CoE 197U Scaling

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Moore's Law

In 1965, Gordon Moore published a 4-page paper entitled "Cramming more components onto integrated circuits"[1], where he predicted that the number of components in an integrated circuit will increase by a factor of two every year, as shown in Fig. 1. Note that he based his extrapolation on just 4 data points!

Figure 1: Gordon Moore's 1965 prediction[1].

Why is this paper and the graph in Fig. 1 important? Gordon Moore's prediction, also known as Moore's Law, has reflected and, more importantly, driven the steady and rapid progress in computing technology[2]. Thus, satisfying Moore's Law has become the goal instead of being merely a prediction.

Evolution of Complexity

As Gordon Moore predicted, the cost and performance advantage of putting more and more devices into a single integrated circuit (IC) led to the rapid increase in circuit complexity. One convenient indicator of circuit complexity is the number of transistors contained in a single IC.

Figure 2: Transistor Count (1970 - 2020)[3].
Figure 3: Technology node and transistor gate length versus calendar year[4].
Figure 4: Scaling and processor performance[5].

Challenges in Digital Design

Figure 5: Supply voltage and power scaling[6].
Figure 6: Active and Leakage Power[7].
Figure 6: Supply and threshold voltage scaling[8].
Figure 7: Leakage and frequency variations[9].

Why Scale?

Figure 7: Semiconductor power density[10].
Figure 6: Calculations per second for a fixed cost[11].

The Cost of Integrated Circuits

Non-Recurrent Engineering Costs

Recurrent Costs

Yield

References

  1. 1.0 1.1 Gordon E Moore, Cramming more components onto integrated circuits, Electronics, Volume 38, Number 8, April 19, 1965 (pdf)
  2. Gordon Moore: The Man Whose Name Means Progress, IEEE Spectrum, March 2015.
  3. Wikimedia
  4. S. E. Thompson, S. Parthasarathy, Moore's law: the future of Si microelectronics, Materials Today, Volume 9, Issue 6, 2006, Pages 20-25. (link)
  5. K. Rupp, 42 Years of Microprocessor Trend Data, https://www.karlrupp.net/2018/02/42-years-of-microprocessor-trend-data/
  6. B. Kunert, Integration and Application of Epitaxial Systems: III/V on Silicon for Optoelectronics, IMEC Belgium 2015
  7. W. Haensch et al., Silicon CMOS devices beyond scaling, IBM Journal of Research and Development, vol. 50, no. 4.5, pp. 339-361, July 2006, doi: 10.1147/rd.504.0339.
  8. ITRS, The International Technology Roadmap for Semiconductors (2004 edition), 2004. Technical Report, http://public.itrs.net
  9. S. Borkar, T. Karnik, S. Narendra, J. Tschanz, A. Keshavarzi and V. De, Parameter variations and impact on circuits and microarchitecture, Proceedings 2003. Design Automation Conference (IEEE Cat. No.03CH37451), Anaheim, CA, USA, 2003, pp. 338-342, doi: 10.1145/775832.775920.
  10. Chen (IBM), ISS Europe 2007, (link).
  11. BCA Research (link).