The PCI-SIG finalized the PCIe 4.0 specification with doubling the data to 16GT/s from 8GT/s in PCIe 3.0 in 2017. Products implementing this technology have begun to hit the market in 2019. Earlier this year, AMD announced it X570 chipset would support the PCIe 4.0 interface and Phison also introduced the world’s first PCIe 4.0 SSD.  With the increasing companies are working on PCIe 4.0 related product development, Cadence, as the key and leading PCIe IP solution vendor in the market, has strived for continuous enhancement of its PCIe 4.0 to be the best in the class IP solution. From our initial PCIe 4.0 solution in 4 years ago (revealed in 2015), we have made many advancements and improvements adding features such as Multi-link with any lane assignment, U.2/U.3 connector, and Automotive support. The variety of applications that PCIe4 finds a home in require extensive robustness and reliability testing over and above the compliance tests mandated by the standard body, i.e., PCI-SIG.

PCIe 4.0 TX Eye-Diagram, Loop-back Test (Long-reach) and RX JTOL Margin Test

Cadence IP team has also implemented additional "stress tests" in conjunction to its already comprehensive IP characterization plan, covering electrical, functional, ESD, Latch-up, HTOL, and yield sorting. Take the Receiver Jitter Tolerance Test (JTOL) for instance. JTOL is a key index to test the quality of the receiver of a system. This test use data generator/analyzer to send data to a SerDes receiver which is then looped back through the transmitter back to the instrument. The data received is compared to the data generated and the errors are counted. The data generator introduce jitter into the transmit data pattern to see how well the receiver functions under non-ideal conditions. While PCI-SIG compliance can be obtained on a single lane implementation, real world scenarios require wider implementations under atypical operating conditions. Cadence’s PCIe 4.0 IP was tested against to additional stressed conditions, such as different combination of multi-lanes operations, “temperature drift” conditions, e.g., bring up the chip at room temperature and check the JTOL at high temperature. 

PCIe 4.0 Sub-system Stress Test Setup

Besides complying with electrical parameters and protocol requirements, real world systems have idiosyncrasies of their own. Cadence IP team also built a versatile “System test” setup in house to perform a system level stress test of its PCIe 4.0 sub-system. The Cadence PCIe 4.0 sub-system is connected to a large number of server and desktop motherboards. This set up is tested with 1000s of cycles of repeated stress under varying operating conditions. Stress tests include speed change from 2.5G all the way to 16G and down, link enable/disable, cold boot, warm boot, entering and exiting low power states, and BER test sweeping presets across different channels. Performing this level of stress test verifies that our IP will operate to spec robustly and reliably when presented with the occasional corner cases in the real world.

More Information

For the demonstration of Cadence PCIe4 PHY Receiver Test and Sub-system Stress Test, see the video:

• PCIe 4.0 Sub-system Stress Test
• PCIe 4.0 PHY Receiver JTOL Test

For more information on Cadence's PCIe IP offerings, see our PCI Express page.

For more information on PCIe in general, and on the various PCI standards, see the PCI-SIG website.

Related Posts

• Blog: PCIe Gen4: It’s Official, We’re Compliant
• Blog: PCIe 3.0 Still Shines While PCIe Keeps Evolving
• Blog: The PCIe 4.0 Era Continues at PCI-SIG Developers Conference 2016

PCI-SIG DevCon 2019 APAC tour has come to Tokyo and Taipei this year. The focus is predominantly around the latest updates for PCIe Gen 5 which its version 1.0 specification was just released this year in May.  A series of presentations provided by PCI-SIG on the day 1 with comprehensive information covering all aspects of Gen 5 specification, including protocol, logical, electrical, compliance updates. On the day 2 (only in Taipei), several member companies shared their view on Testing, PCB analysis and Signal integrity. The exhibit is also another spotlight of this event where the member companies showcased their latest PCIe solutions.

Presentation Track (Taipei), Exhibit (Tokyo), Exhibit (Taipei) 

Cadence, as the market leading PCIe IP vendor, participated APAC tour this year with bringing in its latest PCIe IP solution offering (Gen 5/4) to the region as well as showcasing two live demo setups in the exhibit floor. One setup is the PCIe software development kit (SDK) while the other is the Interop/compliance/debug platform. Both come with the Cadence PCIe Gen 4 hardware setup and its corresponding software kit.

The SDK can be used for Device Driver Development, Firmware Development, and for pre-silicon emulation as well. It supports Xtensa and ARM processor with Linux OS and it also equip with Ethernet interface which can be used for remote debugging. It also supports PCIe stress tests for Speed change, link enable/disable, entry/exist for lower power states, …etc. 

Cadence PCIe 4.0 Software Development Kit

The “System Interop/Compliance/Debug platform” was set up to test with multiple endpoint and System platforms. This system come with integrated Cadence software for basic system debug without the need for analyzer to perform the analysis, such as LTSSM History, TS1/TS2 transmitted/received with time stamp, Link training phases, Capturing Packet errors details, Capturing PHY TX/RX internal state machine details, ...etc.

Cadence PCIe System Interop/Compliance/Debug Platform

The year 2019 is certainly a "fruitful year" for the PCIe as more Gen 4 products are now available in the market, Gen 5 v1.0 specification got officially ratified, and PCI-SIG's revealing of Gen 6 specification development. We were glad to be part of this APAC tour with the chance to further introduce Cadence’s complete and comprehensive PCIe IP solution.

See you all next year in APAC again!

More Information

For more information on Cadence's PCIe IP offerings, see our PCI Express page.

For more information on PCIe in general, and on the various PCI standards, see the PCI-SIG website.

Related Posts

• Blog: Did You “Stress Test” Yet? Essential Step to Ensure a Quality PCIe 4.0 Product
• Blog: PCIe Gen4: It’s Official, We’re Compliant
• Blog: PCIe 3.0 Still Shines While PCIe Keeps Evolving
• Blog: The PCIe 4.0 Era Continues at PCI-SIG Developers Conference 2016

This is the 21st installment of The Rationalist, my column for the Times of India.

When all political parties agree on something, you know you might have a problem. Giriraj Singh, a minister in Narendra Modi’s new cabinet, tweeted this week that our population control law should become a “movement.” This is something that would find bipartisan support – we are taught from school onwards that India’s population is a big problem, and we need to control it.

This is wrong. Contrary to popular belief, our population is not a problem. It is our greatest strength.

The notion that we should worry about a growing population is an intuitive one. The world has limited resources. People keep increasing. Something’s gotta give.

Robert Malthus made just this point in his 1798 book, An Essay on the Principle of Population. He was worried that our population would grow exponentially while resources would grow arithmetically. As more people entered the workforce, wages would fall and goods would become scarce. Calamity was inevitable.

Malthus’s rationale was so influential that this mode of thinking was soon called ‘Malthusian.’ (It is a pejorative today.) A 20th-century follower of his, Harrison Brown, came up with one of my favourite images on this subject, arguing that a growing population would lead to the earth being “covered completely and to a considerable depth with a writhing mass of human beings, much as a dead cow is covered with a pulsating mass of maggots.”

Another Malthusian, Paul Ehrlich, published a book called The Population Bomb in 1968, which began with the stirring lines, “The battle to feed all of humanity is over. In the 1970s hundreds of millions of people will starve to death in spite of any crash programs embarked upon now.” Ehrlich was, as you’d guess, a big supporter of India’s coercive family planning programs. ““I don’t see,” he wrote, “how India could possibly feed two hundred million more people by 1980.”

None of these fears have come true. A 2007 study by Nicholas Eberstadt called ‘Too Many People?’ found no correlation between population density and poverty. The greater the density of people, the more you’d expect them to fight for resources – and yet, Monaco, which has 40 times the population density of Bangladesh, is doing well for itself. So is Bahrain, which has three times the population density of India.

Not only does population not cause poverty, it makes us more prosperous. The economist Julian Simon pointed out in a 1981 book that through history, whenever there has been a spurt in population, it has coincided with a spurt in productivity. Such as, for example, between Malthus’s time and now. There were around a billion people on earth in 1798, and there are around 7.7 billion today. As you read these words, consider that you are better off than the richest person on the planet then.

Why is this? The answer lies in the title of Simon’s book: The Ultimate Resource. When we speak of resources, we forget that human beings are the finest resource of all. There is no limit to our ingenuity. And we interact with each other in positive-sum ways – every voluntary interactions leaves both people better off, and the amount of value in the world goes up. This is why we want to be part of economic networks that are as large, and as dense, as possible. This is why most people migrate to cities rather than away from them – and why cities are so much richer than towns or villages.

If Malthusians were right, essential commodities like wheat, maize and rice would become relatively scarcer over time, and thus more expensive – but they have actually become much cheaper in real terms. This is thanks to the productivity and creativity of humans, who, in Eberstadt’s words, are “in practice always renewable and in theory entirely inexhaustible.”

The error made by Malthus, Brown and Ehrlich is the same error that our politicians make today, and not just in the context of population: zero-sum thinking. If our population grows and resources stays the same, of course there will be scarcity. But this is never the case. All we need to do to learn this lesson is look at our cities!

This mistaken thinking has had savage humanitarian consequences in India. Think of the unborn millions over the decades because of our brutal family planning policies. How many Tendulkars, Rahmans and Satyajit Rays have we lost? Think of the immoral coercion still carried out on poor people across the country. And finally, think of the condescension of our politicians, asserting that people are India’s problem – but always other people, never themselves.

This arrogance is India’s greatest problem, not our people.

© 2007 IndiaUncut.com. All rights reserved.
India Uncut * The IU Blog * Rave Out * Extrowords * Workoutable * Linkastic

Hi,

I have a test session object that I am getting like this:

maeTstSession=maeGetTestSession(test ?session session)

Is it possible to get the test name from this object? I am asking because this object passed to several levels of functions and I don't want to pass an additional argument with the test name

The Cadence® Connections® Verification Program brings together a worldwide network of services, training, and IP development experts that support Cadence verification solutions. The program members help customer accelerate the adoption of new...(read more)

Cadence ® Spectre ® AMS Designer is a high-performance mixed-signal simulation system. The ability to use multiple engines, and drive from a variety of platforms enables you to "rev...

[[ Click on the title to access the full blog on the Cadence Community site. ]]

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.

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.

This is the 21st installment of The Rationalist, my column for the Times of India.

When all political parties agree on something, you know you might have a problem. Giriraj Singh, a minister in Narendra Modi’s new cabinet, tweeted this week that our population control law should become a “movement.” This is something that would find bipartisan support – we are taught from school onwards that India’s population is a big problem, and we need to control it.

This is wrong. Contrary to popular belief, our population is not a problem. It is our greatest strength.

The notion that we should worry about a growing population is an intuitive one. The world has limited resources. People keep increasing. Something’s gotta give.

Robert Malthus made just this point in his 1798 book, An Essay on the Principle of Population. He was worried that our population would grow exponentially while resources would grow arithmetically. As more people entered the workforce, wages would fall and goods would become scarce. Calamity was inevitable.

Malthus’s rationale was so influential that this mode of thinking was soon called ‘Malthusian.’ (It is a pejorative today.) A 20th-century follower of his, Harrison Brown, came up with one of my favourite images on this subject, arguing that a growing population would lead to the earth being “covered completely and to a considerable depth with a writhing mass of human beings, much as a dead cow is covered with a pulsating mass of maggots.”

Another Malthusian, Paul Ehrlich, published a book called The Population Bomb in 1968, which began with the stirring lines, “The battle to feed all of humanity is over. In the 1970s hundreds of millions of people will starve to death in spite of any crash programs embarked upon now.” Ehrlich was, as you’d guess, a big supporter of India’s coercive family planning programs. ““I don’t see,” he wrote, “how India could possibly feed two hundred million more people by 1980.”

None of these fears have come true. A 2007 study by Nicholas Eberstadt called ‘Too Many People?’ found no correlation between population density and poverty. The greater the density of people, the more you’d expect them to fight for resources – and yet, Monaco, which has 40 times the population density of Bangladesh, is doing well for itself. So is Bahrain, which has three times the population density of India.

Not only does population not cause poverty, it makes us more prosperous. The economist Julian Simon pointed out in a 1981 book that through history, whenever there has been a spurt in population, it has coincided with a spurt in productivity. Such as, for example, between Malthus’s time and now. There were around a billion people on earth in 1798, and there are around 7.7 billion today. As you read these words, consider that you are better off than the richest person on the planet then.

Why is this? The answer lies in the title of Simon’s book: The Ultimate Resource. When we speak of resources, we forget that human beings are the finest resource of all. There is no limit to our ingenuity. And we interact with each other in positive-sum ways – every voluntary interactions leaves both people better off, and the amount of value in the world goes up. This is why we want to be part of economic networks that are as large, and as dense, as possible. This is why most people migrate to cities rather than away from them – and why cities are so much richer than towns or villages.

If Malthusians were right, essential commodities like wheat, maize and rice would become relatively scarcer over time, and thus more expensive – but they have actually become much cheaper in real terms. This is thanks to the productivity and creativity of humans, who, in Eberstadt’s words, are “in practice always renewable and in theory entirely inexhaustible.”

The error made by Malthus, Brown and Ehrlich is the same error that our politicians make today, and not just in the context of population: zero-sum thinking. If our population grows and resources stays the same, of course there will be scarcity. But this is never the case. All we need to do to learn this lesson is look at our cities!

This mistaken thinking has had savage humanitarian consequences in India. Think of the unborn millions over the decades because of our brutal family planning policies. How many Tendulkars, Rahmans and Satyajit Rays have we lost? Think of the immoral coercion still carried out on poor people across the country. And finally, think of the condescension of our politicians, asserting that people are India’s problem – but always other people, never themselves.

This arrogance is India’s greatest problem, not our people.

The India Uncut Blog © 2010 Amit Varma. All rights reserved.
Follow me on Twitter.

Hello,
I'm exploring VManager tool capabilities.

I launched a simulation with xrun, which terminates with a fatal error (`uvm_fatal actually).

Then I imported the flow session, through VManager -> Regression -> Collect Runs, linking the directory with ucm and ucd of just failed run.

VManager imports the test with following attributes:

Total Runs =1

#Passed =1

#Failed =0

What I'm missing here? It should be imported as failed test.

If I right click on flow name and choose Analyze All Runs, VManager brings me to Analysis tab and I can see only a PASSED tag in Runs subwindow.

Thank you for any help

Hi all,

         I want to know how to run a regressive test in cadence and merge all ncsim .trn file of each test case into a single file to view all waveform in simvision. I am using Makefile to invoke the test case.

         eg:-

               test0:

                     irun -uvm -sv -access +rwc $(RTL) $(INTER) $(PKG) $(TOP) $(probe) +UVM_VERBOSITY=UVM_MEDIUM +UVM_TESTNAME=test0

             test1:

                   irun -uvm -sv -access +rwc $(RTL) $(INTER) $(PKG) $(TOP) $(probe) +UVM_VERBOSITY=UVM_MEDIUM +UVM_TESTNAME=test1

          I just to call test0 followed by test1 or parallel both test and view the waveform for both tests case.

        I new to this tool and help me with it

Attached is the latest revision of the venerable Specman-Matlab package (Lead Application Engineer Jangook Lee is the latest to have refreshed it for a customer in Asia to support 64 bit mode.  Look for a guest blog post from him on this package shortly.)

There is a README file inside the package that gives a detailed overview, shows how to run a demo and/or validate it’s installed correctly, and explains the general test flow.  The test file included in the package called "test_get_cmp_mdim.e" shows all the capabilities of the package, including:

* Using Specman to initialize and tear down the Matlab engine in batch mode

* Issuing Matlab commands from e-code, using the Specman command prompt to load .m files, initializing variables, and other operational tasks.

* Transfering data to and from the Matlab engine to Specman / an e language test bench

* Comparing data of previously retrieved Matlab arrays

* Accessing Matlab arrays from e-code without converting them to e list data structure

* Convert Matlab arrays into e-lists

Happy coding!

Team Specman

Key Findings: Advantest, in mixed-signal SoC design, sees 50X speedup, 25 day test reduced to 12 hours, dramatic test coverage increase.

Trolling through the CDNLive archives, I discovered another gem. At the May 2013 CDNLive in Munich, Thomas Henkel and Henriette Ossoinig of Advantest presented a paper titled “Timing-accurate emulation of a mixed-signal SoC using Palladium XP”. Advantest makes advanced electronics test equipment. Among the semiconductor designs they create for these products is a test processor chip with over 100 million logic transistors, but also with lots of analog functions.They set out to find a way to speed up their full-chip simulations to a point where they could run the system software. To do that, they needed about a 50X speed-up. Well, they did it!

Figure 1: Advantest SoC Test Products

To skip the commentary, read Advantest's paper here. 

Problem Statement

Software is becoming a bigger part of just about every hardware product in every market today, and that includes the semiconductor test market. To achieve high product quality in the shortest amount of time, the hardware and software components need to be verified together as early in the design cycle as possible. However, the throughput of a typical software RTL simulation is not sufficient to run significant amounts of software on a design with hundreds of millions of transistors.  

Executing software on RTL models of the hardware means long runs  (“deep cycles”) that are a great fit for an emulator, but the mixed-signal content posed a new type of challenge for the Advantest team.  Emulators are designed to run digital logic. Analog is really outside of the expected use model. The Advantest team examined the pros and cons of various co-simulation and acceleration flows intended for mixed signal and did not feel that they could possibly get the performance they needed to have practical runtimes with software testbenches. They became determined to find a way to apply their Palladium XP platform to the problem.

Armed with the knowledge of the essential relationship between the analog operations and the logic and software operations, the team was able to craft models of the analog blocks using reduction techniques that accurately depicted the essence of the analog function required for hardware-software verification without the expense of a continuous time simulation engine.

The requirements boiled down to the following:

• Generation of digital signals with highly accurate and flexible timing

• Complete chip needs to run on Palladium XP platform

• Create high-resolution timing (100fs) with reasonable emulation performance, i.e. at least 50X faster than simulation on the fastest workstations

Solution Idea

The solution approach chosen was to simplify the functional model of the analog elements of the design down to generation of digital signal edges with high timing accuracy. The solution employed a fixed-frequency central clock that was used as a reference.Timing-critical analog signals used to produce accurately placed digital outputs were encoded into multi-bit representations that modeled the transition and timing behavior. A cell library was created that took the encoded signals and converted them to desired “regular signals”. 

Automation was added to the process by changing the netlisting to widen the analog signals according to user-specified schematic annotations. All of this was done in a fashion that is compatible with debugging in Cadence’s Simvision tool.  Details on all of these facets to follow.

The Timing Description Unit (TDU) Format

The innovative thinking that enabled the use of Palladium XP was the idea of combining a reference clock and quantized signal encoding to create offsets from the reference. The implementation of these ideas was done in a general manner so that different bit widths could easily be used to control the quantization accuracy.

Figure 2: Quantization method using signal encoding

Timed Cell Modeling

You might be thinking – timing and emulation, together..!?  Yes, and here’s a method to do it….

The engineering work in realizing the TDU idea involved the creation of a library of cells that could be used to compose the functions that convert the encoded signal into the “real signals” (timing-accurate digital output signals). Beyond some basic logic cells (e.g., INV, AND, OR, MUX, DFF, TFF, LATCH), some special cells such as window-latch, phase-detect, vernier-delay-line, and clock-generator were created. The converter functions were all composed from these basic cells. This approach ensured an easy path from design into emulation.

The solution was made parameterizable to handle varying needs for accuracy.  Single bit inputs need to be translated into transitions at offset zero or a high or low coding depending on the previous state.  Single bit outputs deliver the final state of the high-resolution output either at time zero, the next falling, or the next rising edge of the grid clock, selectable by parameter. Output transitions can optionally be filtered to conform to a configurable minimum pulse width.

Timed Cell Structure

There are four critical elements to the design of the conversion function blocks (time cells):

                Input conditioning – convert to zero-offset, optional glitch preservation, and multi-cycle path

                Transition sorting – sort transitions according to timing offset and specified precedence

                Function – for each input transition, create appropriate output transition

                Output filtering – Capability to optionally remove multiple transitions, zero-width, pulses, etc.

Timed Cell Caveat

All of the cells are combinational and deliver a result in the same cycle of an input transition. This holds for storage elements as well. For example a DFF will have a feedback to hold its state. Because feedback creates combinational loops, the loops need a designation to be broken (using a brk input conditioning function in this case – more on this later). This creates an additional requirement for flip-flop clock signals to be restricted to two edges per reference clock cycle.

Note that without minimum width filtering, the number of output transitions of logic gates is the sum of all input transitions (potentially lots of switching activity). Also note that the delay cell has the effect of doubling the number of output transitions per input transition.

Figure 3: Edge doubling will increase switching during execution

SimVision Debug Support

The debug process was set up to revolve around VCD file processing and directed and viewed within the SimVision debug tool. In order to understand what is going on from a functional standpoint, the raw simulation output processes the encoded signals so that they appear as high-precision timing signals in the waveform viewer. The flow is shown in the figure below.

Figure 4: Waveform post-processing flow

The result is the flow is a functional debug view that includes association across representations of the design and testbench, including those high-precision timing signals.

Figure 5: Simvision debug window setup

Overview of the Design Under Verification (DUV)

Verification has to prove that analog design works correctly together with the digital part. The critical elements to verify include:

• Programmable delay lines move data edges with sub-ps resolution

• PLL generates clocks with wide range of programmable frequency

• High-speed data stream at output of analog is correct

These goals can be achieved only if parts of the analog design are represented with fine resolution timing.

Figure 6: Mixed-signal design partitioning for verification

How to Get to a Verilog Model of the Analog Design

There was an existing Verilog cell library with basic building blocks that included:

- Gates, flip-flops, muxes, latches

- Behavioral models of programmable delay elements, PLL, loop filter, phase detector

With a traditional simulation approach, a cell-based netlist of the analog schematic is created. This netlist is integrated with the Verilog description of the digital design and can be simulated with a normal workstation. To use Palladium simulation, the (non-synthesizable) portions of the analog design that require fine resolution timing have to be replaced by digital timing representation. This modeling task is completed by using a combination of the existing Verilog cell library and the newly developed timed cells.

Loop Breaking

One of the chief characteristics of the timed cells is that they contain only combinational cells that propagate logic from inputs to outputs. Any feedback from a cell’s transitive fanout back to an input creates a combinational loop that must be broken to reach a steady state. Although the Palladium XP loop breaking algorithm works correctly, the timed cells provided a unique challenge that led to unpredictable results.  Thus, a process was developed to ensure predictable loop breaking behavior. The user input to the process was to provide a property at the loop origin that the netlister recognized and translated to the appropriate loop breaking directives.

Augmented Netlisting

Ease of use and flow automation were two primary considerations in creating a solution that could be deployed more broadly. That made creating a one-step netlisting process a high-value item. The signal point annotation and automatic hierarchy expansion of the “digital timing” parameter helped achieve that goal. The netlister was enriched to identify the key schematic annotations at any point in the hierarchy, including bit and bus signals.

Consistency checking and annotation reporting created a log useful in debugging and evolving the solution.

Wrapper Cell Modeling and Verification

The netlister generates a list of schematic instances at the designated “netlister stop level” for each instance the requires a Verilog model with fine resolution timing. For the design in this paper there were 160 such instances.

The library of timed cells was created; these cells were actually “wrapper” cells comprised of the primitives for timed cell modeling described above. A new verification flow was created that used the behavior of the primitive cells as a reference for the expected behavior of the composed cells. The testing of the composed cells included had the timing width parameter set to 1 to enable direct comparison to the primitive cells. The Cadence Incisive Enterprise Simullator tool was successfully employed to perform assertion-based verification of the composed cells versus the existing primitive cells.

Mapping and Long Paths

Initial experiments showed that inclusion of the fine resolution timed cells into the digital emulation environment would about double the required capacity per run. As previously pointed out, the timed cells having only combinational forward paths creates a loop issue. This fact also had the result of creating some such paths that were more than 5,000 steps of logic. A timed cell optimization process helped to solve this problem. The basic idea was to break the path up by adding flip-flops in strategic locations to reduce combinational path length. The reason that this is important is that the maximum achievable emulation speed is related to combinational path length.

Results

Once the flow was in place, and some realistic test cases were run through it, some further performance tuning opportunities were discovered to additionally reduce runtimes (e.g., Palladium XP tbrun mode was used to gain speed). The reference used for overall speed gains on this solution was versus a purely software-based solution on the highest performance workstation available.

The findings of the performance comparison were startlingly good:

• On Palladium XP, the simulation speed is 50X faster than on Advantest’s fastest workstation

• Software simulation running 25 days can now be run in 12 hours -> realistic runtime enables long-running tests that were not feasible before

• Now have 500 tests that execute once in more than 48 hours

• They can be run much more frequently using randomization and this will increase test coverage dramatically

Steve Carlson

The complexity and size of mixed-signal designs in wireless, power management, automotive, and other fast growing applications requires continued advancements in a mixed-signal verification methodology. An SoC, in these fast growing applications, incorporates a large number of analog and mixed-signal (AMS) blocks/IPs, some acquired from IP providers, some designed, often concurrently. AMS IP must be verified independently, but this is not sufficient to ensure an SoC will function properly and all scenarios of interaction among many different AMS IP blocks at full chip / SoC level must be verified thoroughly. To reduce an overall verification cycle, AMS IP and SoC verification teams must work in parallel from early stages of the design. Easier said than done! We will outline a methodology than can help.

AMS designers verify their IP meets required specifications by running a testbench they develop for standalone / out of-context verification. Typically, an AMS IP as analog-centric, hierarchal design in schematic, composed of blocks represented by transistor, HDL and behavioral description verified in Virtuoso® Analog Design Environment (ADE) using Spectre AMS Designer simulation. An SoC verification team typically uses UVM SystemVerilog testbech at full chip level where the AMS IP is represented with a simple digital or real number model running Xcelium /DMS simulation from the command line.

Ideally, AMS designers should also verify AMS IP function properly in the context of full-chip integration, but reproducing an often complex UVM SystemVerilog testbench and bringing over top-level design description to an analog-centric environment is not a simple task.

Last year, Cadence partnered with Infineon on a project with a goal to automate the reuse of a top-level testbench in AMS verification. The automation enabled AMS verification engineers to automatically configure setup for verification runs by assembling all necessary options and files from the AMS IP Virtuoso GUI and digital SoC top-level command line configurations. The benefits of this method were:

• AMS verification engineers did not need to re-create complex stimuli representing interaction of their IP at the top level
• Top-level verification stays external to the AMS IP verification environment and continues to be managed by the SoC verification team, but can be reused by the AMS IP team without manual overhead
• AMS IP is verified in-context and any inconsistencies are detected earlier in the verification process
• Improved productivity and overall verification time

For more details, please see Infineon’s CDNLlive presentation.

This blog talks about how to enable the AMS Designer flex mode.(read more)

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