ADC research trends: Endangered performance parameters

Figure 1. Fraction of papers reporting a specific parameter.

SCIENTIFIC PRACTICES: In the previous post, your opinions on which parameters should be mandatory in an A/D-converter implementation paper were surveyed through a poll. In this one we will see what parameters actually get reported in scientific papers, and how the overall reporting practices have changed over time. We can also try to see how well Converter Passion reader’s opinions are in sync with harsh scientific reality

Working with the ADC survey, I had noticed that the set of measured performance parameters authors choose to report or omit changed over time. I’ve gathered the statistics, and it will be interesting to hear what you think of it. Figure 1 shows the percentage of papers reporting signal-to-noise-and-distortion ratio (SNDR), signal-to-noise ratio (SNR), spurious-free dynamic range (SFDR) and total harmonic distortion (THD) each year. The good news is that dynamic single-tone performance is more frequently reported in today’s papers than ever before. In fact, SNDR was reported in 96% of all papers from 2011. Both SNDR and SFDR show noisy but steadily increasing trends, and SFDR is now reported in around 68% of all papers (2011).

At the same time, SNR is increasingly being abandoned in favor of simply reporting SNDR instead. We can also see that THD is becoming an endangered parameter. SNR and THD have been in a visible decline after year 2000, and THD was only reported in 12% of the papers in 2011. SNR went from 60% in year 2000 to 41% 2011. These numbers trouble me. If the trend continues, we will know less about the noise in our A/D-converters for each year. I can’t possibly see how that can be of benefit to “Science” or to the reader. If you can, be sure to post a comment below.

Figure 2. Fraction of papers reporting specific combinations of parameters.

Above we looked at the reporting frequency for each individual parameter. Authors also choose which simultaneous combination or set of performance parameters they include in a paper. This is shown in Fig. 2. Many works report SNDR together with SFDR, and 67% of all papers from 2011 reported at least these two parameters. There is a strong positive trend, so within a decade we may see SNDR+SFDR reported in nearly all published papers. The second most popular parameter pair is SNDR+SNR, with 38% coverage in 2011. Unfortunately, its reporting frequency is limited by the negative trend for SNR.

A more complete single-tone characterization is achieved with the three-parameter combination SNDR+SNR+SFDR. Only 21% of all papers published in 2011 offer this much information about the circuit. Even if there is currently a positive trend, it might soon become limited by the decline in SNR reporting, and eventually reverse.

The practice to report a full four-parameter set is very unusual – only 9% of the papers did that in 2011. It has actually never been really common, and if THD continues to disappear from papers, the four-parameter performance will be increasingly rare. Lots of credit to authors that are still reporting a full set! It is much appreciated here at Converter Passion.

Rare species

Finally, a few other rare species in the ADC parameter ecosystem are shown in Fig. 3. While the highly valuable parameter self-noise appears to be on its way to extinction, intermodulation distortion (IMD) as represented by the second- and third-order intercept point (IP2, IP3) seems to cling to life in the outskirts of the habitat.

So … what do you make of all this? Do you think it will have any long-term impact on our field of science? Does it matter to you what parameters are reported or not? Have your say in the comments below.

And, what happened around year 2000 to shift the trends so dramatically? Was it the dot-com boom or the Y2K bug? (I haven’t heard about that one for a while now)

Figure 3. Endangered species in the parameter ecosystem.

ADC research trends: Overall publication count

The exponential growth in ADC publications

PUBLICATION TRENDS: Now, with all the new survey data, I’m planning to do a series of posts on A/D-converter performance evolution and research trends. First out is an update of the overall number-of-publications trend, which was originally discussed in one of the first post on the blog.

The graph shows the total number of ADC implementation papers per year in the sources listed here. The y-axis is logarithmic to simplify observation of exponential trends. My interpretation is that publication count follows a consistent exponential trend from 1988 and onwards. A log-fit of the data between 1988 and 2011 reveals that the number of A/D-converter papers have doubled approximately every decade since 1988, and that the annual increase is 6.8%. For anyone interested, the expression for the trend line is

If the scientific output volume follows the current trend, it projects to 225 ADC papers per year by 2020 and 433 papers in year 2030. That’s a lot of papers! Probably we’ll see a slow-down in publication volume before that, but only the future can tell us when, and to what level it will saturate. It is possible that we’re already observing a saturation towards ~120 papers/year. The paper count has not increased since 2008. On the other hand, the historical curve is not monotonic, so it could just as well be noise in the data. A similar four-year plateau is for example observed 1996-1999, without changing the overall trend.

What do you think? Are we observing a saturation of the scientific ADC output volume? Would that be good or bad? Is there a limit for how many papers the ADC community can handle per year? Share your thoughts or answer the polls.

 

Here’s an old poll which is still active:

ADC Survey: Spring 2012 update on FOM state-of-the-art

Will reading tons of ADC papers grow your brain — or wear it out?

Well folks, its the time of year when an A/D-converter survey update is due. Since a significant effort is still invested in the quest for ever-improving figures-of-merit (FOM), I’ll start by firing up the Converter Passion FOM-o-meter  and apply it to the body of ADC science. The latter is here approximated by my pet project – the ADC performance survey.

Including the papers added since last year, the updated survey now has 3628 experimental data points extracted from 1708 scientific papers published between 1974 and April/May 2012. The number of unique ADC implementations will be slightly less, since some papers are full-length versions of conference contributions. The source publications monitored are listed here.

What a difference a year makes …

… or not?

ISSCC/Walden-FOM

Can you believe this: With all the current competition to get a great ISSCC/Walden-FOM

the state-of-the-art (4.4 fJ) reported by van Elzakker et al. at ISSCC four years ago [1] is still number one. Their design really went the extra mile with respect to getting a low energy per sample, and I guess that paid off big time. Well done!

As Michiel commented, it is just a matter of time before someone goes below 4.4 fJ. This is also reflected in the scientific output over the last twelve months. Although the current world record didn’t change, there are several designs that reported an < 10 fJ, and that’s not bad either. They are:

FOM [fJ]	Speed [S/s]	ENOB	Architecture	1st Author	Ref
8.7	2M	8.27	SAR	Sekimoto	[2]
6.8	1k	8.52	SAR	Lu	[3]
6.5	4M	9.4	SAR	Harpe	[4]
6.1	1.1M	7.48	SAR	Shikata	[5]
6.8	10M	10.0	SAR	Verbruggen	[6]
9.7	250M	9.45	SAR	Verbruggen	[6]

The most striking feature is probably that they are all SAR ADCs. Secondly, while they are all impressive efforts, the one that stands out a bit is the design by Verbruggen et al. It maintains a sub-10fJ FOM at a significantly higher sampling rate (250 MS/s) while also reporting the highest resolution [6].

Although it’s beyond the scope of this post, it can be good to keep in mind that there are other aspects to factor in than simply the FOM value when analyzing energy efficiency. It was pointed out by Verbruggen [6] that previous ultra-low FOM ADCs have been reported only at rather low sampling rates or moderate resolution. It is a greater challenge to maintain a low for high sampling rates. Hence, pragmatic limits to the state-of-the-art are speed-dependent. It has also been shown that the limits are both scaling- and resolution-dependent [7, 8], so a perfectly fair comparison between designs is difficult to make. I can pretty much guarantee that I’ll get back to this topic in the future, but for the remainder of this post we’ll just look at the raw FOM numbers as they are.

Thermal FOM

It would have been boring to read another 100+ papers and still have nothing new to report, so I’m very glad to see that the so called “Thermal FOM”

has been improved by over a factor of two through the switched-opamp (SO) based ∆∑ design reported by Xu et al. [9]. Previous state-of-the-art – 2.7aJ reported by Perez et al. [10] – will assume its well-earned place in the Hall of Fame, while we applaud the 1.1 aJ achieved by the Chinese team from Zheijan University and Analog Devices, Shanghai. You’re the best now. Enjoy!

Thermal FOM for Nyquist ADCs

There has also been some evolution among the Nyquist ADCs: The 250MS/s SAR ADC by Verbruggen et al. mentioned above, is actually the new Thermal-FOM champion for Nyquist ADCs as it nudges the previous record [11] from 7.6 to 6.6 aJ. The authors are with imec, Belgium, and Renesas Electronics, Japan. Congratulations!

Old and new winners are always found in the halls of fame for Thermal and Walden FOM, respectively. If you are only interested in checking for the current leaders, the FOM-o-meter gives you both with a single click.

As always: I do believe the information here is correct, but if I’ve misrepresented anyone or forgotten to mention someone that should have been included, just send me an email or post a comment below.

References

[1] 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.

[2] R. Sekimoto, A. Shikata, T. Kuroda, and H. Ishikuro, “A 40nm 50S/s – 8MS/s Ultra Low Voltage SAR ADC with Timing Optimized Asynchronous Clock Generator,” Proc. of Eur. Solid-State Circ. Conf. (ESSCIRC), Helsinki, Finland, pp. 471–474, Sept., 2011.

[3] T.-C. Lu, L.-D. Van, C.-S. Lin, C.-M. Huang, “A 0.5V 1KS/s 2.5nW 8.52-ENOB 6.8fJ/Conversion-Step SAR ADC for Biomedical Applications,” Proc. of IEEE Custom Integrated Circ. Conf. (CICC), San Jose, California, USA, pp. 1–4, Sept., 2011.

[4] P. Harpe, Y. Zhang, G. Dolmans, K. Philips, and H. De Groot, “A 7-to-10b 0-to-4MS/s Flexible SAR ADC with 6.5-to-16fJ/conversion-step,” Proc. of IEEE Solid-State Circ. Conf. (ISSCC), San Francisco, California, pp. 472–473, Feb., 2012.

[5] A. Shikata, R. Sekimoto, T. Kuroda, and H. Ishikuro, “A 0.5 V 1.1 MS/sec 6.3 fJ/Conversion-Step SAR-ADC With Tri-Level Comparator in 40 nm CMOS,” IEEE J. Solid-State Circuits, Vol. 47, pp. 1022–1030, Apr., 2012.

[6] B. Verbruggen, M. Iriguchi, and J. Craninckx, “A 1.7mW 11b 250MS/s 2× Interleaved Fully Dynamic Pipelined SAR ADC in 40nm Digital CMOS,” Proc. of IEEE Solid-State Circ. Conf. (ISSCC), San Francisco, California, pp. 466–467, Feb., 2012.

[7] B. E. Jonsson, “On CMOS scaling and A/D-converter performance,” Proc. of NORCHIP, Tampere, Finland, pp. 1–4, Nov. 2010.

[8] B. E. Jonsson, “Using Figures-of-Merit to Evaluate Measured A/D-Converter Performance,” Proc. of 2011 IMEKO IWADC & IEEE ADC Forum, Orvieto, Italy, June 2011.

[9] J. Xu, X. Wu, M. Zhao, R. Fan, H. Wang, X. Ma, and B. Liu, “Ultra Low-FOM High-Precision ΔΣ Modulators with Fully-Clocked SO and Zero Static Power Quantizers,” Proc. of IEEE Custom Integrated Circ. Conf. (CICC), San Jose, California, USA, pp. 1–4, Sept., 2011.

[10] A. P. Perez, E. Bonizzoni, and F. Maloberti, “A 84dB SNDR 100kHz Bandwidth Low-Power Single Op-Amp Third-Order ΔΣ Modulator Consuming 140μW,” Proc. of IEEE Solid-State Circ. Conf. (ISSCC), San Francisco, USA, pp. 478-480, Feb., 2011.

[11] C. P. Hurrell, C. Lyden, D. Laing, D. Hummerston, and M. Vickery, “An 18 b 12.5 MS/s ADC With 93 dB SNR,” IEEE J. Solid-State Circuits, Vol. 45, pp. 2647-2654, Dec., 2010.

Back from ECCTD 2011

After the crystal-clear scientific presentations at ECCTD, I'm now back in the mist again.

So, I’m back from ECCTD 2011 since late Wednesday, and up here at the southern edge of the northern half of Sweden, the mornings are misty and the leaves are turning yellow. Visiting Linköping was every bit as pleasant as I had expected. The conference was held at Linköping Konsert & Kongress, which is beautifully located at the center of the city, right next to the Linköping Cathedral.

The conference

The conference was excellently organized by the Electronics Systems division at Linköping University and the conference committee. I was particularly impressed with the student helpers. Not only were they helpful, kind and attentive, but quite a few of them also turned out to be passionate about data-converter research and development [one of the healthier states of the human mind, BTW ] and we had several interesting conversations on the topic. I couldn’t possibly have felt more welcome.

Professor Borivoje Nikolić speaks about managing variability.

After we all had been welcomed by the conference general chair, prof. Lars Wanhammar, Linköping University, the conference started with a plenary presentation “Managing Variability for Ultimate Energy Efficiency” given by prof. Borivoje Nikolić from UC Berkeley, USA. The conference then split up into various sessions which are described in detail in the program. ECCTD is a rather broad conference, but there were at least three dedicated data-converter sessions: “Sigma-Delta Modulators“, “Data Converters“, and “Pipelined ADCs“. I had the honor of chairing “Pipelined ADCs“, and I presented my own contribution “Area Efficiency of ADC Architectures” in the “Data Converters” session. I might come back to the content of that paper in another post, but in short (for those of you that were not there), it surveys the chip area vs. performance in speed and resolution for just about every ADC implementation reported in the scientific literature all the way since 1974 – approximately 1500 papers. A normalized area measure

was proposed based on the observed correlation between absolute chip area (A) and effective resolution (ENOB). State-of-the-art A_Q – a.k.a. “Area per effective quantization step” – was seen to be independent not only of ENOB, but also of sampling rate over a broad range of sampling rates and resolutions, respectively. It is also approximately independent of CMOS process node. Chip area per effective quantization step was then compared for individual architectures, and design guidelines derived for area-optimal ADC architecture selection at any given speed and resolution specification. It was seen that there are large differences in the peak area efficiency achieved with different ADC architectures. There is for example a factor of 3 difference between SAR and pipeline, and a factor of 10 between pipeline and flash. Such big area differences can translate to a lot of money if you’re developing high-volume ADCs. So make sure you get hold of this paper as soon as it comes up on IEEE Xplore.

The blogger as session chair. Photo: Mark Vesterbacka

Professor Mark Vesterbacka, Linköping University had to push the electronics in his mobile phone to the maximum in order to document my chairing efforts in spite of the low light. Thanks for sending the picture.

CWCP winner

I could notice a slight peak in blog visitors yesterday. I assume that many of you wanted to know who won the Connect-with-Converter Passion (CWCP) prize, and I apologize for not being as fast as Dr. J Jacob Wikner who was blogging live from ECCTD and managed to fire away several conference-related post on Mixed-Signal Electronics while ECCTD was still developing. One of them correctly revealing that we had a CWCP winner already after the first day. And the winner is:

CWCP-winner Kiran Kariyannawar

Kiran Kariyannawar from Ericsson AB, who showed the enthusiasm and dedication necessary to win the CWCP prize for ECCTD. Congratulations Kiran! Kiran was there together with other Ericsson colleagues to demonstrate The Connected Tree and how to transmit audio and video signals through the human body. Quite far out compared to most demonstrations I’ve seen at scientific conferences. Very fun (at lest from a tech nerd’s perspective), and I’m sure they will figure out a lot of applications for it eventually, although for now they didn’t seem quite sure what to do with it. At least not with the connected tree. I played a bit with the human-body transmission (by becoming the channel), and I think it could be great for DJ-ing. I was just about to get it to rock big time when I started to realize the other delegates need for less noise and gave it up. If only I had a few more minutes to work out that groove …

The next big thing in DJ-ing? Just intermittently add a human body connected between those metal plates – preferably in a rhythmic pattern – and you're all set.

Other impressions

The conference dinner was held at the Air Force Museum – a place I’m likely to return to again to have more time to look at everything. Most likely with the rest of the family. A few photos below will give you some idea of the location. Finding unorthodox locations that can make the conference dinner extra memorable is probably a real challenge to most organizers. Unless they start taking us to outer space and back, I believe that the abundant food stations in combination with the breathtaking beauty of sea life shown at Monterey Bay Aquarium (ISCAS 1998) will remain my personal favorite for the rest of my life, but with ECCTD 2011 now being among the top two. Excellent work!

A classic Swedish beauty.

Chopper techniques. Large implementation.

A peaceful dinner ...

A missile of some kind, with a sign in Swedish saying "DO NOT PUSH HERE". Now, how irresistible is that on a scale to ten? Photo: M. Reza Sadeghifar

Having been to a few conferences, you start to recognize some faces that keep coming back. I had the pleasure of meeting delegates I’ve recently met. Some at NORCHIP, some at ICECS, and others at IWADC. It was great seeing you all. That is the real value of going to conferences.

Peace! 

ECCTD 2011 face-recognition. Note that we observed a severe Linköping bias here that might be compensated for in "future work".

The path to a good A/D-converter FOM

Figure 1. ENOB, power, and sampling rate trajectories showing the evolution path to the current state-of-the art FOM.

If you are participating in the scientific competition to report an ever better ADC figure-of-merit (FOM), you will find some pretty useful information in this post. Basically it will tell you where to start “drilling for oil”, and with a bit of persistence (preferably combined with some skill in the art) it might take you all the way to ISSCC 2013. The deadline for ISSCC 2012 is probably a bit too close for anyone to make a full ADC implementation according to these guidelines and still get it back in time from the foundry. But you can always try. I will give you a set of information about design and performance parameters that will enable you to predict quite accurately where in the design space the next state-of-the-art ADC (with respect to FOM) will be located. Remember that it could be your ADC, if you choose to optimize the speed-resolution-power tradeoff for this particular target.

First, let us clarify that we are talking about the most commonly used ADC figure-of-merit of all:

Figure 1 illustrates the trajectories of each of the three parameters in F_A1 as F_A1 improved over time. Click on the image to enlarge it. Only the data points representing an advance of F_A1 state-of-the-art, i.e., the monotonic decrease of F_A1 over time are used in the plot. Time was also quantized so that only the single best ADC per year appears in the trajectories. The underlying data set is gathered from 1600 scientific papers, and the same as used in [1]-[5]. The FOM axis and the FOM values for each dot are the same for all three plots, while the x axes show the simultaneous values of ENOB, power dissipation and sampling rate, respectively. These are the three parameters used to calculate the FOM, so any systematic trends in their trajectories are likely to be a good direction for a FOM-optimized design.

Figure 2. Approximate trajectory trends suggested by the plots.

Although there is plenty of noise in some of the trajectories, visual inspection suggests the approximate trends indicated in Fig. 2. At least it is my best guesstimate. It is purely ad hoc, and you are of course invited to discuss and refine my estimates by posting comments below. The most obvious trend applies to power dissipation (P), which has reduced by almost six orders of magnitude – from Watts to micro-Watts. At the same time the effective resolution (ENOB) has followed a more noisy, but visible path towards lower (medium) resolutions – from ~14 to currently 9-b ENOB. The change equals a three orders of magnitude increase in error power. Finally, the sampling rates at which state-of-the-art figures-of-merit were achieved have migrated slowly, from ~100 kS/s to 1–10 MS/s, even if state-of-the-art FOMs have occasionally been reported at several GS/s in the past. Looking at the f_s trajectory from a purely mathematical curve-fitting perspective, it would not support the trend suggested by the green curve. Weighing in some understanding of the speed-power tradeoff in actual design (described below), it makes a bit more sense. It appears thus, that the FOM is best improved by lowering the power dissipation and accepting a medium resolution, while running at moderate sampling rates.

Understanding the trajectories

In high-resolution ADCs, it can be shown that the power dissipation has a lower limit defined by the size of capacitors sized for a kT/C-noise in line with the target ENOB. The power used to drive these capacitors increase by 4X for every additional bit of resolution – in other words, as . It was shown in [3] and [4] that the break point where power dissipation becomes proportional to is currently @ 9-b ENOB for the most power efficient ADCs. It was also shown in [4] that F_A1 will always have a sweet spot at this break point.

Since F_A1 (erroneously) presupposes that P is proportional to (rather than ) for P and ENOB to be traded on equal terms, you will always improve F_A1 more by lowering P than by increasing ENOB – as long as ENOB ≥ 9. Below the 9-b break point, state-of-the-art P/f_s is approximately independent of ENOB [3]-[4],  which makes it meaningless to lower the resolution further, as it would only diminish the factor in F_A1 and do very little to reduce P/f_s. This is the reason why the trajectories has not migrated to even lower resolutions and dissipations – for example to a pathologically low ENOB with femto-Watt dissipation.

The reason state-of-the-art F_A1 values tend to be reported for 0.1–10 MS/s ADCs is perhaps less obvious. A reasonable assumption is that energy per sample (P/f_s) increase faster than linearly with f_s when sampling rates are pushed further, and therefore moderately fast designs are likely to have a more optimal P/f_s at any fixed ENOB.

Cookbook for an optimized FOM

It was shown in [2] that the state-of-the-art F_A1 also improves with every step of CMOS scaling. Including the parameter trajectories showed in this post, the recipe for a good A/D-converter FOM would be something like:

• Use the most deeply scaled CMOS process you possibly can.
• Aim for 8–9-b effective resolution, and a modest sampling rate.
• Use the lowest amount of power that will place you at the ENOB sweet spot, and let the measurements decide exactly what f_s you should claim in the paper

There are a few more tricks – some of which can be understood from [3] and some that I’ll save for clients and partners – but that’s more or less it. It will obviously help if you’re prepared to go the extra mile with your design, like the current record holders van Elzakker, et al. [6], who introduced multi-step charging of capacitors to further reduce P/f_s. Honing your design skills will help too, but essentially you’re now set to go out and design the next big scientific hit … 

Keep trying, and best wishes!

References

[1] B. E. Jonsson, “A survey of A/D-converter performance evolution,” Proc. of IEEE Int. Conf. Electronics Circ. Syst. (ICECS), Athens, Greece, pp. 768–771, Dec., 2010.

[2] B. E. Jonsson, “On CMOS scaling and A/D-converter performance,” Proc. of NORCHIP, Tampere, Finland, pp. 1–4, Nov. 2010.

[3] B. E. Jonsson, “An empirical approach to finding energy efficient ADC architectures,” Proc. of 2011 IMEKO IWADC & IEEE ADC Forum, Orvieto, Italy, pp. 1–6, June 2011.

[4] B. E. Jonsson, “Using Figures-of-Merit to Evaluate Measured A/D-Converter Performance,” Proc. of 2011 IMEKO IWADC & IEEE ADC Forum, Orvieto, Italy, pp. 1–6, June 2011.

[5] B. E. Jonsson, “Area Efficiency of ADC Architectures,” Accepted for presentation at Eur. Conf. Circ. Theory and Des. (ECCTD), Linköping, Sweden, Aug., 2011.

[6]    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.