ADC performance evolution: Thermal figure-of-merit (FOM)

Figure 1. Evolution of best reported thermal FOM for delta-sigma modulators (o) and Nyquist ADCs (#). Monotonic state-of-the-art improvement trajectories have been highlighted. Trend fit to state-of-the-art points for DSM [1984–2000] (dotted), and Nyquist [1982–2012] (dashed). Average trend for all designs (dash-dotted) included for comparison.

POWER EFFICIENCY TRENDS (continued): As mentioned in the previous post, a slightly different FOM, sometimes labeled the “Thermal FOM” [1]-[2], has been proposed in order to better compare high-resolution ADCs limited by thermal noise. The thermal FOM, F_B1, is expressed as

The thermal FOM considers error power rather than amplitude (as in the Walden FOM), and therefore the value of F_B1 improves by 4× (rather than 2×) for every additional bit of resolution. This matches the theoretical 4× minimum increase in power if ENOB is limited by kT/C-noise [3] and the architecture remains unchanged [4]. It was shown in [5] that the thermal FOM represents a better description of the state-of-the-art power-resolution tradeoffs according to empirical data than the Walden FOM for ENOB ≥ 9.

As seen in Fig. 1, there is a significant difference between DSM and Nyquist ADCs with respect to F_B1. With the exception of two early 14-b designs [6]-[7], the global state-of-the-art is defined entirely by delta-sigma modulator implementations while Nyquist ADCs lag distinctly behind. A possible explanation could be that the thermal FOM favors converters whose power dissipation is truly limited by thermal noise, and that high-resolution ∆-∑ ADCs are more distinctly driven into the thermal noise limit than their Nyquist counterparts. Another point is that many scientific DSM implementations use an off-chip (i.e., zero power) decimation filter implemented in software. This will give DSM an unfair advantage over Nyquist, although it can hardly be the only explanation for a one order of magnitude FOM difference.

Since the thermal FOM for Nyquist converters has evolved over a rather uneven path, I’ll not make any elaborate interpretations of its shape. The trend (dashed) is simply fitted to all the state-of-the-art points from 1982–2012, revealing an average improvement rate of 2× every two years. The DSM envelope appears to have three main segments with breakpoints at 1990 and 2000, respectively. For simplicity, a single trend was estimated for the envelope until Naiknaware [8], after which the thermal FOM has evolved significantly slower. From Fiedler [9] to Naiknaware, the average improvement rate is 2× every 17 months (1.4 years) – again faster than Moore’s Law [10]-[11] – whereas from year 2000 to present day [12], the state-of-the-art points fit to a more modest 2×/5.5 years slope. Even if the latter is from a fit of only four data points, and the exact slopes can be discussed, it is clear from Fig. 2 that the thermal FOM for DSM experienced a distinct slowdown after year 2000. This coincides with the breakpoint where the relative noise floor – approximately the denominator in (1) – also goes into saturation. It can further be noticed that it coincides with the accelerated evolution of F_A1 as well. A possible, but perhaps speculative interpretation is that the ADC community first focused on thermal noise performance and related design optimization, and after hitting the noise floor around year 2000 moved on to focus on power efficiency.

If you wish to suggest other explanations, please share them below.

This concludes a series of ten posts on ADC performance and technology trends. If you want to go back and read them all from the beginning, these are the topics and the order in which they were posted:

1. CMOS node adoption
2. Low-voltage operation – part 1
3. Low-voltage operation – part 2
4. Thermal noise
5. Jitter
6. Relative noise floor
7. Linearity (SFDR)
8. Sampling rate and resolution
9. Walden FOM
10. Thermal FOM (this post)

As a small postlude, a follow-up post will list known prior art ADC surveys for those of you that (like myself) have an insatiable appetite for technology trend estimations and empirical data dots.

See also …

ADC survey data

References

1. A. M. A. Ali, C. Dillon, R. Sneed, A. S. Morgan, S. Bardsley, J. Kornblum, and L. Wu, “A 14-bit 125 MS/s IF/RF sampling pipelined ADC with 100 dB SFDR and 50 fs jitter,” IEEE J. Solid-State Circuits, Vol. 41, pp. 1846–1855, Aug, 2006.
2. C. Wulff, and T. Ytterdal, “Design of a 7-bit, 200MS/s, 2mW pipelined ADC with switched open-loop amplifiers in a 65nm CMOS technology,” Proc. of NORCHIP, Aalborg, Denmark, Nov., 2007.
3. 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.
4. K. Bult, “Embedded analog-to-digital converters,” Proc. of Eur. Solid-State Circ. Conf. (ESSCIRC), Athens, Greece, pp. 52–60, Sept., 2009.
5. 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. [PDF @ IMEKO]
6. R. J. van de Plassche, and H. J. Schouwenaars, “A Monolithic 14 Bit A/D Converter,” IEEE J. Solid-State Circuits, Vol. SC-17, pp. 1112-1117, Dec., 1982.
7. T. Sugawara, M. Ishibe, H. Yamada, S.-I. Majima, T. Tanji, and S. Komatsu, “A Monolithic 14 Bit/20 µs Dual Channel A/D Converter,” IEEE J. Solid-State Circuits, Vol. SC-18, pp. 723-729, Dec., 1983.
8. 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.
9. H. L. Fiedler, and B. Hoefflinger, “A CMOS Pulse Density Modulator for High-Resolution A/D Converters,” IEEE J. Solid-State Circuits, Vol. SC-19, pp. 995-996, Dec., 1984.
10. G.E. Moore, “Cramming more components onto integrated circuits,” Electronics, Vol. 38, No. 8, Apr. 1965.
11. G. E. Moore, “No exponential is forever: but “forever” can be delayed!,” IEEE ISSCC, Dig. Tech. Papers, San Francisco, CA, Feb. 2003, pp. 20–23.
12. 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.

ADC performance evolution: Walden figure-of-merit (FOM)

Figure 1. Evolution of best reported Walden FOM for delta-sigma modulators (o) and Nyquist ADCs (#). Monotonic state-of-the-art improvement trajectories have been highlighted. Trend fit to DSM (dotted), and Nyquist (dashed) state-of-the-art. Average trend for all designs (dash-dotted) included for comparison.

POWER EFFICIENCY TRENDS: A series of blog posts on A/D-converter performance trends would not be complete without an analysis of figure-of-merit (FOM) trends, would it? We will therefore take a look at the two most commonly used FOM, starting with the by far most popular:

where P is the power dissipation, f_s is Nyquist sampling rate, and ENOB is the effective number of bits defined by the signal-to-noise and-distortion ratio (SNDR) as:

F_A1 is sometimes referred to as the Walden or ISSCC FOM and relates the ADC power dissipation to its performance, represented by sampling rate and conversion error amplitude. The best reported F_A1 value each year has been plotted for delta-sigma modulators (DSM) and Nyquist ADCs in Fig. 1. Trajectories for state-of-the-art have been indicated, and trends have been fitted to these state-of-the-art data points. The average improvement trend for all ADCs (2×/2.6 years) is included for comparison.

By dividing the data into DSM and Nyquist subsets, it is seen that delta-sigma modulators have improved their state-of-the-art FOM at an almost constant rate of 2×/2.5 years throughout the existence of the field – just slightly faster than the overall average. State-of-the-art Nyquist ADCs have followed a steeper and more S-shaped evolution path. Their overall trend fits to a 2× improvement every 1.8 years, although it is obvious that evolution rates have changed significantly over time. A more accurate analysis of Nyquist ADC trends should probably make individual fits of the early days glory, the intermediate slowdown, and the recent acceleration phase. This was done in [1] where evolution was analyzed with DSM and Nyquist data merged. However, for simplicity I’ll just stick to the more conservative overall Nyquist trend. [I wouldn’t want anyone to suggest that I’m producing “subjective” or “highly speculative” trend estimates, would I? 😉 ]

Still, if anyone is curious to know … 🙂 … the state-of-the-art data points fit to a 2×/14 months trend between 2000 and 2010. That’s actually faster than Moore’s Law, which is traditionally attributed a 2×/18 months rate [2]-[3]. A new twist on “More than Moore”, perhaps? Even the more conservative overall 2×/21 months trend is close enough to conclude that the state-of-the-art FOM for Nyquist ADCs has developed exponentially in a fashion closely resembling Moore’s Law. And that’s got to be an impressive trend for any analog/mixed circuit performance parameter.

Irrespective of what’s the best fit to data, it should be evident from Fig. 1 that Nyquist ADCs broke away from the overall trend around year 2000, and has since followed a steeper descent in their figures-of-merit. They have also reached further (4.4 fJ) [4] than DSM (35.6 fJ) [5]. The overall trend projects to a 0.2 fJ ADC FOM in 2020. Whether or not that’s possible, we’ll leave for another post. A deeper look at the data also reveals that:

• The acceleration in state-of-the-art is almost completely defined by successive-approximation (SAR) ADCs [4], [6]-[11], accompanied by a single cyclic ADC [12]. The superior energy efficiency of the SAR architecture was empirically shown in [13].
• A significant part of the acceleration can be explained by the increased tendency to leave out, for example I/O power dissipation when reporting experimental results – a trend also observed by Bult [14]. The FOM in the graph was intentionally calculated from the on-chip rather than total power dissipation because: (a) ADCs are increasingly used as a system-on-chip (SoC) building block, which makes the stand-alone I/O power for a prototype irrelevant, and (b) Many authors don’t even report the I/O power anymore.
• F_A1 has a bias towards low-power, medium resolution designs rather than high-resolution, and thus benefits from CMOS technology scaling as shown in [15],[16]. An analysis of the underlying data shows that, for the best F_A1 every year, the trajectories for ENOB and P follows distinct paths towards consistently lower power and medium resolution. You simply gain more in F_A1 by lowering power dissipation than by increasing resolution because (1) does not correctly describe the empirically observed power-resolution tradeoff for ADCs [13],[15].

In order to compare high-resolution ADCs limited by thermal noise, it has therefore been proposed to use a slightly different FOM, sometimes labeled the “Thermal FOM” [17]-[18],

This figure-of-merit will be the topic of the next post.

See also …

ADC survey data

Walden’s survey [19]

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. G.E. Moore, “Cramming more components onto integrated circuits,” Electronics, Vol. 38, No. 8, Apr. 1965.
3. G. E. Moore, “No exponential is forever: but “forever” can be delayed!,” IEEE ISSCC, Dig. Tech. Papers, San Francisco, CA, Feb. 2003, pp. 20–23.
4. 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.
5. 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.
6. 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.
7. 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.
8. S.-K. Lee, S.-J. Park, Y. Suh, H.-J. Park, and J.-Y. Sim, “A 1.3µW 0.6V 8.7-ENOB Successive Approximation ADC in a 0.18µm CMOS,” Symp. VLSI Circ. Digest of Technical Papers, Honolulu, USA, pp. 242–243, June, 2009.
9. H.-C. Hong, and G.-M. Lee, “A 65-fJ/Conversion-Step 0.9-V 200-kS/s Rail-to-Rail 8-bit Successive Approximation ADC,” IEEE J. Solid-State Circuits, Vol. 42, pp. 2161–2168, Oct., 2007.
10. M. D. Scott, B. E. Boser, and K. S. J. Pister, “An Ultra-Low Power ADC for Distributed Sensor Networks,” Proc. of Eur. Solid-State Circ. Conf. (ESSCIRC), Firenze, Italy, pp. 255–258, Sept., 2002.
11. M. D. Scott, B. E. Boser, and K. S. J. Pister, “An Ultralow-Energy ADC for Smart Dust,” IEEE J. Solid-State Circuits, Vol. 38, pp. 1123–1129, July, 2003.
12. D. Muthers, and R. Tiekert, “A 0.11mm2 low-power A/D-converter cell for 10b 10MS/s operation,” Proc. of Eur. Solid-State Circ. Conf. (ESSCIRC), Leuven, Belgium, pp. 251–254, Sept., 2004.
13. 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. [PDF @ IMEKO]
14. K. Bult, “Embedded analog-to-digital converters,” Proc. of Eur. Solid-State Circ. Conf. (ESSCIRC), Athens, Greece, pp. 52–60, Sept., 2009.
15. 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. [PDF @ IMEKO]
16. B. E. Jonsson, “On CMOS scaling and A/D-converter performance,” Proc. of NORCHIP, Tampere, Finland, Nov. 2010.
17. A. M. A. Ali, C. Dillon, R. Sneed, A. S. Morgan, S. Bardsley, J. Kornblum, and L. Wu, “A 14-bit 125 MS/s IF/RF sampling pipelined ADC with 100 dB SFDR and 50 fs jitter,” IEEE J. Solid-State Circuits, Vol. 41, pp. 1846–1855, Aug, 2006.
18. C. Wulff, and T. Ytterdal, “Design of a 7-bit, 200MS/s, 2mW pipelined ADC with switched open-loop amplifiers in a 65nm CMOS technology,” Proc. of NORCHIP, Aalborg, Denmark, Nov., 2007.
19. R. Walden, “Analog-to-digital conversion in the early twenty-first century,” Wiley Encyclopedia of Computer Science and Engineering, pp. 126–138, Wiley, 2008.

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.

<- Previous update | Next update ->

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. [PDF @ IMEKO]

[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.

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. [PDF @ IMEKO]

[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. [PDF @ IMEKO]

[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.

Going to Linköping … Yes, Yes, Yes!!

Curves like these can be really useful if you're going for small chip area. Those who attend ECCTD 2011 will get the full picture and learn what's on the X and Y axes.

You’d be forgiven to think that, with all the praise I recently gave to Italy and the IWADC conference, there’s no room in my heart for any other conference or location. But going to the European Conference on Circuit Theory and Design in Linköping, Sweden will be very special. The location isn’t nearly as exotic to me as Italy – quite the opposite in fact. I used to study in Linköping, and I was also a PhD student at the very department that is hosting the conference. What is special with Linköping is that it’s the city I used to call home for about 15 years of my life – 15 good years filled with memorable moments, good friends and talented engineers and scientists. It’s a nice Swedish town, and I highly recommend you to go there. ECCTD 2011 offers the perfect excuse.

If, like me, you’re also interested in what’s actually presented at the conference, it too is an excellent reason to go there. I guess there will be a conference program up on the conference site sooner or later. Until then I can only tell you about my contribution “Area Efficiency of ADC Architectures”, which I was very glad to get accepted. No extra points for guessing the general topic of the paper, and I’m not going to spoil the fun by telling you everything about it. Suffice to say that it’s another huge survey of scientific A/D-converter achievements. This time we’ll take a first look at the area-efficiency of various ADC architectures at different speed/resolution specifications. It exemplifies a small fraction of the EDO methodology used by ADMS Design AB, and gives you some overall guidelines to get you started with area-optimized ADC design.

So, if you design ADCs for high volume production and a low manufacturing cost is important … don’t miss this paper.