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A Perspective on Dark Silicon

  • Anil KanduriEmail author
  • Amir M. Rahmani
  • Pasi Liljeberg
  • Ahmed Hemani
  • Axel Jantsch
  • Hannu Tenhunen
Chapter

Abstract

The possibilities to increase single-core performance have ended due to limited instruction-level parallelism and a high penalty when increasing frequency. This prompted designers to move toward multi-core paradigms [1], largely supported by transistor scaling [2]. Scaling down transistor gate length makes it possible to switch them faster at a lower power, as they have a low capacitance. In this context, an important consideration is power density—the power dissipated per unit area. Dennard’s scaling establishes that reducing physical parameters of transistors allows operating them at lower voltage and thus at lower power, because power consumption is proportional to the square of the applied voltage, keeping power density constant [3]. Dennard’s estimation of scaling effects and constant power density is shown in Table 1.1. Theoretically, scaling down further should result in more computational capacity per unit area. However, scaling is reaching its physical limits to an extent that voltage cannot be scaled down as much as transistor gate length leading to failure of Dennardian trend. This along with a rise in leakage current results in increased power density, rather than a constant power density. Higher power density implies more heat generated in a unit area and hence higher chip temperatures which have to be dissipated through cooling solutions, as increase in temperature beyond a certain level results in unreliable functionality, faster aging, and even permanent failure of the chip. To ensure a safe operation, it is essential for the chip to perform within a fixed power budget [4]. In order to avoid too high power dissipation, a certain part of the chip needs to remain inactive; the inactive part is termed dark silicon [5]. Hence, we have to operate working cores in a multi-core system at less than their full capacity, limiting the performance, resource utilization, and efficiency of the system.

Keywords

Energy Efficiency Threshold Voltage Power Budget Frequency Scaling Technology Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Anil Kanduri
    • 1
    Email author
  • Amir M. Rahmani
    • 1
  • Pasi Liljeberg
    • 1
  • Ahmed Hemani
    • 2
  • Axel Jantsch
    • 3
  • Hannu Tenhunen
    • 2
  1. 1.University of TurkuTurkuFinland
  2. 2.KTH Royal Institute of TechnologyStockholmSweden
  3. 3.TU WienViennaAustria

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