In early February LogicVision announced the release of its SiVision product whose core technology came through the acquisition of SiVerion in late 2004. SiVision is a yield analysis solution which offers the new SmartPE component-based analysis model and scripting capabilities that allow users to automate and standardize their analysis processes. SmartPE comes with a set of pre-defined data handling, statistical analysis, visualization and reporting components that can be used with SiVision's scripting capabilities. SiVision is available as a hosted solution or as an enterprise license. I had an opportunity to discuss this product with Jaffer Hussain, VP of Product Marketing for
the SiVision product line.
Tell me a little bit the company.
LogicVision is a provider of yield learning solutions. We basically build software applications that help semiconductor vendors improve their time-to-market and time-to-yield which means to be able to get out to customers quicker, time to yield which is build these parts in volume faster, reduce test costs and improve the quality of silicon. We're a public company. We went public a few years ago. We have been around since the early 90s. We have three product lines that enable this yield learning solution to add value to customers. The first product is our embedded test product, ETCreate. It is a BIST or built in self test offering. The ETCreate technology inserts these minitesters
or “eyes-in-the-die” as we call them into the silicon. The silicon is observable from the inside. The second product line is called ETAccess for easy access which links up with the testers to extract this information so that you can see inside the chip. The third product line is called SiVision. This basically looks at information, test and foundry information, across the range of manufacturing conditions, across the range of operating conditions, and across multiple dies, multiple wafers and multiple wafer lots to get the figures and to see how your product is performing in the bigger scheme of things and whether it is meeting the yield requirements. We have a pretty blue
chip list of customers including FreeScale, Intel, Agere, Matshusta, Microsystems, LSI Logic; a very large and diverse group of companies from the consumer, telecommunications, and just about any sector that does semiconductor design.
Editor: For calendar 2005 LogicVision had total revenue of $10.9 million, an increase of 7.8% from the $10.1 million in 2004. Net loss for year was nearly $10 million, compared to a net loss of $8.4 million in 2004.
A little bit of history on SiVision. SiVision came from an acquisition a little over a year ago of a company called SiVerion, Inc. which was located in Arizona. I was VP of Marketing for SiVerion. I came to LogicVision as part of that acquisition. I still run Marketing. The old SiVerion is now a business unit at LogicVision.
How long had SiVerion been in business?
Every one thinks the name is Siberian but it is SiVerion. That firm was incorporated three of four years ago around the 2002 timeframe. The founders of the company were running a consulting shop and then converted into a product practice with SiVerion. The technology goes back another five or six years to 1998.
How big a company was SiVerion at the time of the acquisition?
It was not a large company. It was a venture funded startup. It had roughly 10 people, primarily focusing on initial product development. It was in existence about two years when LogicVision acquired us.
How big is the SiVerion business unit now?
Pretty much the same size. As you can understand we have our whole extensive worldwide presence and support infrastructure from LogicVision. We have hired engineering people in the SiVerion unit. We do not need our own sales people. We use the breadth of the LogicVision channel.
Does LogicVision sell directly or through VARs or distributors? Is the sales model geographically dependent?
Exactly! It is geography dependent. It has its own sales in the US and a direct channel in Japan but the other regions around the world work through distributors.
Will you tell me about the SiVision product?
Let me come at it from the yield learning message. The reasons why LogicVision acquired us were to add more value and to address this yield learning need for the customer. I will explain what SiVision does in that context.
If you are a semiconductor vendor that is building silicon, the key requirement is to get the product to market on time, to be able to sample parts within the market window timeframe. The second requirement is to not only ship some parts but to do it cost effectively with the right yield so that you can actually make money from it. Obviously you are interested in what happens beyond that so you want quality to a strong component. You don't want to get the product out but have field returns which are extremely costly as you can imagine. What LogicVision does is the three product lines I have explained. Before the SiVision product came, LogicVision had the ETCreate technology that adds
these BIST structures inside the chip. The ETAccess technology then gets the information out. That information was specific to a few devices. You didn't know what was happening across the manufacturing conditions, across multiple wafers and across multiple lots. That's where SiVision comes in. We can take and analyze all of this information across the different manufacturing and operating conditions in order to know how the silicon is performing in the greater scheme of things. What we are doing in terms of integrating the product really is combining the depth and the detailed information that ETCreate and ETAccess products create for a particular piece of silicon with the breath of
analysis that SiVision brings. This combination of depth versus breath offers the level of capability that is unmatched by any other solution. As you know there is a wall between design and manufacturing which all of these DFM startups and even some of the larger companies are attempting to bridge because at 90nm and less it is becoming a much bigger issue to guarantee a certain yield when you are going through the design process. It is that wall that our combined products will help bridge from reliability and time-to-market and time-to-yield points of view. Let me focus on the SiVision product.
This is basically post silicon analysis. We take test and foundry data. The tests are performed on the silicon at different stages of post silicon cycle, at the wafer stage, and at the packaged part stage. What you are trying to see is how this silicon is performing. You take a number of measurements that are indicative of that. Our typical users are product engineers. During what is called the characterization phase which is right after the first silicon becomes available the product engineers try to understand how this part is behaving with reference to what the design spec were. They build these test parts across the range of the manufacturing conditions so the process corners
and they test them across the range of operating conditions. The operating conditions may be temperature or voltage, basically what the part is going to see in the real world. They capture a lot of data and then they try to make sense of that data in order to see how this part performing with respect to a particular process corner or to a particular operating condition. Then if there are any issues, how do I go and remove them to make sure that when I hit volume production, that I get the right yield and that this product works well in the marketplace? The second phase is when you go into volume production after you have done your ramp up. You have got to be watching these parts to be
able to quickly identify excursions in any parameters so that you can quickly fix them and get your yield back on track. The SiVision product takes all of the information, analyzes it, and helps users visualize it. What we have done which is very unique in this analyses phase is what we described in the press release, what we call SmartPE that stands for Product Engineering. So what this SmartPE does is add a totally new level of automation to the analysis procedure.
Are you familiar with RDC (Design Rule Checker) tools? Twenty to twenty-five years ago when you did DRC, you would plot out the chip and you would visually inspect whether all the rules were respected. Similar to that we built a system that automatically executes best practices for analysis techniques on the selected data and identifies problematic behavior. In addition a customer can take existing yield analysis procedures and use our product to automate them. What we have built is what we call a component based analysis model. It provides all of the atomic actions that the customer would use. It basically fetches a certain set of data and analyzes it a lot of different ways. It has
a lot of different analysis techniques and it help visualize by creating some specific plot or report. We have built these components which are pieces of software. The user is able to take these components, put them in a script and then automatically execute them. You are taking a work flow. You can automate a yield procedure with this component model.
So the product engineer is performing a Design of Experiment on the intended range of operational parameters and seeing how that relates to yield?
Right! That's the characterization phase. When they do these DOEs and build these test parts, they try to understand the behavior across all these ranges. The second thing that is done in volume production is that they still keep watching these parameters on every piece of silicon that is built to see if any problematic behavior occurs or a yield excursion that they can quickly fix. There is a characterization phase and a monitoring phase.
So the production phase would suggest to someone in manufacturing that the process is straying a bit?
That could be the issue but they are really looking at what the part is doing. So it could be the process or some other issue. But you are right. Most of the time the design doesn't change. It is the process that is straying. They look at the effect of that straying on the parameters. If in production there is something straying, they typically adjust the process.
If during characterization they find out that the behavior is not according to spec in a particular temperature range or in a particular voltage range, what does SiVision do beyond simply reporting that fact?
Spotting an excursion is the easy part. Helping them to figure out what caused that excursion is what the tool exists for. That's why we have for example correlation analysis. This enables one to correlate the parts that are failing for example where the limits that are being exceeded with the conditions that are causing it. To be able to identify that most of the parts that are failing are in this process corner. Correlate failures to an operating condition and then be able to help them analyze what is causing this problem and what they need to go and fix. Typically if the product engineers have an issue during characterization, they go to the design engineers and ask “Is
this the behavior you were expecting in silicon?” The design engineers look at it and say “No, it isn't. Here's what you should look out for.” It's a team effort to figure out what the cause of the problem is. What we give them is all of this data in one area, all correlated. You basically know for this part here in the test, the conditions used and for the same part later on where they did wafer acceptance testing or etest which is even earlier what were the parameters. They are able to correlate much earlier in the manufacturing cycle and determine what they should be looking out for to ensure that the part works properly in the end. And if it is not
working properly, it helps to find out what they should go and adjust. Should I go back to the fab and tell them to stay away from this process corner or adjust this process parameter because when this process parameter is in this range, we get the yields we expect. Basically in helping them we also come up with actionable information to make a fix.
Let me give you a specific example where a customer derived value from our software. One of our customers that was in production saw a major yield hit. Their yield suddenly went down to 50%. They couldn't figure out what the problem was. The foundry couldn't figure it out either. There was a lot of finger pointing as to whether it was a design issue or not. By simply doing a correlation analysis with respect to the equipment, they were able to see that most of the failing parts were going through one particular piece of equipment. It was clear then when they went through that equipment that things were unlikely to work. When they didn't go through that piece of equipment, things
worked out much better. It was clearly an equipment problem which the foundry accepted. That's a simple example but from a dollar standpoint it provided great value because they were able to get their yield back on track.
Is this the first release of SiVision by LogicVision?
This is the first release after the acquisition. We did have a release before the acquisition which was pretty much the first version of the product. We have focused over the last year on building the next generation component based automated analysis system. This is the first release of that system.
How many customers were there for the prior release?
We have a small group of customers. The ones we can talk about include a customer in Texas called Microtune who builds digital tuners. Another customer is Agere who is also a major LogicVision customer.
What is the pricing and packaging of SiVision?
The pricing of SiVision starts at about $70K on a per design basis. It's a TBL, one year license. If you have more than one design, we give you discounts on multiple designs.
Per design or per designer basis?
Per design! One of the points that I didn't make is that the key capability of the product is that it is a browser or web based system. When a set of product engineers are working on it, we want to enable them to work with their foundry, their test house and with their designers more efficiently. We have built it basically like a web tool. Anyone anywhere in the world who you would like to be on the system and to be able to see the behaviors that you are seeing can do so. We try not to limit ho0w many people use it. That's why we sell it on a per design basis, not on a user basis.
For a typical design, how many people might be using this tool?
Obviously it depends on the design. On a single design there might be 2 to 5 product engineers. A lot of times these product engineers are working on multiple designs. It could be a larger team but it is typically 2 or 3 PEs working on a design. It really depends upon what stage of the post silicon you are working on. If it is characterization, then there is intense activity for a few weeks or months. If it is production monitoring, there may be a single or a couple of PEs watching multiple designs. They are not actively doing stuff to it. They are just looking out for excursions.
How is the information presented to the users: text, tables, graphs?
The information that comes in is first cleansed. That's a big part because the data that comes in raw needs to be formatted. As I mentioned our data base takes all of this data and correlates to which means that you can cross reference this is the part this tracks from the very beginning, when it is part of a wafer to when it is packages. We cross correlate. Different views at different stages of test are available. We have a host of different plotting and mapping techniques. Product engineers use box plots quite a bit, histograms and some plots. All of these ways of analyzing data are there.
Automated analysis reports, Smart CE reports that I talked about are textual but one of the key tings we do is that it is a web based system. So for any report that we create for you, you can drill down to any level of detail. It is like a website. You can click on any parameter; it will take you down to the next level, all the way to the individual measurement. This navigation capability is extremely important when the PE is trying to figure out why something is going wrong. They want to get more detail or cross correlate something. It is very easy to do with this product. It is primarily because this was built after the web revolution took place. We have used a loot of web
technology. It is easy to use and easy to deploy.
Is there a sweet spot for this product: high frequency, analog,
? Is it equally applicable everywhere or is it better suited for certain applications?
It can add value for any design but obviously there is a sweet spot for it. When we segment the market, complexity of design is important. Complexity could be measured by gate count, frequency, pin count
The more complex the device is, the more complex its behavior and the more you need this level of automation. Then other thing we look at is the process node that the product is on. The more advanced processing at 90nm and 65 nm are going to see more issues. You will need automation to look at more data. Analog is part of that as well because analog process features see more variation in their behavior so this level of automation makes sense. Lastly we see that the more
dollars you have at risk when it is an expensive part or a very high volume part, where the yield is very costly, that's where we see customers really get interested. They want to accelerate their time to volume or their time to yield. The technology does exactly that. It can provide more tangible financial return.
Is there any competitor out there doing anything similar?
The general space that it fits into is yield data analysis. There are players in this space but for the most part what we see is that people are using generic technologies. A lot of product engineering groups still use Excel. There is another tool called SAS. They still use products like this because that is what they have been doing. There are third party technologies. PDF Solutions has a product called dataPOWER. There is a low end product called Examinator from a company called Galaxy Semiconductor Solutions. There are third party products but for the most part we see product groups using generic technology but this is very manual where someone sits in front of a screen, creates
a plot or histogram, then they eyeball the results and perhaps see something is wrong. A lot of times when we visit product engineers, they are carrying this very thick manual of plots that they are trying to analyze. The level of automation that we provide is not available to them. That's very unique to SiVision, i.e. the ability to create these scripts and automate the analysis procedures. Also the level of data mining we provide. Some products do have data mining but it is not built using this component model that gives you the ultimate level of flexibility. At the most basic level when you do manual analysis you can cut the data a lot of different ways but think of all the
permutations and combinations. You can have different test conditions, a host of parameters. If you want to look at everything, there are literally hundreds of thousands maybe millions of different permutations and combinations. If you do it manually, you can only hit so many of these. With a program like ours, it goes through every possible combination and spots issues for example with respect to homogeneity of distribution. It assumes if you plot a parameter against a set of conditions that your data is going to be homogeneous. But if it is clustered in one region and a bunch of outliers at the bother end, that's an issue. What are those outliers correlated with? These are the
kinds of things we can automatically catch with our program solution.
What are the possible future directions for this product technology?
The most exciting future direction would be the integration with other LogicVision technology which we are doing. We basically combine the breadth of information across multiple devices and wafer lots. SiVision gives the width while ETCreate and ETAccess products provide the detailed device level information. That for me was the reason for merging the two companies together. That is a very exciting because that gives the customers the ability to take failure information into these devices and be able to say I have this particular memory that is failing in this process corner. Basically it will give very actionable information within the chip on where to go and what to change in order
to improve yield. That's the most exciting direction that I see with SiVision and the other two LogicVision products. Obviously there is a need to keep improving our component model, add more components to the model, more capabilities to provide automation.
Does the more to 65 nm have any ramifications for your product?
Very good question. The need for a product like this is driven by the move that you mentioned for two reasons. We have seen analysts report that suggest the causes of yield failures are increasingly performance failure not as much particle defects. Theses are exactly the failures that we target with SiVision product going toward 90 nm and then onto 65 nm and 45 nm. The need to do this detailed analysis where you have more pins on devices, more variables in the process itself. You just absolutely have to capture more data and analyze it in order to be able to spot the behavior and to prevent them from happening in volume production. This level of automation with this increased amount
of data is even more important.
My question was more whether the product and its underlying technology would need some quantum leap in order to analyze designs at these advanced process nodes?
The product doesn't break. But the kinds of automation techniques, the kind of data mining, and the rules you write may change. There are more rules you want to look at. There could be foundry specific rules and IP specific rules to look at. One of the strengths of the product is that it can take all of these rules and represent these rules and procedures automatically. We have given customers the ability to evolve over time by building this level of automation which these advanced process nodes may require.
BlackBerry is Saved
Research in Motion Ltd. (RIM) agreed to pay $612.5 million to settle all claims. In return, RIM gets a perpetual license to NTP's technology. The license covers all of RIM's products, services and technologies; and permits the company and it partners to sell products and services free of any claims by NTP. RIM had already set aside $450 million for a possible settlement. Jim Balsillie, RIM chairman and co-Chief Executive Officer, said “The absolute motivation was really to give clarity and certainty to all our ecosystems so we can really start our new year, which starts Monday ... with no more of the noise and distraction of this suit". He also said “There’s no
question we took one for the team here.”
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