Cadence has a new white paper out on Computational Software . I've written on these topics in Breakfast Bytes, most recently in the posts: Computational Software System Analysis: Computational...

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We have talked about aspects of the in-design symbol edit application mode in the past. This is the environment specific to the Allegro® Package Designer Plus layout tools allowing you to work...

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In last week's post, 1G Mobile: AMPS, TOPS, C-450, Radiocom 2000, and All Those Japanese Ones . I covered 1G mobile, the first analog standards. Then we went digital. 2G The Nordic countries...

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Do you have a set of Bluetooth earbuds yet? If not, you will. The iPhone was the first to kill the ubiquitous 3.5mm headphone jack, but many other manufacturers have quietly followed. Of course,...

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If I talk about my life, it was much simpler when I used to live with my parents. They took good care of whatever I wanted - in fact, they still do. But now, I am living alone, and sometimes I buy...

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Complexity is driving the urgency for advanced artificial intelligence systems more than ever—and that means someone has to supply the tools to create those systems. Cadence is up to the task: we’ve been expanding our AI offerings. If you haven’t already seen what Cadence can do for your AI needs, or if you’re not quite up-to-date on this whole AI boom, let this presentation given by K.T. Moore at the Cadence Theater at DAC bring you up to speed.

The technology behind AI isn’t as new as you’d think—the principles that govern how AI learns have been in development since 1959, when Arthur Samuel defined the concept of “machine learning.” At the time, there was nothing even resembling the necessary compute power to put Samuel’s concepts into practice—but now we can. AI designs are huge, and they’re massively parallel—simulating them on older computers and simulators would have taken ages; never mind how long it would take to do some by-hand measure like they had to do in the '60s.

But with advancements in server technology and the parallelization technology in products like Xcelium Parallel Logic Simulator and JasperGold smart technology, plus hardware-based engines like the Palladium and Protium platforms, verifying AI designs is not only possible—it’s easy.  But, read on, its not just about simulation technology.

AI tech is flooding the industry. It’s applicable to almost every vertical—cloud computing can use AI to intelligently manage a user’s required resources, consumer electronics are using it to tailor a user experience based on a whole host of collected data, automotive companies want to use AI to drive cars, healthcare to assist in diagnoses given a set of symptoms and a database of other, similar patients—and that’s saying nothing of the multitude of industrial applications. AI is also useful in the creation of developers’ tools themselves. Part of what’s causing the semiconductor industry boom is just this—an exploding interest in AI chips. And with 5G technology imminent, and with the looming billion-gate plus sizes of the SoCs that implement 5G, AI-assisted developers' tools might need to become the norm, not an outlier.

So: in all of this, where is Cadence?

Cadence is focusing its efforts on two areas, dubbed “machine learning inside” and “machine learning outside.” ML inside in the digital design flow refers to improving PPA, faster engines, and better testing and diagnostics. None of this physically affects how you use a tool, but it makes using that tool a much better experience. ML outside talks about the design flow in general, working toward an automated design flow, as well as productivity improvements across the flow. These things do change how you use a tool, but don’t worry, it’s all for the better.

Additionally, Cadence is working to improve design enablement; that is, hardware and software co-design. Smart Genus and Innovus solutions make designing your SoC easier than ever—using the full flow can result in up to a 21% PPA gain.

If you’re looking specifically for IP to enable AI on your SoC, the Tensilica DNA 100 processor has you covered, too. It’s great for companies designing edge or AI chips, offers great compression rates and efficient power usage, and has 4.7X the performance of other AI SoC IP on similar array sizes.

Cadence has you covered no matter where you’re going in this new world of AI systems—with our AI-enabled tools, IP,  and our strong partner ecosystem, you can be at ease knowing you’ll be supported no matter how complex your needs are.

Everyone keeps talking about “the cloud” this and “the cloud” that these days—but you’re a semiconductor designer. Everyone keeps saying “the cloud” is revolutionizing all aspects of electronics design—but what does it mean for you? Cadence's own Tom Hackett discussed this in a presentation at the Cadence Theater during DAC 2019.

What people refer to as “the cloud” is commonly divided into three categories: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and software as a Service (SaaS). With IaaS, you bring your own software—i.e. loading your owned or appropriately licensed tools onto cloud hardware that you rent by the minute. This service is available from providers like Google Cloud Platform, Amazon Web Service, and Microsoft Azure. In PaaS (also available from the major cloud providers), you create your own offering using capabilities and a software design environment provided by the cloud vendor that makes subsequent scaling and distribution really easy because the service was “born in the cloud”.  Lastly, there’s SaaS, where the cloud is used to access and manage functionality and data without requiring users to set up or manage any of the underlying infrastructure used to provide it.  SaaS companies like Workday and Salesforce deliver their value in this manner.  The Cadence Cloud portfolio makes use of both IaaS and SaaS, depending on the customers’ interest.  Cadence doesn’t have PaaS offerings because our customers don’t create their own EDA software from building blocks that Cadence provides.

All of these designations are great, but you’re a semiconductor designer. Presumably you use Workday or some similar software, or have in the past when you were an intern, but what about all of your tools? Those aren’t on the cloud.

Wait—actually, they are.

Using EDA tools in the cloud allows you to address complexity and data explosion issues you would have to simply struggle through before. Since you don’t have to worry about having the compute-power on-site, you can use way more power than you could before. You may be wary about this new generation of cloud-based tools, but don’t worry: the old rules of cloud computing no longer apply. Cloud capacity is far larger than it used to be, and it’s more secure. Updates to scheduling software means that resource competition isn’t as big of a deal anymore. Clouds today have nearly unlimited capacity—they’re so large that you don’t ever need to worry about running out of space.

The vast increase in raw compute available to designers through the cloud makes something like automotive functional safety verification, previously an extremely long verification task, doable in a reasonable time frame. With the cloud, it’s easy to scale the amount of compute you’re using to fit your task—whether it’s an automotive functional safety-related design or a small one.

Nowadays, the Cadence Cloud Portfolio brings you the best and brightest in cloud technology. No matter what your use case is, the Cadence Cloud Portfolio has a solution that works for you. You can even access the Palladium Cloud, allowing you to try out the benefits of an accelerator without having to buy one.

Cloud computing is the future of EDA. See the future here.

Emulators are great. They vastly speed up verification to the point where it’s hard to imagine life without them; as designs grow in complexity, simple simulation can’t keep up for the biggest designs. The extra oomph from emulation is almost a necessity for the top percentages of design sizes. However, many users of Palladium aren’t efficiently using their unit’s processing power, and as a result they’re missing out on the full speed-up potential that Palladium can provide.

Altair’s HERO is here for you. With its help, your Palladium unit can be even more amazing for your productivity than before.

HERO (that’s Hardware Emulator Resource Optimizer) adds emulator support to Altair’s Accelerator. You already know and love Altair’s scheduling tools; so why not make them do more for you, so you can be one of those people who are making the most out of their Palladium system?

Emulators are kind of like big computers, but it’s a lot harder to manage leftover resources on an emulator than it is on, say, a CPU. A scheduler like HERO neatly sidesteps this problem by more intelligently using the resources available to ensure that there’s a minimal patchwork of leftover resources to begin with.

HERO supports past generations of Palladium as well, so if you’re still using an older version, you can still take advantage of the upgrades HERO provides. There’s a wide variety of features HERO has that make your emulator easier to use. HERO separates a job into a “select” section and a “run” section: the “select” part makes a last-minute decision on which domains or boards to use, while the “run” part is the actual job. This makes it easier to ensure that your Palladium emulator is being used as efficiently as possible. Jobs are placed using “shapes”, which are a set of job types; these can be selected from a list of pre-defined ones by the user. Shapes can have special constraints if those are needed.

A new reservation system also helps HERO organize Palladium’s processing power better. HERO offers both “hard” reservations and “soft” reservations. A hard reservation locks other users out of reserving any part of the emulator at all, while a soft reservation allows a user to reserve a part of the emulator for a later use. Think of it like this: a soft reservation is like grabbing a ticket from the deli counter, while a hard reservation stops you from ever entering the market.

When using HERO, you can manage your entire verification workload. You’ll find that your utilization of your emulator vastly increases—it’s been reported that some users using only 30% of the capabilities of their Palladium unit(s) saw a massive increase to over 90% once they made the switch to HERO.

If you’re ready to take your Palladium productivity to the next level, Altair has a HERO for you.

To see the full presentation given by Andrea Casotto in the Cadence Theater at DAC 2019, check here.

Autonomous vehicles are coming. In a statistic from the U.S. Department of Transportation, about 37,000 people died in car accidents in the United States in 2018. Having safe, fully automatic vehicles could drastically reduce that number—but the trick is figuring out how to make an autonomous vehicle safe. Internet-enabled systems in cars are more common than ever, and it’s unlikely that the use of them will slow or stop—and while they provide many conveniences to a driver, they also represent another attack surface that a potential criminal could use to disable a vehicle while driving.

So—what’s being done to combat this? Green Hills Software is on the case, and they explained the landscape of security in automotive systems in a presentation given by Max Hinson in the Cadence Theater at DAC 2019. They have software embedded [FS1] in most parts of a car, and all the major OEMs use their tech. The challenge they’ve taken on is far from a simple one—between the sheer complexity of modern automotive computer systems, safety requirements like the ISO 26262 standard, and the cost to develop and deploy software, they’ve got their work cut out for them. It’s the complexity of the systems that represents the biggest challenge, though. The autonomous cars of the future have dynamic behaviors, cognitive networks, require security certification to at least ASIL-D, require cyber security like you’d have on an important regular computer system to cover for the internet-enabled systems—and all of this comes with a caveat: under current verification abilities, it’s not possible to test every test case for the autonomous system. You’d be looking at trillions of test cases to reach full coverage—not even the strongest emulation units can cover that today.

With regular cars, you could do testing with crash-test dummies, and ramming the car into walls at high speeds in a lab and studying the results. Today, though, that won’t cut it. Testing like that doesn’t see if a car has side-channel vulnerabilities in its infotainment system, or if it can tell the difference between a stop sign and a yield sign. While driving might seem simple enough to those of us that have been doing it for a long time, to a computer, the sheer number of variables is astounding. A regular person can easily filter what’s important and what’s not, but a machine learning system would have to learn all of that from scratch. Green Hills Software posits that it would take nine billion miles of driving for a machine learning system of today’s caliber to reach an average driver’s level—and for an autonomous car, “average” isn’t good enough. It has to be perfect.

A certifier for autonomous vehicles has a herculean task, then. And if that doesn’t sound hard enough, consider this: in modern machine-vision systems, something called the “single pixel hack” can be exploited to mess them up. Let’s say you have a stop sign, and a system designed to recognize that object as a stop sign. Randomly, you change one pixel of the image to a different color, and then check to see if the system still recognizes the stop sign. To a human, who knows that a stop sign is octagonal, red, and has “STOP” written in white block letters, a stop sign that’s half blue and maybe bent a bit out of shape is still, obviously, a stop sign—plus, we can use context clues to ascertain that sign at an intersection where there’s a white line on the pavement in front of our vehicle probably means we should stop. We can do this because we can process the factors that identify a stop sign “softly”—it’s okay if it’s not quite right; we know what it’s supposed to be. Having a computer do the same is much more difficult. What if the stop sign has graffiti on it? Will the system still recognize it as a stop sign? How big of an aberration needs to be present before the system no longer acknowledges the mostly-red, mostly-octagonal object that might at one point have had “stop” written on it as a stop sign? To us, a stop sign is a stop sign, even with one pixel changed—but change it in the right spot, and the computer might disagree.

The National Institute of Security and Technology tracks vulnerabilities along those lines in all sorts of systems; by their database, a major vulnerability is found in Linux every three days. And despite all our efforts to promote security, this isn’t a battle we’re winning right now—the number of vulnerabilities is increasing all the time.

Check back next time to see the other side: what does Green Hills Software propose we do about these problems? Read part 2 now.

If you missed the first part of this series, you can find it here.

So: what does Green Hills Software propose we do?

The issue of “solving security” is, at its core, impossible—security can never be 100% assured. What we can do is make it as difficult as possible for security holes to develop. This can be done in a couple ways; one is to make small code in small packs executed by a “safing plan”—having each individual component be easier to verify goes a long way toward ensuring the security of the system. Don’t have sensors connect directly to objects—instead have them output to the safing plan first, which can establish control and ensure that nothing can be used incorrectly or in unintended ways. Make sure individual software components are sufficiently isolated to minimize the chances of a side-channel attack being viable.

What all of these practices mean, however, is that a system needs to be architected with security in mind from the very beginning. Managers need to emphasize and reward secure development right from the planning stages, or the comprehensive approach required to ensure that a system is as secure as it can be won’t come together. When something in someone else’s software breaks, pay attention—mistakes are costly, but only one person has to make it before others can learn from it and ensure it doesn’t happen again. Experts are experts for a reason—when an independent expert tells you something in your design is not secure, don’t brush them off because the fix is expensive. This is what Green Hills Software does, and it’s how they ensure that their software is secure.

Now, where does Cadence fit into all of this? Cadence has a number of certified secure offerings a user can take advantage of when planning their new designs. The Tensilica portfolio of IP is a great way to ensure basic components of your design are foolproof. As always, the Cadence Verification Suite is great for security verification in both simulation and emulation, and JasperGold platform’s formal apps are a part of that suite as well.

We are entering a new age of autonomous technology, and with that new age we have to update our security measures to match. It’s not good enough to “patch up” security at the end—security needs to beat the forefront of a verification engineer or hardware designer’s mind at all stages of development. For a lot of applications, quite literally, lives are at stake. It’s uncharted territory out there, but with Green Hills Software and Cadence’s tools and secure IP, we can ensure the safety of tomorrow.

In the former blog about Python and Specman: Specman: Python Is here!, we described the technical information around Specman-Python integration. Since Python provides so many easy to use existing libraries in various fields, it is very tempting to leverage these cool Python apps.

Coverage has always been the center of the verification methodology, however in the last few years it gets even more focus as people develop advanced utilities, usually using Machine Learning aids. Anyhow, any attempt to leverage your coverage usually starts with some analysis of the behavior and trends of some typical tests. Visualizing the data makes it easier to understand, analyze, and communicate. Fortunately, Python has many Visualization libraries.

In this blog, we show an example of how you can use the plotting Python library (matplotlib) to easily display coverage information during a run. In this blog, we use the Specman Coverage API to extract coverage data, and a Python module to display coverage grades interactively during a single run and the way to connect both.

Before we look at the example, if you have read the former blog about Specman and Python and were concerned about the fact that python3 is not supported, we are glad to update that in Specman 19.09, Python3 is now supported (in addition to Python2).

The Testcase
Let’s say I have a stable verification environment and I want to make it more efficient. For example: I want to check whether I can make the tests shorter while hardly harming the coverage. I am not sure exactly how to attack this task, so a good place to start is to visually analyze the behavior of the coverage on some typical test I chose. The first thing we need to do is to extract the coverage information of the interesting entities. This can be done using the old Coverage API. 

Coverage API
Coverage API is a simple interface to extract coverage information at a certain point. It is implemented through a predefined struct type named user_cover_struct. To use it, you need to do the following:

1. Define a child of user_cover_structusing like inheritance (my_cover_struct below).
2. Extend its relevant methods (in our example we extend only the end_group() method) and access the relevant members (you can read about the other available methods and members in cdnshelp).
3. Create an instance of the user_cover_structchild and call the predefined scan_cover() method whenever you want to query the data (even in every cycle). Calling this method will result in calling the methods you extended in step 2.  

 The code example below demonstrates these three steps. We chose to extend the end_group() method and we keep the group grade in some local variable. Note that we divide it by 100,000,000 to get a number between 0 to 1 since the grade in this API is an integer from 0 to 100,000,000. 

Pass the Data to a Python Module
After we have extracted the group grade, we need to pass the grade along with the cycle and the coverage group name (assuming there are a few) to a Python module. We will take a look at the Python module itself later. For now, we will first take a look at how to pass the information from the e code to Python. Note that in addition to passing the grade at certain points (addVal method), we need an initialization method (init_plot) with the number of cycles, so that the X axis can be drawn at the beginning, and end_plot() to mark interesting points on the plot at the end. But to begin with, let’s have empty methods on the Python side and make sure we can just call them from the e code.

 # plot_i.py
def init_plot(numCycles):
    print (numCycles)
def addVal(groupName,cycle,grade):
    print (groupName,cycle,grade)
def end_plot():
    print ("end_plot") 

And add the calls from e code:

 Before running this, note that you need to ensure that Specman finds the Python include and lib directories, and Python finds our Python module. To do this, you need to define a few environment variables: SPECMAN_PYTHON_INCLUDE_DIR, SPECMAN_PYTHON_LIB_DIR, and PYTHONPATH. 

 The Python Module to Draw the Plot
After we extracted the coverage information and ensured that we can pass it to a Python module, we need to display this data in the Python module. There are many code examples out there for drawing a graph with Python, especially with matplotlib. You can either accumulate the data and draw a graph at the end of the run or draw a graph interactively during the run itself- which is very useful especially for long runs.

Below is a code that draws the coverage grade of multiple groups interactively during the run and at the end of the run it prints circles around the maximum point and adds some text to it. I am new to Python so there might be better or simpler ways to do so, but it does the work. The cool thing is that there are so many examples to rely on that you can produce this kind of code very fast.

 In the example we used, we had two interesting entities: packet and state_machine, thus we had two equivalent coverage groups. When running our example connecting to the Python module, we get the following graph which is displayed interactively during the run.

When analyzing this specific example, we can see two things. First, packet gets to a high coverage quite fast and significant part of the run does not contribute to its coverage. On the other hand, something interesting happens relating to state_machine around cycle 700 which suddenly boosts its coverage. The next step would be to try to dump graphic information relating to other entities and see if something noticeable happens around cycle 700.

To run a complete example, you can download the files from: https://github.com/okirsh/Specman-Python/

Do you feel like analyzing the coverage behavior in your environment? We will be happy to hear about your outcomes and other usages of the Python interface.

Orit Kirshenberg
Specman team

We're happy to have guest blogger Thorsten Dworzak, Principal Consultant at Verilab GmbH, describe how he added Specman/e syntax to Sublime Text 3:

According to the 2018 StackOverflow Developer Survey, the popularity of development environments (IDEs, Text Editors) among software developers shows the following ranking:

1. Visual Studio Code 34.9%
2. Visual Studio 34.3%
3. Notepad++ 34.2%
4. Sublime Text 28.9%
5. Vim 25.8%
6. IntelliJ 24.9%
7. Android Studio 19.3%
8. (DVT) Eclipse 18.9%
9. …

15. Emacs 4.1%

Of these, only Vim, (DVT) Eclipse, and Emacs support editing in e-language (at least, last time I checked). Kate, which comes with KDE and also has a Specman mode, is not on this list.

I started using Sublime Text 3 some time ago. It offers packages that support a number of programming languages.

Though there is an e-language syntax available from Tsvi Mostovicz, it is unfinished work, and there are many syntactic constructs are missing. So, I created a fork of his project and finished it (it will eventually be merged back here).

It is a never-ending task because my code base for testing is limited and e is still undergoing development. The project is available through ST3's Package Control and you can contribute to it via Github.

I am eagerly waiting for your pull requests and/or comments and contributions!

Looking to learn? There's a bunch of new RAKs (Rapid Adoption Kits) available online now!

1) Indago 19.09 Better Driver Tracing and More

Are you new to Indago and not sure where to start? Luckily, there’s a new Rapid Adoption Kit for you: the Indago 19.09 Overview RAK! This neat package contains everything you need to get your debugging started through Indago. In four short labs, plus a brief introductory lab, you’ll have all the basics of Indago 19.09 down—the Indago working environment, the SmartLog, how Indago interacts with the rest of the Cadence Verification Suite, and how Indago uses HDL driver tracing.

Lab 1 discusses the various debugging tools included in Indago and teaches you how to customize your Indago windows and environment settings. Lab 2 covers the SmartLog feature and talks about analyzing and filtering its messages to suit your needs, as well as how to interact with the waveform marker. Lab 3 is an interactive Indago debugging experience—it’ll walk you through how to use Indago and its features in an actual working environment: setting breakpoints, using simulator commands in the Indago console, toolbars, switches, and more. Lab 4 is all things HDL tracing—recording debug data, an introduction to debug assertions, waveform visualizations, driving expression analysis, and single-step driver tracing, among other things.

Interested? Check out the RAK here.

2) IXCOM MSIE: Faster Palladium Build Time

Got several testbenches you want to compile with the same DUT and tests and you want to do it fast? With IXCOM, all you have to do to compile those different testbenches is use the xrun command for each after compiling your DUT. But what exactly is IXCOM, and how does one start using it? This quick RAK can help—here, you’ll learn the basics of using MSIE features with IXCOM, complete with an example to get you started. Using MSIE can vastly improve your build times with Palladium and using IXCOM is the best way to shrink that tedious rebuild time as small as it can get. Check out this RAK here.

3)  JasperGold Control and Status Register Verification App Automates UVM Register Map Verification

New to the JasperGold Control and Status Register (CSR) Verification App for your UVM testbenches? Don’t worry; there’s a RAK for that! This eponymous RAK can get you up and running with this in no time, helping you automate your checks from UVM register map specs. With this RAK, you’ll learn the basics of the JasperGold CSR, how to use JasperGold CSR’s Proof Accelerator, and more. CSR features a model-based approach to predicting a register’s expected value, supports pipeline interfaces, all IP-XACT access policies, and it can fully model any expected register value. It also supports register aliases, read and write semantics, and separate read/write data latencies in any given field.

If this functionality sounds up your alley, you can take a look at this RAK here.

Curious about what’s going on behind the scenes with verification? Bernard Murphy, Jim Hogan, and our own Paul Cunningham are on the case with the “Innovation in Verification” blog stream over at semiwiki.com. Every month, this trio reviews a newly-published paper in academia that pertains to verification and discusses its implications. Be sure to stop by—it’s a great place to see what might be coming down the pipeline someday.

This month, they discuss the implications of metamorphic testing. The purpose of metamorphic testing is to define a verification approach where is there is no “golden reference.” This situation comes up a lot now as designs grow in complexity, and it begs the question: “how does one know the design is verified if there is no standard to compare to?”. Metamorphic testing addresses the problem of not having a “gold standard” to compare to by comparing the results of related tests instead. The paper reviewed by this team used metamorphic testing to study methods of managing JavaScript tags.

Paul saw this as a valuable new class of coverage. Metamorphic testing represents a way to create better distribution analyses through understanding the relationships among tests. This can reveal critical-but-complex issues that traditional verification methods may overlook. He saw this as an emerging class of coverage that new verification tools could be built around. Paul asserted that a future metamorphic-testing-based tool’s main contribution to the field of verification would be to better analyze noisy performance results where the noise is multi-modal. It could be useful in detecting race conditions and similar hard-to-debug anomalies. Paul also sees metamorphic testing as ripe for ML techniques. Overall—Paul sees a bright future for metamorphic testing in verification.

Jim is reminded of Solido and Spice—these metamorphic testing capabilities are “more than just a feature”—they might be a product. Maybe even a whole new class of verification tools, as Paul said.

Bernard says that this topic is “too rich to address in one blog”, so be sure to head over to the post to see more of what the future has in store for verification.

Our customers’ tests have become more complex, longer, and consume more resources than before. This increases the need to optimize the regression while not compromising on coverage.

Some advanced customers of Specman use Machine Learning based solutions to optimize the regressions while some use simpler solutions. Based on a request of an advanced customer, we added a new Coverage API in Specman 19.09 called Coverage Callback. In 20.03, we have further enhanced this API by adding more options. Now there are two Coverage APIs that provide coverage information during the run (the old scan_cover API and this new Callback API). This blog presents these two APIs and compares between them while focusing on the newer one.

Before we get into the specifics of each API, let’s discuss what is common between these APIs and why we need them. Typically, people observe the coverage model after the test ends, and get to know the overall contribution of the test to the coverage. With these two APIs, you can observe the coverage model during the test, and hence, get more insight into the test progress.

Are you wondering about what you can do with this information? Let’s look at some examples.

1. Recognize cases when the test continues to run long after it already reached its coverage goal.
2. View the performance of the coverage curve. If a test is “stuck” at the same grade for a long time, this might indicate that the test is not very good and is just a waste of resource.

These analyses can be performed in the test itself, and then a test can decide to either stop the run, or change something in it configuration, or – post run. You can also present them visually for some analysis, as shown in the blog: Analyze Your Coverage with Python.

scan_cover API (or “Scanning the Coverage Model”)

With this API you can get the current status for any cover group or item you are interested in at any point in time during the test (by calling scan_cover()). It is very simple to use; however it has performance penalty. For getting the coverage grade of any cover group during the test, you should
1. Trigger the scan_cover at any time when you want the coverage model to be scanned.
2. Implement the scan_cover related methods, such as start_item() and end_bucket(). In these methods, you can query the current grade of group/item/bucket.
The blog mentioned earlier: Analyze Your Coverage with Python describes the details and provides an example.

Callback API

The Callback API enables you to get a callback for a desired cover group(s), whenever it is sampled. This API also provides various query methods for getting coverage related information such as what the current sampled value is. So, in essence, it is similar to scan_cover API, but as the phrase says: “same same but different”:

1. Callback API has almost no performance penalty while scan_cover API does.
2. Callback API contains a richer set of query methods that provide a lot of information about the current sampled value (vs just the grade with scan_cover).
3. Using scan_cover API, you decide when you want to query the coverage information (you call scan_cover), while with the Callback API you query the coverage information when the coverage is sampled (from do_callback). So, scan_cover gives you more flexibility, but you do need to find the right timing for this call.

There is no absolute advantage of either of these APIs, this only depends on what you want to do.  

Callback API details

The Callback API is based on a predefined struct called: cover_sampling_callback. In order to use this API, you need to:

1. Define a struct inheriting cover_sampling_callback (cover_cb_save_data below)
   1. Extend the predefined do_callback() method. This method is a hook being called whenever any of the cover groups that are registered to the cover_sampling_callback instance is being sampled.
   2. From do_callback() you can access coverage data by using queries such as: is_currently_per_type(), get_current_group_grade() and get_current_cover_group() (as in the example below) and many more such as: get_relevant_group_layers() and get_simple_cross_sampled_bucket_name().
2. Register the desired cover group(s) to this struct instance using the register() method.

Take a look at the following code:

// Define a coverage callback.
// Its behavior – print to screen the current grade.
struct cover_cb_save_data like cover_sampling_callback {
    do_callback() is only {
       // In this example, we care only about the per_type grade, and not per_instance
       if is_currently_per_type() {           
            var cur_grade : real = get_current_group_grade();
            sys.save_data (get_current_cover_group().get_name(), cur_grade);
        };//if
    };//do_callback()
};// cover_cb_send_data


extend sys {
    !cb : cover_cb_save_data;

   // Instantiate the coverage callback, and register to it two of my coverage groups
    run() is also {
       cb  = new  with {
        var gr1:=rf_manager.get_struct_by_name("packet").get_cover_group("packet_cover");
        .register(gr1);
        var gr2:=rf_manager.get_struct_by_name("sys").get_cover_group("mem_cover");
       .register(gr2);
       };//new  
    };//run()

  save_data(group_name : string, group_grade : real) is {
        //here you either print the values to the screen, update a graph you show or save to a db 
  };// save_data
};//sys

In the blog Analyze Your Coverage with Python mentioned above, we show an example of how you can use the scan_cover API to extract coverage information during the run, and then use the Specman-Python API to display the coverage interactively during the run (using plotting Python library - matplotlib). If you find this usage interesting and you want to use the same example, by the Callback API instead of the scan_cover API, you can download the full example from GIT from here: https://github.com/efratcdn/cover_callback.

Specman Team

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Hello, i saw that MAESTRO is a plotting addon is it a part of ADE EXPLORER?

i cant see the relation between the two.i started to read manual and regarding MAESTRO i only see code.

is there some simple examples?
Thanks.

Hello, i have a realy mistick thing going with copying libraries in cadence virtuoso,

When i copy straight forwart the whole library it gives me a warning that accsess was denied,but when i go into the library and copy it as a single file, then it goes fine.

another problem is it doesnt show in the massage console  ALL the files which could not be copied.(which is the much bigger problem,becuase i would have to pass threw all the subdirectories to verify if all files are there)

Is there a way to see which files wasnt able to be copied?

Thanks. 

Hi,
I am new to the circuit design and troubleshooting. My project is to design a trans-impedance amplifier using Cadence that can amplify a signal coming from a photodiode. I started out with the regulated cascode configuration as shown in the circuit below. I look at the frequency response using AC simulation and it looks like a high pass (/net 5). The results doesn ot show any gain (transient response), or expected low-pass roll-off in the AC response.

First thing, I looked into the operating regions of the MOSFETs and adjusted the input dc voltage of the Vsin to 0.5 to make sure that the T0, T1 mosfets are in saturation(checked this with the print->dc operating points). Beyond this point, I am not sure on how to proceed and interpret the results to make changes. Any help would be greatly appreciated.

Thanks,

-Rakesh.

Hello , i am trying to extract netlist from a circuit  in assembler

I have found the manual shown bellow , however there is no such option in tools in assembler.

how do i view the NETLIST of this circuit?

Thanks.

ASSEMBLER VIEW menu

Virtuoso Version -- IC6.1.7-64b.500.23

Cadence Spectre Version -- 17.10.515

I have a very simple circuit. Please find attached. It is basically a resistor across a port. I run a S-param simulation and can plot the S-params, but unfortunately not the Z-param or Y-param. 

/resized-image/__size/320x240/__key/communityserver-discussions-components-files/33/Capture_5F00_Sch.JPG

/resized-image/__size/320x240/__key/communityserver-discussions-components-files/33/Capture_5F00_Error.JPG

Can anyone point me in the correct direction to sort out this problem? The zpm does work in another design environment, but not in the new design environment (a new project). The virtuoso and the cadence-spectre versions match in both the project environments. I am at a loss at what to look for. 

Hello,

Would anyone know how to setup a PSS or QPSS simulation with 25% dutycycle clock sources or if such a thing is possible with QPSS.

Fig1 (below) is a snapshot of the circuit I am trying to characterize. This has 4 clock ports each with 25%duty cycle in the ON state. Fig2 below shows two of these clocks.

Each path in the circuit consists of two switches with a low pass RC sandwiched in between. The Input is a 50Ohm port sine wave and the output is a 1K resistor. The output nets of all paths are connected together.

I am trying to determine the swept frequency response from input to output (voltage) when the input is from 500Mhz to  510MHz. The Period (T=1/Fp) of each of the pulses is such that Fp=500MHz. The first pulse source has a delay=0, second has delay=T/4, third delay=2T/4, etc...

I am currently getting it working and seeing the correct result (bandpass response) with Transient but the problem is doing a dft at 500MHz with 10KHz spacings needs at least 100us and takes up a lot of time and disk space.

Many Thanks,
Chris.

Fig1

Fig2

Hello, I have a problem with a certain type of transistor,my hyrarchy has a lot components an sub components and visually inspecting them is very hard.

is there a way like in other cadence layout viewer tools , to enter the name of the component or a NET somewhere and it will focus on it visualy or give the hyrarchy path to it?

Thanks.

Hello,

I am using virtuoso version IC 6.1.7-64b.500.1, and I am trying to follow the Spectre RF Workshop-Noise-Aware PLL Design Flow(MMSIM 7.1.1) pdf.

I could find the workshop library "pllMMLib", but I cannot find PLL Macro Model Wizard, and I attached my screen.

Could you please help me install the module "PLL Macro Model Wizard"?

Thanks a lot!

Hello

The document I referenced is https://filebox.ece.vt.edu/~symort/rfworkshop/Mixer_workshop_instruction.pdf. (This is cadence workshop document)

While following the pxf simulation in the above article, the results are different and I have a question.

My result picture is shown below.

<my result error>

<document result>

<my direct plot>

<document direct plot>

The difference with the documentation is that in the direct plot screen after the pxf simulation,

1.output harmonics-> input sideband

2.Frequency axis: out-> frequency axis: absin

3.The results for port0 (RF port) are also different (see photo below).

4.The frequency values in the box are different.

My screen shows 5G, 10G, 1K ~ 10M, but the document is the same as 1K ~ 10M.

Ask for a solution. Thank you.

Hello, I am trying to use two inductors in my LNA as shown bellow to have a S-PARAM response so i will have S11 with lowerst possible values and tweak them for matching network. However when i ran EXPLORER live tuning with SParam as shown bellow i get no change in the response.

I know that Cgs and Cgd with the inductors having a resonance so by Varying L value i should have seen the change in resonance location,

But there is no change.Where did i go wrong?

Thanks. 

Hi all,

What is the most accurate way to simulate the gm of  RF transistors (RF stage) of an active mixer (single balanced or Gilbert cell)?

I tried to simulate it with many ways such as:

1. DC annotation (but of course its incorrect due to the switching operation of the mixer)

2. d(i_ds)/d(v_gs) using HB analysis and then taking the value at zero (since it is a DC characteristic). In this way I chose in the simulator results of HB: Voltage, spectrum, rms, magnitude. 

3. Using the OP, OPT buttons in the calculator and then extracting the gm of the transistor. 

The problem is that each way gives a different value which makes the procedure of designing an active mixer very difficult. In addition, when I simulate the voltage conversion gain of the active mixer and trying to compare it to the formula (2/pi)*gm*RL (either in linear or dB), I get numbers which are way too far from simulations. I understand that I would not get the same results but not different by hundreds percent. 

I see in many publications that people are plotting graphs of mixer's gm vs. different parameters and starting to doubt whether the results are correct.

I would appreciate any help,

Thanks in advance

Hello, I looking for reaching minimal NOISE FIRUGE by peaking a combination of the RLC on the output load as shown bellow.
I tried to do it with PNOISE  but it gives me an error on the |f(in)| i am not sure regarding the sidebands in my case(its not a mixer)

How can i show Noise Figure and optimize it using my output RLC?

Thanks

Hello, i have made a power gain circle for 30dB,for setting a GAIN we need to set a matching network for input and output inpedance.

but in this Gain circles it shows me only one complex number instead of two.(As shown bellow)

Where did i go wrong with using it to find the input and output impedancies needed to be matched in order to have 30dB gain?
Thanks.

Hi, all

Recently, I meet the simulation error as the picture shows when I simulate my circuit with transient.  how can I solve this problem?

thank you~

Hello, i am trying to produce a gain circles on a simple transistor as shown bellow.

i have defined the range from 1 til 30 dB and i dont get any circle just dots in infinity?

Where did i go wrong?
Thanks.

Hello, i have built a matching network of 13dB gain and  NF as shown bellow step by step.(including all the plots and matlab )

its just not working at all,i am doing it exacly by the thoery

taking a point inside the circle-> converting its gamma to Z_source->converting gamma_s into gamma_L with the formulla bellow as shown in the matlab->converting the gamma_L into Z_L-> building the matching network for conjugate of Z_L and Z_c.Its just not working.

where did i got  wrong?

Thanks.

gamma_s=75.8966*exp(deg2rad(280.88)*i);
z_s=gamma2z(gamma_s,50);
s11=0.99875-0.03202*i
s12=721.33*10^(-6)+8.622*10^(-3)*i
s21=-188.37*10^(-3)+30.611*10^(-3)*i
s22=875.51*10^(-3)-100.72*10^(-3)*i
gamma_L=conj((s22+(s12*s21*gamma_s)/(1-s11*gamma_s)))
z_L=gamma2z(gamma_L,50)

Hello, i need to test the  parameter Kf under some conditions in subthreshold.i cannot just plot the OP param,becasue i need to derive it under certain conditions.

Spectre(of Cadence) like BSIM(of Berkley) has developed a method for deriving each parameter in their model.

Is there a way to help me with such manual where i can test in cadence virtuoso the Kf parameter shown in the formula bellow?

Thanks.

Hi All,

I saw the cadence tutorial on measuring IIP3 with 3 tones test (Lets say I have a mixer in the test so two tones are entered in the RF port and one is the LO).

Now, I would like to verify if my receiver meets the bluetooth standard. In the standard it says to enter a signal at -64dBm and two additional signals (interference) 

at -39dBm each which placed one k (lets say k equals to one for the example) channels apart and the other 2k channels apart (so 3 signals enter the RF port). These signals cause an intermodulation product to fall

at the frequency of the desired signal. I would like to measure the IIP3 in this case. 

Now, I need to enter 4 tones and the IIP3 is measured (based on cadence tutorial) using sweep in the hb.

I do not want to sweep power since I need to enter exact power. I tried to use multi sinusoidal option in the port with exact power but it does not work.

How in general am I be able to check communication standard in this way using virtuoso and measure IIP3?

Can someone please help me?

Thanks in advance! 

Hi,

i am designing a broadband (100 MHz -6 GHz BW) receiver chain for  radar/rcs measurement tester. i will put Low noise amplifier after antenna input followed by mixed(10 MHz IF BW and digitizer.

I am facing problem regarding LAN. bandwidth of LAN is  approx 6 GHz(100 MHz-6GHz), gain 25-35 dB, with NF less than 2. I am uncertain about noise floor at the output of LNA.  I dont know exact SNR at the input of LNA but it shall be good.System operation will be on stepped CW waveform so receiver input signal will sweep over the BW and some step size.

so LNA output r noise floor will be? i assume, we can neglect thr role of input noise because it will be lesser than internal noise of LNA.

will it be LNA internal noise (Thermal noise due to BW) only ?

will it be LNA internal noise (Thermal noise due to BW)  + LAN Gain ? -78+25 =-53 dB? internal noise shall be lesser because NF is less than 3 . 

i have practically observed that that output noise floor is much lesser then even thermal noise( over LNA BW). i have gone through some tutorial where  formula says( internal noise+input noise)+gain. in  my case input noise shall be much less than theoretical internal noise. 

Thanks

Hi all,

I am having trouble plotting the IIp3 of gilber RF mixer I made

I have plotted 1 dB compression point using QPSS and QPAC simulation. flo=2.42GHz and frf=2.4GHz , 20 MHz IF

However my IIp3 simulation shows strange results

QPSS and QPAC setup

Hello, i managed to extract my S-param data into vcsv file,however i need a standart S2P file

i have this table displayed, as shown bellow.
is there a way to extract s2p file in cadence virtuoso?
Thanks.

Hello, There is a manual in matlab of matching LNA  shown in the link bellow.

In it as shown in the plot bellow they mention input and output circle plots.

Is there such option of input and output circle in cadence virtuoso?

https://www.mathworks.com/help/rf/examples/designing-matching-networks-part-1-networks-with-an-lna-and-lumped-elements.html

Hi, when I applied a voltage divider implemented by two 100-ohm resistors to a 2Vpp 5GHz vsin source, the phase noise simulation using pnoise/fullspectrum with different types, jitter and source have different results. The simulated output noise results are 165.76aV2/Hz for pmjitter case, and 828.79zV2/Hz for source case. The source case result equals to the output noise calculation.

For my application, the output will be applied to driven circuits and thus pm jitter is concerned. As the pmjitter is based on the noise sampling at the threshold crossings, I was wondering how spectre gets the pmjitter resullts since sampling white noise with infinite bandwidth is impossible to my knowledge?

Interestingly, the Jee result by integration from 10kHz to 2.5GHz is ~41fs and is closed to Jee,rms from the transient noise simulation. I am also not sure how these results come and match each other. If applying the voltage divider output to drive next stages, I was wondering to what extent I can trust the input jitter from these simulations? Thank you.

Hi,

i'm using spectre HB simulation on PA (Power Amplifier) test_bench to perform large signal analysis (i want to plot Output power vs intput power, PAE and Gain)

Although the simulation returns no error, i still can't plot anything. seem like there is an issue with the ports i'm using. (analoglib ports)

i attach an image of my configuration so maybe you can find something helpful in it. 

thank you all for your help

best regards

hi everyone, 

i'm trying to create a netlist for aging simulation. i would like to simulate how power, Gain and PAE (efficiency) are inlfuenced after 3 hours

i would be grateful if someone can correct my syntax in the netlist since i'm trying to make a sweep HB  simulation where the input power is the parameter.

i did it without any error for the sp (S parameters)  simulation.

you can see the images for both sp and hb simulation netlists. (from left to right: sp aging netlist; hb aging netlist)

i will be grateful if someone can provide me some syntax advices.

thanks,

best regards