power meter and both circuits - can be reproduced with about $500.00. To demonstrate the efficacy of our framework, we have used it to measure the energy consumed by programs running on ARM cores, on the GPU, and on a remote server. Furthermore, we have studied the impact of OpenACC directives on the energy efficiency of high-performance applications. (C) 2017 Elsevier B.V. All rights reserved.
机译:计算机科学向能源意识的实践迈进。这种趋势不仅影响计算机体系结构的设计,还影响程序的设计。但是,开发人员仍然缺乏负担得起的精确技术来衡量计算系统中的能耗。本文的目的是减轻这种问题。为此,我们介绍了JetsonLEAP,这是一个支持节能程序实施的框架。 JetsonLEAP包含一个嵌入式硬件(在我们的示例中是NVIDIA Jetson TK1开发板),一个用于控制能量流的电路(由我们自己设计)以及一个用于存储程序零件的库。我们讨论了两种不同的电路设置。最精确的设置使我们能够可靠地测量225,000条指令所消耗的能量,最不精确(尽管更便宜)的设置使我们可以看到975,000条指令的窗口。为了探究系统的精度,我们将其与高精度,高成本的采集系统配合使用,并表明结果与使用更简单的仪器获得的结果没有显着差异。我们的整个基础设施-电路板,功率计和两个电路-都可以用大约$ 500.00复制。为了证明我们框架的有效性,我们使用它来测量运行在ARM内核,GPU和远程服务器上的程序所消耗的能量。此外,我们研究了OpenACC指令对高性能应用程序的能效的影响。 (C)2017 Elsevier B.V.保留所有权利。

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