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RSVP: Soft Error Resilient Power Savings at Near-Threshold Voltage Using Register Vulnerability

机译:RSVP:使用寄存器漏洞,在接近阈值电压时节省了软错误回弹功耗

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With the ever-growing scaling of computing capability, computing systems like supercomputers and embedded systems are bounded by limited power nowadays. Upon the mutually constrained nature between power efficiency and resilience, trade-offs of them have been extensively studied for achieving the optimal performance-power ratio, either under a certain power cap, or within the requirement of quality metrics of applications. Theoretically, running programs in the low-power mode of computational components (e.g., CPU/GPU) can lead to increasing on-chip failure rates in terms of register-level susceptibility to soft errors. However, experimentally, such errors may not arise due to register vulnerability - errors occur at non-vulnerable register access intervals are invalidated and thus will not propagate to later execution. In this work, leveraging register vulnerability, we investigate the validity of failure rates in computing systems at Near-Threshold Voltage (NTV), and empirically evaluate the practice of achieving optimal power savings without incurring observable number of soft errors during program runs. We propose the framework of RegiSter Vulnerability based Power efficiency (RSVP) for reliable and power efficient computing. Experimental results for a wide spectrum of applications on a power-aware simulated platform demonstrate the power saving capability of RSVP, by 11.2% on average, without incurring runtime soft errors at the optimal NTV level for power savings.
机译:随着计算能力的不断扩展,如今,像超级计算机和嵌入式系统这样的计算系统受到有限的能力的束缚。考虑到功率效率和弹性之间的相互制约性质,已经对它们的折衷进行了广泛研究,以在一定功率上限或应用质量指标要求范围内实现最佳性能-功率比。从理论上讲,以寄存器级对软错误的敏感性而言,以计算组件(例如CPU / GPU)的低功耗模式运行程序可能会导致片上故障率上升。但是,从实验上讲,此类错误可能不会由于寄存器漏洞而发生-错误发生在无漏洞的寄存器访问间隔处,因此这些错误将无效,因此不会传播到以后的执行中。在这项工作中,利用寄存器漏洞,我们研究了在近阈值电压(NTV)下计算系统中故障率的有效性,并凭经验评估了实现最佳节能效果的实践,而不会在程序运行期间产生可观数量的软错误。我们提出了基于RegiSter漏洞的电源效率(RSVP)框架,以进行可靠且高效的计算。在具有功耗意识的仿真平台上进行的各种应用的实验结果表明,RSVP的节电能力平均达到了11.2%,而不会在用于节电的最佳NTV级别上产生运行时软错误。

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