1 Zambian Kwacha = 0.0077 Mauritian Rupee

1 South Korean Won = 0.0326 Mauritian Rupee

1 Jordanian Dinar = 55.9692 Mauritian Rupee

1 Lebanese Pound = 0.0263 Mauritian Rupee

1 Bahraini Dinar = 105.0042 Mauritian Rupee

1 Chilean Peso = 0.0481 Mauritian Rupee

1 Maldivian Rufiyaa = 2.5613 Mauritian Rupee

1 Malaysian Ringgit = 9.1624 Mauritian Rupee

1 Nicaraguan Cordoba Oro = 1.1542 Mauritian Rupee

1 Netherlands Antillean Guilder = 22.1203 Mauritian Rupee

1 Estonian Kroon = 2.7843 Mauritian Rupee

1 Danish Krone = 5.7711 Mauritian Rupee

1 Fiji Dollar = 17.6253 Mauritian Rupee

1 New Zealand Dollar = 24.3742 Mauritian Rupee

1 Croatian Kuna = 5.7231 Mauritian Rupee

1 Peruvian Nuevo Sol = 11.6828 Mauritian Rupee

1 Dominican Peso = 0.7215 Mauritian Rupee

1 Papua New Guinean Kina = 11.5761 Mauritian Rupee

1 Brunei Dollar = 28.0984 Mauritian Rupee

In the world of analog design, IP3—the third order intercept point, is a known parameter that is used to measure the linearity in the radio frequency (RF) components. The extracted IP3 values are very essential to determine the operating power ...(read more)

I have a modeless informational dialog box defined at the beginning of a SKILL script, but its contents don't display until the script finishes.

How do you get a modeless dialog box contents to display while a SKILL script is running?

procedure(myproc()

   prog((myvars)

     hiDisplayAppDBox()    ; opens blank dialog box - no dboxText contents show until script completes!

     ....rest of SKILL code in script...launches child processes

   );prog

);proc

Vegas, here we come. All of us fun EDA engineers at once. Be prepared, next week’s Design Automation Conference will be busy! The trends I had outlined after last DAC in 2018—system design, cloud, and machine learning—have...(read more)

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.

Hi All,

I'm trying to understand checkpoint concept. When I found save and restart concept in cdnshelp, There is just describing about "$save" and "xrun -r "~~~".

and I found also the below link about save restart and it saves your time.

But I can't find any benefits from my experiment from save&restart article( I fully agree..the article)

Ok, So I'v got some experiment  Here.

1. I declared $save and got the below result as I expected within the simple UVM code.

In UVM code...

$display("TEST1");
$display("TEST2");
$save("SAVE_TEST");
$display("TEST3");
$display("TEST4");

And I restart at "SAVE_TEST" point by xrun -r "SAVE_TEST", I've got the below log

xcelium> run
TEST3
TEST4

Ok, It's Good what I expected.(The concept of Save and Restore is simple: instead of re-initializing your simulation every time you want to run a test, only initialize it once. Then you can save the simulation as a “snapshot” and re-run it from that point to avoid hours of initialization times. It used to be inconvenient. I agree..)

2. But The Problem is that I can't restart with modified code. Let's see the below example.

I just modified TEST5 instead of "TEST3"

$display("TEST1");
$display("TEST2");
$save("SAVE_TEST");
$display("TEST5"); //$display("TEST3");
$display("TEST4");

and I rerun with xrun -r "SAVE_TEST", then I've got the same log

xcelium> run
TEST3
TEST4

There is no "TEST5". Actually I expected "TEST5" in the log.From here We know $save can't support partially modified code after $save. 

Actually, through this, we can approach to our goal about saving developing time. 

So I want to know Is there any possible way that instead of re-initializing our simulation every time we want to run a test, only initialize it once and keep developing(debugging) our code ?

If we do, Could you let me know the simple example?

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G DATA TOTAL SECURITY version 25.4.0.3 suffers from an active-x buffer overflow vulnerability.

Ubuntu Security Notice 4058-1 - It was discovered that Bash incorrectly handled the restricted shell. An attacker could possibly use this issue to escape restrictions and execute any command.

Ubuntu Security Notice 4058-2 - USN-4058-1 fixed a vulnerability in bash. This update provides the corresponding update for Ubuntu 12.04 ESM and Ubuntu 14.04 ESM. It was discovered that Bash incorrectly handled the restricted shell. An attacker could possibly use this issue to escape restrictions and execute any command. Various other issues were also addressed.

Ubuntu Security Notice 4180-1 - It was discovered that Bash incorrectly handled certain inputs. An attacker could possibly use this issue to cause a crash or execute arbitrary code.