VarEMU:可变性感知软件的仿真测试平台

L. Wanner, Salma Elmalaki, Liangzhen Lai, Puneet Gupta, M. Srivastava
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引用次数: 35

摘要

采用纳米技术制造的现代集成电路,由于老化和环境波动,在芯片之间、芯片之间以及随着时间的推移,存在显著的功率/性能变化。此外,一些现有的和新兴的可靠性损失机制导致了瞬态、间歇性和永久性故障率的增加。虽然这种可变性通常是由工艺、设备和电路设计师解决的,但最近有一种趋势是在软件的各个层中感知和适应可变性。然而,当前的硬件平台通常缺乏可变性感知能力。即使感知能力是可用的,在大量硬件样本中评估可变性感知软件技术也将证明是非常昂贵和耗时的。我们将介绍VarEMU,它是QEMU虚拟机监视器的扩展,可作为评估可变性感知软件技术的框架。VarEMU为用户提供了模拟功耗和故障特征变化的方法,并在软件中感知和适应这些变化。通过使用(和动态更改)功率模型中的参数,用户可以创建具有静态和动态功耗变化的虚拟机。错误可以在任何指令执行之前或之后注入,也可以完全取代任何指令的执行。根据老化模型,功耗和故障易感性也会发生动态变化。VarEMU的软件堆栈具有对故障的精确控制,并为操作系统和进程提供虚拟能量监视器。这允许用户精确地量化和评估单个应用程序变化的影响。我们展示了VarEMU如何根据变化感知的功率和老化模型跟踪能耗,并给出了如何使用它来量化指令执行中的错误如何影响应用程序的示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VarEMU: An emulation testbed for variability-aware software
Modern integrated circuits, fabricated in nanometer technologies, suffer from significant power/performance variation across-chip, chip-to-chip and over time due to aging and ambient fluctuations. Furthermore, several existing and emerging reliability loss mechanisms have caused increased transient, intermittent and permanent failure rates. While this variability has been typically addressed by process, device and circuit designers, there has been a recent push towards sensing and adapting to variability in the various layers of software. Current hardware platforms, however, typically lack variability sensing capabilities. Even if sensing capabilities were available, evaluating variability-aware software techniques across a significant number of hardware samples would prove exceedingly costly and time consuming. We introduce VarEMU, an extension to the QEMU virtual machine monitor that serves as a framework for the evaluation of variability-aware software techniques. VarEMU provides users with the means to emulate variations in power consumption and in fault characteristics and to sense and adapt to these variations in software. Through the use (and dynamic change) of parameters in a power model, users can create virtual machines that feature both static and dynamic variations in power consumption. Faults may be injected before or after, or completely replace the execution of any instruction. Power consumption and susceptibility to faults are also subject to dynamic change according to an aging model. A software stack for VarEMU features precise control over faults and provides virtual energy monitors to the operating system and processes. This allows users to precisely quantify and evaluate the effects of variations on individual applications. We show how VarEMU tracks energy consumption according to variation-aware power and aging models and give examples of how it may be used to quantify how faults in instruction execution affect applications.
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