Flash Hit Its Physical Limit. ReRAM Is the Replacement: WeeBit Nano's Ilan Sever

0:00There is a memory in almost every chip that nobody talks about, and it holds a few kilobytes to a few megabytes. It has no, like, spot price or a super cycle. But without it, most chips, analog especially, can't work or even meet the specs on its datasheet. So for 30 years, that memory has been embedded flash. But as we get to smaller technology nodes, it really stops working. today's guest designed Embedded Flash and then spent the rest of his career on what comes after it.

0:36Hey, welcome to another episode of Semi-Doped Podcast. I'm Vic Shaker, the founder of Semi-Exponent, where I do boutique research on semiconductors and AI infrastructure. I also write Vic's newsletter on Substack, one of the top 20 technology newsletters on the platform covering AI and semis. I come from two decades of working in the semiconductor industry and my work now is taking that engineering background and explaining what matters in the technology and why it matters to the markets. Check out VIX newsletter on Substack and for technology research reach out to me at SemiExponent. And our guest today is Ilan Severe, Chief Memory Architect at VBitNano.

1:16He has spent over 30 years in non-volatile memory, semiconductor IP and SOC design. He was previously group CTO at Dolphin Design, director of IP and libraries at Tower Semi, and design manager of flash memory at ST Microelectronics. Ilan, welcome to the podcast.

1:37Ilan Sever: Happy to be here, Vik. Awesome. So I guess one of the things that we don't often talk about is what exactly are non-volatile memories? Because when I mentioned flash memory, that's there pretty much everywhere. But it is so ubiquitous that people have even stopped thinking about it in the mainstream. It is assumed to be there, but it's still a very important part of all of our electronics. and it's not just like DRAM and SRAM. That's the whole problem, right? So you've worked on this stuff before. So let me start by going through your journey. What made you get started on working on flash memory?

2:23Ilan Sever: Yes, thanks, Vic. So yes, non-volatile memory is basically a fundamental element of any electronic system. It's where you store your software code and your parameters and anything that you would like to stay even when the power goes away. So we all have systems in which the battery can run out or we shut it down, but when we power it back up, everything goes back to life. So where is this stored? All this information is stored in non-volatile memory, meaning a memory that doesn't need the power in order to retain the data. So you mentioned flash memory in the technology of choice, even today in what we call NAND storage, like your phone storage is what we call NAND flash.

3:23Ilan Sever: I'm not talking about this technology. We are now referring to technologies which are embedded within system on chips on silicon. and this was previously served with embedded flash, which is a no-type flash. Basically, flash technology is storing charge on some floating gates, so there is some capacitance which is charged, and it returns there even if you shut the power down, and that's how flash works. As you mentioned, flash doesn't scale well. So in geometries below 28 or 22 nanometer, flash reached its physical limit, actually. So physically, you cannot implement embedded flash anymore. And the industry had been looking for alternative technologies for a few decades now.

4:26Ilan Sever: and we will talk today about one of these technologies that is now gaining really market and acceptance, which is resistive RAM. Awesome. That's a great introduction. So for people listening, we always talk about static RAM, SRAM, which holds the state, but it holds information without having to be refreshed. However, if you turn off the power to that SRAM, you're going to lose everything in the SRAM. Like you switch off your computer, your OS is removed from the SRAM and all of that stuff. So on dynamic RAM, I think it's more like you have to keep refreshing it. But of course, you take power out, that goes out too.

5:15Non-volatile memory that, Ilan, that you were mentioning is that it's the stuff that stays all the time on and even if you turn off your phone, it holds information and that's very important because your devices just can't forget stuff all the time. So we'll definitely get to why eFlash stops scaling as we went to smaller nodes and what resistive RAM means but I just want to step back just a little bit and say exactly what is the role of non-volatile memory in a device? It could be an embedded device or a sensor or a power controller or an automotive chip, whatever it is, what is the role of this non-volatile memory?

5:59What does it actually hold?

6:01Ilan Sever: Yeah, that's a very good question, Vic. So fundamentally, I would say the base usage or the most wide usage is for any embedded MCU or microprocessor, it has its software. And if you want to have a really embedded, whether it's an IoT device, a medical device, your hearing aid, or whatever device that needs to be compact, low power, fully embedded, without additional external chips, you would like to have your code inside the same system on chip. You have an MCU, whether it's, you know, one of any MCU architecture, it would need to run some firmware, which is software. Like a microcontroller, right?

7:00Like MCU is a microcontroller unit, and it has to have, it has to run some code. The question is, where does it get this code from?

7:07Ilan Sever: So, of course, if you want the code to be there, even when someone is replacing batteries, or maybe the battery is out, or even applications that don't have power all the time. You know, there are applications today which do energy harvesting and they just get energy from ambient sources and they are not always connected to any power source. So in any of these cases, you want the software stored. So the main usage or the first usage, I would say, is to store your software. But then, in addition, just think about sensors. So you have some IoT device or medical device. It is logging maybe the temperature, maybe your heart a bit, maybe some ambient data from some sensors.

8:04Ilan Sever: And you want to have a logging of this data. So think about the sensor, it's logging what happened, and maybe after a while it is transmitting the information to some system, whether it's an industrial sensor, medical sensor, any type of these devices. So they always need, in addition to the code storage that we discussed before, also some data logging storage. Moreover, most of these systems, these mixed signal embedded systems, they have also some analog parts. And for the analog parts, usually you would need to have some kind of trimming. So these are a kind of a normally one-time programmed data that you do upon production to just put all the analog values in place.

8:59Ilan Sever: So you use streaming. That's another usage for non-volatile memory. So you just want to kind of burn this data into the chip so it returns throughout the lifetime of the chip. And last but not least, on security applications, there is always storage of some secret key. So encryption keys are normally stored on some kind of non-volatile memory on security applications. Awesome. Yeah, that's a great introduction because I think what most people don't realize is, take the example of the analog part you mentioned. My own background is in analog semiconductors. So it's like, it's amazing that, you know, when you're making a billion of these little analog sensors or any analog power supply unit or a power distribution chip or whatever it is, you know, as you manufacture a billion of them, right, what you're saying is like not all of them are going to come out the same.

10:02No way, because there is process variation. And if you say that this thing has to output like one volt, it's going to output 1.02. The next chip will output 0.99. You know, this is not usable because let's say you want to power a GPU with this power controller chip. It can't be putting out these random variables of voltages. And so the trimming aspect is just an electronic knob that is inside the chip that when you can write in something like a code, like, hey, adjust the voltage by 0.02 volts down. And you can write, you know, code that in, you know, one time fashion and then center everything.

10:43Like the alternative in the digital world is you have to kind of keep binning chips. Like Intel will take, oh, these are the fastest chips. I'll sell them as I9. These are the slowest chips. I'll sell them as I5, you know. But in the analog world, they don't do that. They just trim and calibrate things so that they all work the same. So this is like a very unspoken part of the analog world, which is extremely important.

11:06Ilan Sever: Yes, this is correct. And this is, again, one of the use cases. In this case, we are talking about a very small amount of data that needs to be retained throughout the lifetime. And it also is programmed only once or maybe very few times. So when we discuss non-volatile memory, it's important to state one very important term, which is what we call endurance or programming cycles. So, for example, if you program a software, then yes, you would need to change it, right? the software versions, people do even what is called FOTA firmware update over the air today, so your system can update code even in the field or over the air.

11:59Ilan Sever: So all this requires reprogramming of the data, unlike this streaming data or what we just mentioned, it is more like production data that you stored once. In any case, any type of non-volatile memory is able to reprogram data. Not as many times as you can write to SRAM or DRAM, which are the volatile technologies that you mentioned. Obviously, you can read and write to them almost infinitely. Exactly. Okay, this is great because you're setting this non-volatile memory to be a kind of memory that you mostly write one time or a few times and read many, many times in its lifetime? Yes. So any type of non-volatile memory will need to be reprogrammed.

12:52Ilan Sever: And one of the parameters that we look at when we look at NVM technology is the number of cycles, the endurance of this memory. So some technologies can only work up to 10K, 10 ,000 reprogramming cycles. Advanced and non-volatile memory is expected to already allow in the order of 100K, 100 ,000 to a million reprogramming cycles. And this means it's a very good technology that allows a wide usage for many types of applications. Awesome. That's helpful to know because we will obviously talk about endurance and reprogrammability when we actually talk about what resistive RAM is. One other important point that you mentioned I think we should touch on is the capacity of this thing.

13:52When you talk about, you mentioned NAND in the beginning, you can store terabytes on NAND flash. And in DRAM, you can store gigabytes. In SRAM, you can store hundreds of megabytes. So what is the range of non-volatile memory in terms of storage capacity?

14:08Ilan Sever: The capacity of the non-volatile memory depends on the application, obviously. So we mentioned embedded MCUs having some firmware. Well, this is normally counted in kilobytes, but I would say tens, hundreds of kilobytes to single megabytes. So maybe one, two or four megabytes is a large NVM capacity for embedded MCU, maybe four megabytes. So we're talking about single-digit megabits, right? Like 1, 8, maybe 16 megabits, 32 megabits for code storage. Of course, all the other use cases like data logging or trimming that I mentioned are much smaller. We're talking about kilobytes. Now, in more advanced MCUs, so maybe some in lower geometries where people embed a non-volatile memory with high-performance microprocessors for any type of applications, automotive, industrial, it can reach to, I would say, ranges of 16, 32 megabytes.

15:38Ilan Sever: But we are definitely still not in the gigabit or gigabyte terrain that is implemented in other type of technologies like the ones you mentioned, DRAM or NAND flash. Yeah, so that's also very important to understand about these non-volatile memories because you want to essentially, let's say, reprogram them over the air. What you're actually reprogramming is only a few megabits bytes or a few kilobits kilobytes. And when you drive your Tesla into your driveway and it wirelessly connects and updates its firmware, this is where it is actually stored. It is stored in a non-volatile memory, probably on the larger capacity side than you would have in a little sensor.

16:32I would assume an automotive NVMe, non-volatile memory, NVM, with like embedded flash or whatever, is like a larger capacity than a sensor, which would for the trimming applications, it's going to be really small because you only need to correct for like, you know, put in a code, that's it. So it has to store very little amount of memory compared to what, you know, an automotive application would use, but it's definitely not in the gigabits, gigabytes range and all that, right? So that's the whole thing here. So typically we've used eFlash for doing this and now it seems like eFlash has hit some kind of a limitation as we go to smaller nodes.

17:21What exactly is eFlash and why does it not scale to lower technology nodes, say below 22 nanometers?

17:31Ilan Sever: That's a good question. So embellished flash, basically flash memory, is storing some charge in an insulated floating gate. So it's like a transistor in which the gate has some charge stored or a floating gate, and it changes the conductance or the threshold of the transistor. That's the way the data is stored. So you can have charge stored on that floating gate or taken away, and it changes the behavior of the transistor. Now, the amount of charge that you store there, when the technology scales to low geometries like 28 nanometer, 22, and I'm not even talking about single-digit nanometer technologies that are available today, the dimensions of this transistor and the dimension of this so-called floating gate are so tiny, and the amount of charge that is stored there is just moving physically to almost single electrons.

18:49Ilan Sever: You know, a very small amount of charge, and this is just a physical limit. So, and of course, holding this charge over there without any leakage, without the charge going away by all kinds of physical mechanisms is becoming really impossible in the smallest geometries. And that's why flesh cannot scale to these smaller geometries. Okay, that's very helpful. Actually, I wanted to compare this to what, like, for example, DRAM looks like. You know, a modern DRAM actually uses the equivalent of, let's say, a 10 nanometer transistor. But the charge that is stored is never stored within the transistor itself because there is a capacitor on top of the DRAM that actually stores the charge.

19:43And the whole problem of DRAM and capacity and DRAM density is how to get as much capacity by digging a deep trench in the silicon and connecting a transistor to it and how to maximize that capacitance without having to rely on the transistor to hold that charge. But what you're saying is like in the flash world, the transistor has to hold the charge. And then you make the transistor so small that you can hold basically, you know, a few electrons of charge in it and that's about it because it's so small. it physically stops scaling. You need to hold more charge than that for which you need larger transistors, period.

20:27And that's why flash does not scale beyond 22 nanometers. So there's no flash memory in FinFET transistors or below.

20:36Ilan Sever: Yeah, this is a very good point because you mentioned all kinds of vertical capacitors and trenching to the silicon editor down in discrete DRAM chips. When we are talking about the embedded world, it's very important to note that the whole idea of embedding a system on chip with memories and with analog is that you would like to keep a plain CMOS technology that allows to integrate on the same chip with the same basic technology features. You would like to have analog components, you would like digital components, you would like to have SRAM because there will always be SRAM, and you would like to have an NVM, but you will never invest a special trench capacitor or you will never invest a lot of special technology because it will make the whole system on chip too expensive.

21:47Ilan Sever: So another key parameter that we look at when selecting a non-volatile technology, I mentioned before endurance and the performance of the memory, is how much does it interfere? How much does it add on top of the baseline CMOS technology? At the end of the day, semiconductors are very cost sensitive. So it doesn't seem like that, but just imagine how much is the selling price for such an embedded MCU. If one would need to add too many processing layers, which eventually translate to money and to time of manufacturing the silicon wafer, that will make the whole system on chip too expensive. Imagine there is a large system on chip that has everything I mentioned, digital analog, and it has one NVM component, one NVM code storage.

22:51If you add more layers of processing, special structures, you pay this additional cost over the whole area of the chip, which is making the whole system on chip more

23:06Ilan Sever: expensive. So a key parameter in adding any technology is how many masks we count. Basically, in semiconductor processing, we count masks. So how many masks does the technology add on top of the plain CMOS, you know, plain vanilla technology? And that's another key element because in the end of the day, this means how much are you paying premium for having a system on chip with embedded NVM? So when you mentioned, for example, an NAND flash, that's a totally different technology with 3D integration and many levels. And when you mentioned, for example, discrete DRAM with a trench capacitor, these are expensive technologies, but they are optimized for a single use case, which is an NAND flash chip or a DRAM chip.

24:08Ilan Sever: In embedded, you need to have a plain vanilla technology with the minimum additional layers to support all the type of memories that you need. Yes, okay, it's very important. Because you're saying that, look, the cost of these microcontroller chips that require these non-volatile memories is already very low. Now, if you want to add like a whole lot of masks into the semiconductor process, just because you have to implement this non-volatile technology, it better be very inexpensive because otherwise you can't have the whole bill of materials for the chip go up just because you want to add NVM materials inside.

24:52So non-volatile memories should come with as few masks as possible. So with that being said, how many masks does a typical NVM embedded flash process add?

25:05Ilan Sever: Yes, so important to mention, So embedded flash adds another, I would say, polysilicon layer, a floating gate layer on top of the transistor. In some cases, there is a split gate technologies, all kinds of flavors of that. But they add a lot of processing, and this processing is done in what we call the front end of life. So in the transistor, very close to the silicon substrate where you actually implement your transistor. and for making that we are talking about in the range of 10 additional masks maybe 8 to 10 additional masks just to process these additional features required for embedded flash.

25:53Okay that's what percentage of the total mask count would you think that is a typical CMOS process has would you say like 70 80 masks uh even less i mean typical cmos will have even less

26:08Ilan Sever: masks and so yeah this can add 25 30 percent add-on and it can become very significant in the cost that's a problem that's that's what we are actually trying to solve here and when you're trying to go to smaller transistor nodes anyway you can't store enough charge and you can't add so many layers. If you have to add 30 % more layers, that's not a cost-optimal feature. So I think this is a good time to get into... We've set the stage exactly as to what is non-volatile memory, why is it used, where is it used, what are its features, and what is required from a non-volatile memory in terms of cost, simplicity of implementation, capacity, and everything.

26:54So I think we have set the foundation of non-volatile memory and where it lies. I think the next interesting step is to go into what VBitNano actually does, which is resistive RAM. This is a nice time to get into what that is and how it solves many of these problems that we just talked about.

27:12Ilan Sever: So indeed, resistive RAM is a technology that is aiming at replacing embedded flash. It has several key benefits related to our previous discussion. First of all, it is very low cost. It is adding just two additional masks to the technology. It is embedded only in what we call the back end of line. So we actually build the structures between the metal layers way above the silicon substrate and transistors. Now, why is this important? We mentioned before all kinds of mixed signal chips, analog chips that require some non-volatile memory. These technologies have passed through a lot of optimizations of their unique analog characteristics.

28:15Ilan Sever: For example, some technologies have BCD transistors, which are high voltage transistors. And when you invested so much in analog technology to have the perfect analog properties for power management and other type of applications, If you had to now embed what we call a front-end of line technology, a technology that sits at the transistor level, it would interfere with the other analog transistor that you spend years optimizing. So another key importance of technology that you would like to add on top of an existing, let's say, analog or mixed signal platform is that putting it in the back end of line means it is totally decoupled from the transistors.

29:11Ilan Sever: so you are not impacting the transistor behavior and you are not impacting any analog characteristics because the memory processing is done actually after way after you finished processing all your CMOS technology it is actually done in the top layers top routing layers meta layers above of the silicon. One second. I just wanted to make, that is a very, that's a very interesting point that you mentioned here. That's because I think people need to understand where resistive RAM sits inside the stack of a silicon chip. What you were saying is that back end of line means that it is sitting like very way on top of the chip where if you think the transistors are way below, the substrate is way below.

29:59This is all the way on the top. So it's actually processed almost very much at the end of the chip processing. And so it's very decoupled from what is happening in the transistor world downstairs. And so you also mentioned BCD technology. So for those who have not heard of this, it stands for BiCMOS, CMOS, and DMOS. And this is a specific technology that is good for high-voltage transistors. It's used a lot in automotive applications because it can withstand a lot of voltage, like tens of volts. So these transistors are unique to what they do. Like they are used in like power conversion circuits and things like that.

30:37You don't want to go and put a storage and non-volatile memory storage technology that messes with the transistor structure. So that would make the whole BCD transistor, which is so well optimized for power performance or like whatever that is supposed to do at high voltage performance, is going to mess up because the non-volatile memory is interfering with that. So the best place to put it is really far away and process it really after all the silicon is done at the back end of line right on top of the chip. So that is what resistive RAM does with just one or two added masks, which makes it very inexpensive.

31:18Ilan Sever: That's right on. So what is resistive RAM? So basically, as opposed to flash that we said is storing charge, A resistive RAM, the type of resistive RAM that WiBit Nano is doing, which is called OxRAM, so oxygen vacancy-based resistive RAM, is actually implementing a resistive element, which you can change between two states, a low resistive state and a high resistive state, by applying voltage. So I will try to explain it with this demo that we have here. Let's see if it works. Yeah, if you're listening to this, this is a good time to switch to YouTube because Ilan has like a nice 3D model of the internal structure of a resistive RAM cell.

32:18And I'm just describing what I'm looking at here with changes between its low resistance and high resistance states.

32:23Ilan Sever: Resistive RAM is actually a resistor that can switch between two states, a high resistive state and a low resistive state. What we do, we take an insulating layer, like a capacitor that has a very high resistance, and by applying electrical voltage and current, we actually create these oxygen vacancies that are that you can see here that are actually forming this filament that is a conductive filament so with oxygen vacancies charge can go through and this is becoming conductive. Conductive means lower resistance so when the memory has this filament built the resistance is low and we are storing the value of one.

33:20Ilan Sever: Then by applying voltage in the opposite direction, what we can do is actually dissolve this filament. So in this side, in the high resistive state, we dissolve the filament. It goes back to an insulating layer that has a high resistance. So a current can not longer go through or the resistance is high. So we have these two states, Either the filament is created and we are in the low resistive state, or the filament is dissolved and we are in the high resistive state. So these two states, we then read them with some sense amplifier, which is a typical circuit that is used to read any type of memory, whether it's flash, DRAM, S-RAM.

34:11Ilan Sever: So we can actually sense whether the filament is there and then we read a 1 or the filament is dissolved and we read a 0. So that's basically the way resistive RAM is programmed by applying voltage that will create the filament or voltage in the opposite direction that will dissolve it and it is read by reading or sensing the resistance, whether it's a high resistance or a low resistance. Okay, this is fascinating. Usually, these are not the kind of devices that we see inside typical CMOS technology process. So, what I find fascinating about this is that clearly, you can't use any kind of a dielectric material that creates oxygen vacancies, right?

35:04There should be something that is different. Now, I know VBIT Nano would probably have its proprietary materials, but would you be able to broadly explain what is the property that causes these oxygen vacancies? What kind of materials do this, and how is it compatible with the CMOS process flow?

35:28Ilan Sever: Yeah, so we'll not dive into the whole physics of resistive RAM, But basically, I mentioned that we have an insulating layer, but on top of bottom of it, there are two electrodes. So there is a bottom electrode that is built from some kind of inert material. And there is a top electrode that is built from what we call a scavenging layer. So the scavenging layer is the layer that can actually kind of store oxygen or give it back. So according to the electrical field, this scavenging layer either will take away oxygen oxygen from the electric material or will give back oxygen to it. So by applying the electrical fields in opposite directions, we can either have oxygen vacancies inserted into the material or oxygen going away and creating vacancies or the opposite contribute back oxygen to dissolve the vacancies.

36:53Awesome okay that's unique like so this material is actually compatible with CMOS foundries?

37:03Ilan Sever: So maybe the most important or an overwhelming property of resistive RAM is that to generate it, we at Webit Nano use only fab-friendly material. So we use materials that are available in any CMOS technology. We don't use any rare earth material. We don't use any expensive, and we don't use any contaminating materials. So some technology that maybe we'll not discuss in this podcast like magnetic ram and ferroelectric ram, these are competing technologies that are also non-volatile but to actually manufacture them, you would need several rare contaminating and expensive materials that are not available in normal production lines.

38:09Ilan Sever: And in many cases, to just be able to process with these materials, you need totally separate rooms, separate chambers, separate machines to make sure you don't have any contamination of these materials. So in the resistive RAM here at Webit, we use only fab-friendly materials, very basic materials that you would know. Of course, I cannot tell you the secret sauce of the Webit technology in this podcast. For decades now, this technology was developed. So Webit is over a decade now. And even before that, our technology partner, CEA Letty in France, had developed these technologies for many years before.

39:04Ilan Sever: together with our partners we reach this technology that is as I said not using any contaminating materials and is performing with the best in class nvm performance and features yeah that's that's resistive ram itself is like not an idea that is like new right uh you mentioned Webit Nano has been doing this for 10 years. But why now? What has changed now about resistive RAM that we should, you know, people have been trying this since Panasonic have tried it. Samsung has tried it. What's the need now? What has changed? So I think it's a combination of many elements. One is what we mentioned before that, you know, flash is hitting the physical limit.

39:59Ilan Sever: and cost is you know we know that the cost pressure and semiconductor is always growing there is the moor law and there is a you know a lot of pressure to reduce cost moreover I think one of the driving application driving is a good word here is automotive. You mentioned it before. So we at Webit were able to demonstrate that this technology is not only a low cost and has a very good performance, but it can actually serve this very challenging market of automotive. So we all know that in our cars today, everything is electronic, you know, hundreds of chips, and many of them require a non-volatile.

40:59Ilan Sever: Today, resistive RAM technology can serve the automotive market, and I think it's a major breakthrough. So, it's nice. You mentioned that the competitors to this technology are MRAM, magnetoresistive RAM, and ferroelectric RAM, both of which are alternative materials and not really well suited to be integrated into a CMOS fab. So those technologies are ruled out. But then there's also, I think, another alternative technology called phase change memory, which alters its physical crystal structure with voltages. So, like, this is... Resistive RAM is another application where automotive is driving a lot of requirement here, especially as we go to smaller technology nodes where flash stops working.

41:55Resistive RAM is really well-suited to automotive. And so has this technology been qualified already for automotive? Because I know that there's a standard called the AEC-Q100, which is like a very hard automotive standard to pass. Does VBITnano already pass this standard?

42:13Ilan Sever: Yes. So indeed, our technology is now qualified for ACQ100 automotive. And we are continuing this with additional customers. So we recently announced two, I would say, leading IDMs that are both active in the automotive space that license our technologies for automotive platforms. So the way that this resistive RAM technology works from VBitNano is that you guys have the secret recipe that explains how resistive RAM can be made in a fab and a fab would license it from you. Is that how this whole thing works? Yes. But that's where when you asked me why resistive RAM is now becoming available. available, it's because it's not all about the secret sauce.

43:21Ilan Sever: So the secret sauce, for sure, it was developed throughout decades and we have now all the recipe for the exact dielectric structure and the exact electrodes that are needed to, you know, do the scavenging of the oxygen and all of that. and we really have tens of PhDs in Webbit working on this part along with our partners, as I mentioned. But that's not enough. If you are an embedded, I would say, MCU, let's say a system-on-chip architect, what you need is a full-blown memory module that you can just commission a read command, a write command, that's it. All the rest is done. You don't work with the bit cell.

44:18Ilan Sever: You don't work with physics. You need to write a 32 or 64-bit word onto the memory and be able to read it back when you need it. And that's where Wibit Nano is today. the only fully vertically integrated and fully independent IP provider. Because with Webit, we have all the pillars that are needed to build such a technology. So yes, you need the bit cell that I showed and the physics around it and the secret sauce. But around it, you need to build the design and the layout of the full memory array. You need to design and lay out all the peripheral circuits, like the decoders and the drivers and the sense amplifiers that I mentioned before, which are basically of analog nature, that are able to sense these exact resistances.

45:28Ilan Sever: and for programming the resistive RAM, we need to apply, as I mentioned, electrical field, which is actually voltages and currents that needs to be controlled very precisely. So for that, you need a whole analog design and layout team. And then on top of it, the programming sequence of resistive RAM is done using a proprietary smart algorithm. So not only that we did an analog capabilities, we also need a very strong algorithm team. We need a very strong digital design and verification team. So basically what I'm telling you is that the resistive RAM module that our customer actually embeds into their SOC is comprised not only of the physical bit cell, it has a lot of analog design, memory architecture, layout, digital design, algorithms.

46:39Ilan Sever: and even software is developed at Webit in order to have a full offering of embedded resistive RAM IP. So yeah, it's much more than just making the physical transistor. Like a user of resistive RAM would rather just get the whole black box with all the layouts inside, with all the sense amplifiers and all the voltage controls wired up, place it into their design, and then you have the software that controls that aspect of the algorithm. So it's all done for you approach. It's not like somebody has to go and place these physical structures in their layout and struggle with it. So all a user has to do is like license it, dump it in, go ahead and do the rest of your chip So everything is handled by Webit Nano for the customer using this IP.

47:40Ilan Sever: It sounds easy, but actually what is unique at Webit Nano is that all these teams are sitting together. So when there is a discussion of, let's say, a performance that needs to be met or automotive, let's say, meeting automotive qualification you mentioned before, You know, it requires meeting very high temperature profiles and high endurance. And in order to meet this, you cannot do it by just the bit cell. You cannot do it by just some analog design. You need a fully multidisciplinary approach that takes the best of the device physics and the process, the best of the analog design, the best of the digital and the algorithm, and wraps everything together into this product.

48:41Ilan Sever: And that's the main strength of Wibit Nano, and that's probably the only way that you can have any NVM technology be commercially viable. It was done before in flash memory. It is mostly done in other technologies. But for the resistive RAM today, we are doing it. And all these capabilities exist inside the team at Webit. So you mentioned endurance was one of the factors that you have to really design in as well. It's not as easy as it seems. What in the rough ranges is the endurance of resistive RAM? and how does it compare to let's say flash memory or any other alternatives if you have the numbers off the top of your head I'm trying to place is it more endurance or less endurance where does it fit I would say typically embedded flash is 10k cycles it depends of course there are some technologies that are more but I would say 10k cycles typically and for our resistive RAM we have some products that are 10k.

50:06Ilan Sever: We already demonstrated and qualified 100k cycles, which is opening the market for additional applications, automotive and others. and we are working on extending it beyond the 100k into the million cycles in the near future. Okay, awesome. So it's going to be quite performant in spite of the treacherous conditions that automotive applications want from, I don't know, from driving cars in Alaska to the Sahara Desert. You have to support all temperatures. And so it's usually a very challenging qualification to pass. And especially the lifetime of memory used in automotive also should be pretty high.

50:57So all of these things should fit broadly into that umbrella. Where do you see resistive RAM going next? So what's next? So, you know, we already spoke about microcontrollers. What's the next big thing?

51:08Ilan Sever: Yes, that's a very good question, Vic. so we all know that the next big thing or the existing big thing is AI so resistive RAM or I would say in the academic and naming is called memory stores it's kind of how the Academy wants to to name it had been studied in multiple academic researchers for what we call in-memory compute or IMC. Webit is also very active in this field, probably a good topic that we can discuss in one of the next podcasts. But basically the idea is that resistive RAM, a different type of resistive RAM array can actually create AI calculation inside the memory by just combining resistive elements.

52:26Ilan Sever: And this had been demonstrated in the academy, and commercializing it, I would say, is one of the next big things for Resistible. Amazing. That would be very interesting to hear. Analog in-memory compute has been around as a concept for a long time. And as we have like the AI era coming up and GPUs sucking like 1 ,000 to 2 ,000 watts per GPU, Maybe the future lies somewhere where we can do it differently. But that is a big topic and a topic for another day. All right, Ilan, before we wrap up this, I want to hear, like, what is the one story of innovation that you faced or came across while developing this technology within WeBoot Nano?

53:19That's a good story to tell for the whole audience.

53:23Ilan Sever: Yeah, I can think about such a story. You know, we mentioned analog trimming before, right? So embedded system on chip, mixed cellular chips will always have some analog. But I also mentioned that we have our own piece of analog within our memory. So obviously we need also to trim that part. So we came up with the idea, hey, we have non-volatile memory and we need to do trimming. So let's just take, you know, some part of the non-volatile memory, just some additional row, store our own data on trimming values there, read them, and we can just use it to trim our own system. and then when we went to our lead customers and we explained to them and they asked us how do you do this and we said yeah we have our own mechanism that we use our own non-volatile memory to trim our system they say what we want to use that as well so can you grant us access and we would like to trim our own system and it just saves us having additional NVM for trimming our system.

54:45Ilan Sever: And today it became a standard feature in all our modules in which we let the end customer get his own user data, his own trimming data, right out of the NVM. and this is done automatically and became a lead feature. That's amazing. So the key takeaway I'm getting from all of this is that it is important that you solve problems. It doesn't have to be the customer's problems. Even if you solve your own problems that you come up sometimes, you just have like a new product on your hands or a new problem you solve for someone else. And you can turn around and sell your own solution to your problem to solve someone else's problem, and it's like a perfectly viable business model.

55:39Ilan Sever: I guess that's what you call engineering, right? Yeah, that's amazing. It's a nice story. Awesome. Thanks, Ilan, for coming on SemiDoped. It's glad to have you here. I know we don't often talk about things like resistive RAM, but that's what SemiDoped is for, that we sometimes try to go outside of the normal narrative of AI, semiconductors, memory, optics. You know, we talk about all this stuff, But every once in a while, we like to throw a curveball and have someone like you explain what resistive RAM is to us. So thank you for coming on the podcast. Thank you for having me, Vik. All right. So that's the end of the podcast.

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