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.

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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

Why Scale?

Figure 5: Semiconductor power density[6].
Figure 6: Calculations per second for a fixed cost[7].

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. https://upload.wikimedia.org/wikipedia/commons/0/00/Moore%27s_Law_Transistor_Count_1970-2020.png
  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. Karl Rupp, 42 Years of Microprocessor Trend Data, https://www.karlrupp.net/2018/02/42-years-of-microprocessor-trend-data/
  6. Chen (IBM), ISS Europe 2007, (link).
  7. BCA Research (link).