1 Danish Krone = 5.7711 Mauritian Rupee

1 Danish Krone = 0.2224 Australian Dollar

1 Fiji Dollar = 1.6672 Saudi Riyal

1 Fiji Dollar = 17.6253 Mauritian Rupee

1 Fiji Dollar = 0.6793 Australian Dollar

1 New Zealand Dollar = 2.3056 Saudi Riyal

1 New Zealand Dollar = 24.3742 Mauritian Rupee

1 New Zealand Dollar = 0.9394 Australian Dollar

1 Croatian Kuna = 0.5414 Saudi Riyal

1 Croatian Kuna = 5.7231 Mauritian Rupee

1 Croatian Kuna = 0.2206 Australian Dollar

1 Peruvian Nuevo Sol = 1.1051 Saudi Riyal

1 Peruvian Nuevo Sol = 11.6828 Mauritian Rupee

1 Peruvian Nuevo Sol = 0.4502 Australian Dollar

1 Dominican Peso = 0.0682 Saudi Riyal

1 Dominican Peso = 0.7215 Mauritian Rupee

1 Dominican Peso = 0.0278 Australian Dollar

1 Papua New Guinean Kina = 1.095 Saudi Riyal

1 Papua New Guinean Kina = 11.5761 Mauritian Rupee

1 Papua New Guinean Kina = 0.4461 Australian Dollar

1 Brunei Dollar = 2.6579 Saudi Riyal

1 Brunei Dollar = 28.0984 Mauritian Rupee

1 Brunei Dollar = 1.0829 Australian Dollar

X is a song written by Y and famously covered by Z. Time Magazine’s Josh Tyrangiel described it thus:

Y murmured the original like a dirge, but except for a single overwrought breath before the music kicks in, Z treated the 7-min. song like a tiny capsule of humanity, using his voice to careen between glory and sadness, beauty and pain, mostly just by repeating the word X. It’s not only Z’s best song — it’s one of the great songs, and because it covers so much emotional ground and is not (yet) a painfully obvious choice, it has become the go-to track whenever a TV show wants to create instant mood. ‘X can be joyous or bittersweet, depending on what part of it you use,’ says Sony ATV’s Kathy Coleman. ‘It’s one of those rare songs that the more it gets used, the more people want to use it.’

Name X, Y and Z.

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EDA investor and former executive Jim Hogan is optimistic about automotive electronics, but he has some concerns as well. At the recent Design Automation Conference (DAC 2015), he delivered a speech titled “The Looming Quality, Reliability, and Safety Crisis in Automotive Electronics...Why is it and what can we do to avoid it?"

Hogan gave the keynote speech for IP Talks!, a series of over 30 half-hour presentations located at the ChipEstimate.com booth. Presenters included ARM, Cadence, eSilicon, Kilopass, Sidense, SilabTech, Sonics, Synopsys, True Circuits, and TSMC. Held in an informal setting, the talks addressed the challenges faced by SoC design teams and showed how the latest developments in semiconductor IP can contribute to design success.

Jim Hogan delivers keynote speech at DAC 2015 IP Talks!

Hogan talked about several phases of automotive electronics. These include assisted driving to avoid collisions, controlled automation of isolated tasks such as parallel parking, and, finally, fully autonomous vehicles, which Hogan expects to see in 15 to 20 years. The top immediate priorities for automotive electronics designers, he said, will be government regulation, fuel economy, advanced safety, and infotainment.

More Code than a Boeing 777

According to Hogan, today’s automobiles use 50-100 microcontrollers per car, resulting in a worldwide automotive semiconductor market of around $40 billion. The global market for advanced automotive electronics is expected to reach $240 billion by 2020. Software is growing faster in the automotive market than it is in smartphones. Hogan quoted a Ford vice president who observed that there are more lines of code in a Ford Fusion car than a Boeing 777 airplane.

One unique challenge for automotive electronics designers is long-term reliability. This is because a typical U.S. car stays on the road for 15 years, Hogan said. Americans are holding onto new vehicles for a record 71.4 months.

Another challenge is regulatory compliance. Aeronautics is highly regulated from manufacturing to air traffic control, and the same will probably be true of automated cars. Hogan speculated that the Department of Transportation will be the regulatory authority for autonomous cars. Today, automotive electronics providers must comply with the ISO26262 automotive functional safety specification.

So where do we go from here? “We’ve got to change our mindset,” Hogan said. “We’ve got to focus on safety and reliability and demand a different kind of engineering discipline.” You can watch Hogan’s entire presentation by clicking on the video icon below, or clicking here. You can also watch other IP Talks! videos from DAC 2015 here.

https://youtu.be/qL4kAEu-PNw

Richard Goering

Related Blog Posts

DAC 2015: See the Latest in Semiconductor IP at “IP Talks!”

Automotive Functional Safety Drives New Chapter in IC Verification

Dear all,

I am using Conformal Constraint Designer (Version 17.1) to analyse a SystemVerilog based design.

While performing default HDL checks it finds  some violations (issues) in RTL and complains (warnings, etc) about RTL checks and others.

My questions:

Is there any directive which I can add to RTL (system Verilog) so that particular line of code or signal is ignored or not checked for HDL or RTL checks.

I can set ignore rules in rule manager (gui) but it does not seems effective if code line number changes or new signals are introduced.

What is the best way to customize default_hdl_rules ?

I will be grateful for your guidance.

Thanks for your time.

When I place a pcell and do not change the W parameter (default is used) the value is not saved in the OA cell property.

When I change the default value of the super master now, the old pcell will get the new default value automatically because there is nothing saved inside the OA cell for this parameter.

Do you have any Idea, that how we can save the default values in the OA cell properties so that this value doesn't get updated if the default values are updated in the new PDKs

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.

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.

Imagine you are on a vacation with your family, and suddenly, your phone starts buzzing. You pick it up and what are you looking at is a bunch of pending, unanswered e-mails. You start recollecting the checklist you had made before taking off only to realize that you haven’t put on the automatic replies! (read more)

Hi all,

I am creating shapes on plane layers for a coupon and want to void them using axlShapeAutoVoid()

The shapes are attached to a symbol.

I've tried using axlShapeAutoVoid, but this only voids the pins, not the route keepouts created by nc_backdrill.

I also tried selecting the shape, individually, then running axlShapeAutoVoid. That was unsuccessful, also.

planeShapes is a list of shapes I created. The code for voiding:

;run backdrill to get route keepouts
axlShell("setwindow pcb;backdrill setup ;setwindow form.nc_backdrill;FORM nc_backdrill apply ;FORM nc_backdrill close")

foreach(sHape planeShapes
axlShapeAutoVoid(car(sHape))
)

Hi,

I've vhdl block containing fsm . IMC not able to auto extract the state machine coded like this:

There is a intermediate state state_mux  between next_state & state.

Pls. help in guiding IMC how to recognize this FSM coding style? 

Snipped of the fsm code:

----------------------------------------------------------------------------------------------------------------------------------------------

               type state_type is (ST_IDLE, ST_ADDRESS, ST_ACK_ADDRESS, ST_READ, ST_ACK_READ, ST_WRITE, ST_ACK_WRITE, ST_IDLE_BYTE);

               signal state : state_type;

               signal state_mux : state_type;

               signal next_state : state_type;

process(state_mux, start)

         begin

               next_state <= state_mux;

               next_count <= (others => '0');

           case (state_mux) is

                 when ST_IDLE => 

                            if(start = '1') then

                                 next_state <= ST_ADDRESS;

                              end if;

            when ST_ADDRESS =>

   …………….

          when others => null;

         end case;

     end process;

process(scl_clk_n, active_rstn)

               begin

                      if(active_rstn = '0') then

                           state <= ST_IDLE after delay_f;

                  elsif(scl_clk_n'event and scl_clk_n = '1') then

                             state <= next_state after delay_f;

                            end if;

end process;

process(state, start)

               begin

                     state_mux <= state;

               if(start = '1') then

                       state_mux <= ST_IDLE;

                              end if;

               end process;

Thanks

Raghu

Hi,

I'm doing fault injection with ncsim and got stuck at the following (and not so useful) message: "ncsim: *E,FLTIGF: [FLT] Failed to inject fault at circuit_tb.U0.n2174." I already tried with other NETs, with SET, SA0, SA1, always the same error occurs.

My scripts so far, considering I already compiled the Verilog testbench and also the gates from the technology library (gate-level simulation):

#this runs ok

ncelab -work worklib -cdslib circuit/trunk/backend/synthesis/work/cds.lib -logfile ncelab.log -errormax 15 -access +wc -status -timescale 1ps/1ps worklib.circuit_tb -fault_file circuit/trunk/backend/synthesis/scripts/fi.list

#this runs ok
ncsim -fault_good_run -fault_tw 1ns:4ns -fault_work fault_db -fault_overwrite worklib.circuit_tb:module -input ../scripts/fs_strobe.tcl -exit

#this runs NOT OK
ncsim -fault_sim_run -fault_work fault_db worklib.circuit_tb:module -input ../scripts/injection.tcl -exit

After the above command I get: "ncsim: *E,FLTIGF: [FLT] Failed to inject fault at circuit_tb.U0.n2174."

Here are the files called from the commands above.

fi.list:

fault_target circuit_tb.U0.n2174 -type SET+SA1+SA0

fs_strobe.tcl:

fs_strobe circuit_tb.WRITE_OUT circuit_tb.PC_OUT[0]

injection.tcl:

fault -stop_severity 3 -inject -time 2ns -type sa1 circuit_tb.U0.n2174

I already checked the NETs with simvision, so their paths are correct.

Any ideas?

PS: I know about Xcellium, however, I don't have it yet.

Here are two screen capture of Before and After Autorouting my board. Padstacks have all been revised and corrected. The Capture Schematic is correct. All Footprints have been verified after Padstack revision. a new NETLIST generation have been done after some corrections made in Capture. I have imported the new Logic. I revised my Layout Cross Section as such: TOP, GND, VCC, BOTTOM. Both VCC and GND shapes have been assigned to their respective logical GND and VCC Nets (verified). Yet, I still have the Autorouter to systematically use extra vias to make GND and VCC connections to the VCC and GND planes. Where a simple utilisation of the part padstack inner layer would have been indicated. What Im I missing ?

Question for forum:

I’m currently working on a code to automatically add CLP files to DRA files and then add two classes called “APPROVED” and “CLP”. To do this manually you have to open a DRA file, click file import subdrawing and choose the clp file with the same name as dra. (path already set). You then set the clp to position x 0 0. And then click on Set Up > Subclasses > Package geometry and type in “Approved” and “Clp.”

So far we’ve recorded the macros in Allegro for all of these actions. The macros correspond to one specific file name and we want to apply this to numerous files. To do this we created a python program that locates all of the specified CLP and DRA files, and if they have a matching name, runs a for loop that puts each file name into a stored variable that runs a loop for each file. We converted this script into batch and then added a function that we thought would run Allegro macros from batch.

In order to get the script working, we need to have an allegro batch command that will run the script without opening the Allegro start popup, or closing the popup when it appears.  We need to do this to run any script from starting Allegro.

I’ve done another similar program in batch where I made a for loop for each dra file and within the loop there was a batch a2dxf command that converted all dra files to dxf files. Is there a similar batch command for adding clp files to position 0 0 and/ or adding classes? If anyone has done something similar please let me know!

Thank you very much for the help.

Jen

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.

Since the release of the Automated Device Placement and Routing solution last year, we have continued to improve and build upon it. In this blog, I’ll talk about the latest addition—the Auto Device Array form—how this is an integral piece of the new Automated Device Placement and Routing solution.(read more)

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