ADC Energy Efficiency Trends


Fig. 1. State-of-the-art energy per sample vs. ENOB in five-year steps from 1983 to 2013.

Fig. 1. State-of-the-art energy per sample vs. ENOB in five-year steps from 1983 to 2013.

ADC ENERGY EFFICIENCY EVOLUTION: What are the trends for ADC energy efficiency and why did the “Walden” figure-of-merit get almost canonical status when it doesn’t fit to current data? Read on, and you’ll know.

Evolution front

Figure 1 shows how the state-of-the-art boundary for energy-per-sample (Es) vs. effective-number-of-bits (ENOB) has progressed over time in 5-year steps from 1983 to 2013. The energy vs. resolution dependencies suggested by the Walden and Thermal figures-of-merit (FOM) have been indicated as the Walden and Thermal slope, respectively.

Snow cone scatter

The most immediately striking feature in Fig. 1 is that the curves are increasingly more separated at lower resolutions, and tend to group more closely together as ENOB increases. With the Thermal and Walden slopes overlaid as in Fig. 1, you get a kind of “snow cone scatter plot”. It means that the energy efficiency has improved far more for low-resolution ADCs than for high-resolution converters during the 30 years of research covered by Fig. 1. A possible explanation for that is the fairly low number of attempts reported above 15-b ENOB. Another reason could be that the power dissipation at ultra-high resolution almost inevitably becomes limited by thermal noise constraints, and that the few reported designs were carefully optimized. As an example, the work by Naiknaware et al. [1] is the only scientific ADC reporting an ENOB > 20-b (other works only report static linearity or measures that did not resolve to an SNDR value). Although Naiknaware’s design was reported as early as year 2000, it is still on par with today’s noise-limited state-of-the-art. That’s quite impressive!

Slope twist

A second distinct feature in Fig. 1 is that the slope for Es vs. ENOB has changed over time from an almost perfect Walden FOM model (doubling of Es per additional bit) to an almost perfect Thermal FOM model (quadrupling of Es per additional bit).

This explains the great mystery of the Walden FOM and its near-canonical status: Even as late as 2003, the state-of-the-art edge aligned very well with a Walden model. In fact, the Walden model remained true to empirical data all the way to 2007. By 2008, however, the experimental data had started to break away from the Walden slope – something that was also noted by Murmann in his well-known CICC 2008 paper [2] – and by 2013 the experimental data fits more or less perfectly with the thermal-noise model.

The van Elzakker leap

The single most influential contribution to this shift is probably that by van Elzakker et al. [3] as it represented nothing less than a quantum leap in energy efficiency for ADCs in the lower mid-range of resolutions. It gave us a new experimental data-point that completely redefined the energy landscape as it showed their medium-resolution design to be pushed all the way to the thermal-noise power limit of 2008. I believe their contribution broke a mental barrier for many regarding how far you can actually go, and what is the real energy limit. Over the last five years, other authors have followed by reporting more experimental data – both filling the gap created by the van Elzakker leap and pushing efficiency even further [4]-[6].

Low-resolution plateau

As always, we have the low-resolution plateau. There is a slight tendency towards a plateau already in the 1998 curve, and by 2003 it was fully visible – although at a much higher Es level than today’s plateau. Figure 1 also shows us that there has been significant progress at resolutions below 9-b over the 20 years from 1988 to 2008, but almost no movement at all during the last 5 years. The relative amount of attempts below 9-b (~35%) has remained the same both before and after 2008, so it should not be due to lack of interest.

Any explanations you might have would be very interesting to hear. Pure speculations are fine too 😉

Hopes and expectations for the future

In coming years I would expect to see progress in the 10–13 bit region, which seems to be a bit underexplored at the moment. We saw an extension in this direction by the most recent state-of-the-art work by Harpe et al. [4]. I hope that future authors will continue to push the resolution for ultra-efficient ADCs. It should be possible to “iron out the wrinkles” on the current state-of-the-art border. It would be particularly nice if we could populate the border with evenly spaced SAR implementations spanning all the way up to the high resolution of commercial SAR ADCs.

I also hope that someone will explore the empty space below the low-resolution plateau. It seems to be a lot of data points missing there that could give us a better understanding of the true energy limits.

More data at ultrahigh resolution – please!

Finally, I want to plead to those of you designing ultrahigh resolution ADCs to start including traditional dynamic performance measures (at least SNDR) even if the target application you’re imagining doesn’t care about it. If nothing else, it would increase your visibility in my scatter plots, but the main benefit for our science is that we would get more experimental data and a better understanding of the design space for “20-b and beyond”.

So, please … 🙂

References

  1. R. Naiknaware, and T. Fiez, “142dB ∆∑ ADC with a 100nV LSB in a 3V CMOS Process,” Proc. of IEEE Custom Integrated Circ. Conf. (CICC), Orlando, USA, pp. 5-8, May, 2000.
  2. B. Murmann, “A/D converter trends: Power dissipation, scaling and digitally assisted architectures,” Proc. of IEEE Custom Integrated Circ. Conf. (CICC), San Jose, California, USA, pp. 105–112, Sept., 2008.
  3. M. van Elzakker, E. van Tuijl, P. Geraedts, D. Schinkel, E. Klumperink, and B. Nauta, “A 1.9μW 4.4fJ/Conversion-step 10b 1MS/s charge-redistribution ADC,” Proc. of IEEE Solid-State Circ. Conf. (ISSCC), San Francisco, California, pp. 244–245, Feb., 2008.
  4. C.-Y. Liou, and C.-C. Hsieh, “A 2.4-to-5.2fJ/conversion-step 10b 0.5-to-4MS/s SAR ADC with Charge-Average Switching DAC in 90nm CMOS,” Proc. of IEEE Solid-State Circ. Conf. (ISSCC), San Francisco, USA, pp. 280–281, Feb., 2013.
  5. P. Harpe, E. Cantatore, and A. van Roermund, “A 2.2/2.7fJ/conversion-step 10/12b 40kS/s SAR ADC with Data-Driven Noise Reduction,” Proc. of IEEE Solid-State Circ. Conf. (ISSCC), San Francisco, USA, pp. 270–271, Feb., 2013.
  6. H.-Y. Tai, H.-W. Chen, and H.-S. Chen, “A 3.2fJ/c.-s. 0.35V 10b 100KS/s SAR ADC in 90nm CMOS,” Symp. VLSI Circ. Digest of Technical Papers, Honolulu, USA, pp. 92–93, June, 2012.
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6 responses to “ADC Energy Efficiency Trends

  1. Are there any studies that attempt to relate converter technology to maturity (perhaps as expressed in volume production or price). e.g. If I am using a prototype A/D that costs $40K at some sample rate & ENOB, how long will it be before that is available at prices that could be used in production (lets say $50). I assuming cost and production quantities are related.

    • Gregory, I’m sorry your comment was left forgotten in moderation queue for so long (only the first one requires moderation).

      About the study, I don’t know of anyone like that. I’ve been collecting pricing info together with the tech data for commercial ADCs with the intention of eventually studying cost-performance “boundaries” and similar.

      To see how long it typically takes to drop from “novelty/cutting-edge performance” to “commodity” pricing, one would need a longer sequence of historic pricing data which I unfortunately don’t have, and suspect it would take a really long time to accurately collect. With a bit of luck, someone else will have this data and feel like making the interesting study that you suggest.

      /Bengt

  2. I want to commend you on your plots and also on your discussion of the Van Elzakker SAR paper from 2008. It was a FoM champion until ISSCC 2013 if I remember correctly. I have used some of the circuits from that paper myself. I didn’t know anyone was blogging specifically about data converters with this level of detail and I have entirely enjoyed reading what little I have had time to read this evening. My thanks to you for writing all of this and I will definitely be browsing back over here and reading quite a bit more of what you have taken the time to write down.

  3. Mads Lauridsen

    Hi Mr. Jonsson,
    I have read your blog with great interest!
    I’m currently trying to understand what the ADC energy efficiency will be in 2020 (I’m working on one of the many emerging wireless 5G projects) and therefore I have also studied your predictions regarding the FOM evolution.
    My question is whether you plan to present (or have seen somewhere else) a view on the evolution in sample rate vs. power consumption, and ENOB vs. power consumption. The optimum would be a 3d plot comparing both ENOB, sample rate, and power consumption.

    In my opinion the FOM is not so informative in this respect since an ADC with low FOM may have a very low ENOB and a high sample rate or vice versa, and in that case not be useful for a mobile phone. I expect such a 5G phone to require 10-12 ENOB and handle a channel bandwidth of at least 100 MHz.

    Currently I see the ADC as one of the major challenges for 5G, not only due to the ENOB and sample rate requirements (leading to possibly high power consumption), but also because there will be a need for many ADCs in each phone due to both carrier aggregation and multiple spatial streams. This will obviously affect both cost and size of the device.

    I look forward to reading your view on this topic.

    Best regards,
    Mads

    P.S. Feel free to contact me directly via e-mail

    • Thanks Mads,
      Good points. I’ll need to think a bit before producing any numbers, but I completely agree that simply a FOM doesn’t give you what you need in this case. A few graphs in response to your question could perhaps make for an interesting post. I have a few ideas that (if they tur out the way I hope) I might bounce with you directly first to see what you think.
      /Bengt

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