NDLI: Analyzing the Dark Silicon Phenomenon in a Many-Core Chip Multi-Processor under Deeply-Scaled Process Technologies

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Analyzing the Dark Silicon Phenomenon in a Many-Core Chip Multi-Processor under Deeply-Scaled Process Technologies

Content Provider	ACM Digital Library
Author	Wang, Yanzhi Pedram, Massoud Ramadurgam, Srikanth Bogdan, Paul Xue, Yuankun Shafaei Bejestan, Alireza
Abstract	The impact of dark silicon phenomenon on multicore processors under deeply-scaled FinFET technologies is investigated in this paper. To do this accurately, a cross-layer framework, spanning device, circuit, and architecture levels is initially introduced. Using this framework, leakage and dynamic power consumptions as well as frequency levels of in-order and out-of-order (OoO) processor cores, and on-chip cache memories and routers in a network-on-chip-based chip multiprocessor system synthesized in 7nm FinFET technology and operating in both super- and near-threshold voltage regimes are presented. Subsequently, total power consumptions of multicore chips manufactured with (i) OoO and (ii) in-order processor cores are reported and compared. According to our results, for a 64-core chip and 15W thermal design power budget, 64% and 39% dark silicon are observed in OoO and in-order multicores, respectively, under super-threshold regime. These percentages drop to 19% and 0% for OoO and in-order multicores operating in the near-threshold regime, respectively. Furthermore, the highest energy efficiencies are achieved by operating in the near-threshold regime, which points to the effectiveness of near-threshold computing in mitigating the effect of dark silicon phenomenon under deeply-scaled technologies.
Starting Page	127
Ending Page	132
Page Count	6
File Format	PDF
ISBN	9781450334747
DOI	10.1145/2742060.2742096
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-05-20
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Finfet devices Near-threshold computing Dark silicon
Content Type	Text
Resource Type	Article

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