Systematic Mismatch - English Version
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- เผยแพร่เมื่อ 20 ก.ย. 2024
- This video contain Systematic Mismatch in English, for basic Electronics & VLSI engineers.as per my knowledge i shared the details in English.
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Thank you. So I understand, oxide thickness variation (your delta) is very causal in mismatching as compared to doping or ion implanting? So we can apply your delta strategy to optimize our layout. If we do this properly, we can correct for oxide thickness variations on the wafer? As a result, we have ALSO corrected for mismatches from other sources - like doping and ion implanting - simultaneously?
One of the pain points in the design of Semi-conductor product is that its components (hence its performance) vary a lot across process, power supply voltage and ambient temperature whereas customers would prefer a part whose behaviour is identical from part to part (i.e., across wafer processing) and across voltage and temperature as their customers would demand the same. This is obvious because variability in performance parameters makes quality control difficult and may cause disappointments in the end user. Hence it becomes a competitive advantage for semi-conductor vendors if behaviour of his product is tightly controlled and rock-solid in any application. Hence, all designers across the industry break their back, day and night to make their products less variable (Data sheet parameter tighter) than their competitors.
This is where concept of matching may come to rescue designers. The basic concept around matching is that absolute value of device parameters like W, L, threshold, gate capacitance etc varies a lot across process corners, voltage and temperature (PVT) but ratio of parameters does not vary much if two devices are identical and close to each other. This is an extremely useful idea which can be exploited to design robust circuits across PVT.
The variation in ratio of parameters in matched device is less but not zero. Hence designers need to know this information. These days every Fab process PDK comes with matching models for most of the devices. Like any other process parameter, one would expect that min and max value of matching parameter would be provided. But instead of min/max value of the matching parameter, it is specified in terms of statistical parameter. It is assumed that matching would follow a normal distribution and standard deviation is specified in the model. Standard deviation is a function of dimension of devices. Bigger size gives lower standard deviation. For a given Fab process, constants of the function are provided in the model.
I believe, there is nothing special about matching that it had to be specified in terms of statistical parameters. Generally other parameters like threshold, mobility, gate capacitance etc are also random and follow normal distribution. These parameters are part of Wafer Acceptance Test (WAT) and min/max value are set to accept or discard a given wafer. Whereas matching is not part of WAT and hence it is difficult to specify its min/max value in the model.
Matching distribution model is valid for only those devices that are identical, at minimum distance with each other and which have identical surroundings also. Now question is till what distance surroundings should be identical. I think, more the distance, more likely is that simulation would match silicon behaviour. So as many dummy devices should be put around the matching devices as possible. Another question is what happens for those devices which are far apart. In those devices, there is another component of mismatch which is systematic and called gradient error. In the model, this component is absent. This is taken care in the layout by doing common centroid layout. It is believed that by doing common centroid layout, gradient error can be canceled altogether. In most cases, it is very difficult to accomplish common centroid layout. For example, it may not be possible to choose a common element. And ratio of the device sizes (for example; 1:3) may not be suitable for common centroid layout. Even if it is achieved, it would probably cancel only first order gradient error. So depending on common centroid layout may not be adequate where very accurate matching is the requirement.
There is a trade-off between random error and systematic error. Random error reduces if device size is bigger whereas systematic error increases if distance between devices is more. Bigger device size means larger distance between devices. So there would be a optimum device size for best matching for a given design structure. However, I am not sure whether anybody looks at this aspect of the matching. If model for gradient errors is also provided by the Fab, then it would be easier to get the optimum size in simulation itself otherwise it has to be learnt through test chip.
Generally before tapeout, just Monte-Carlo simulation is run to predict the effect of matching on the performance parameter. I think, this is not sufficient for many cases and other aspects mentioned above needs to be taken into account.
@Analog Layout
Systematic mismatch has nothing to do with process mismatch .. as you said in your slide at the top ..process mismatch happens because of process condition variations while systematic mismatch are due to different parameters like over etch lateral diffusion locos process well proximity effects .. please refer to johns martin books for more information
Hi sir can you explain deep nwell concept clearly.
As soon , IL explain
hello sir,
according to your mismatches video1 (random mismatches) thickness of wafer,etching and all process variations all are not in our control. but in your 2nd(systematic mismatches) video we are control those effects by following the good layout methods.am try to understand but i cont . can you please explain if you have time.
Sure
So there are three different mismatches that you should know
Systematic mismatch which can be corrected by proper layout techniques systematic mismatches are occurred because of over etching lateral diffusion etc . These can be reduced by layout techniques like common centroid etc
Random mismatches are because of say dopant variations these are random in nature and difficult to eliminate complete .. vt mismatch is the main mismatch .. larger device size reduce these mismatch .. read pelgram ieee paper on this ..
Third is process mismatch which designers can’t control .. it is because of variation in process conditions like temperature , equipment Changes etc .. we do corner analysis for process mismatch which checks with max min models ...
We do more Carlo analysis to see device mismatches with statistical models ... not corner modes ...
sir explain about finfet if its possible
asap , all the topic il try to upload
how can do get job opportunities for analog layout engineeries
take a proper training , and try .... every whr its available
i know training but physical design versus analog latout versus verification ......difference
@@shanmukhadasari8650 if u can work with some script & coding u can go PD , verification is fully based on programming skill , layout is regardless of coding & scripts with full of basic electronics
Uppload Deep Newell as well as finfet sir
linux commands explain plz