1 Croatian Kuna = 0.0553 Omani Rial

1 Croatian Kuna = 0.6246 Malaysian Ringgit

1 Croatian Kuna = 2.2344 Maldivian Rufiyaa

1 Croatian Kuna = 5.7231 Mauritian Rupee

1 Croatian Kuna = 8.19 Macedonian Denar

1 Croatian Kuna = 1.416 Moroccan Dirham

1 Croatian Kuna = 0.1201 Cayman Islands Dollar

1 Peruvian Nuevo Sol = 1.3102 Romanian Leu

1 Peruvian Nuevo Sol = 0.1128 Omani Rial

1 Peruvian Nuevo Sol = 1.2751 Malaysian Ringgit

1 Peruvian Nuevo Sol = 4.5612 Maldivian Rufiyaa

1 Peruvian Nuevo Sol = 11.6828 Mauritian Rupee

1 Peruvian Nuevo Sol = 16.7185 Macedonian Denar

1 Peruvian Nuevo Sol = 2.8905 Moroccan Dirham

1 Peruvian Nuevo Sol = 0.2452 Cayman Islands Dollar

At 10:30 AM PST Dorian and Max will be off running!

1 Dominican Peso = 0.0809 Romanian Leu

1 Dominican Peso = 0.007 Omani Rial

1 Dominican Peso = 0.0787 Malaysian Ringgit

1 Dominican Peso = 0.2817 Maldivian Rufiyaa

1 Dominican Peso = 0.7215 Mauritian Rupee

1 Dominican Peso = 1.0325 Macedonian Denar

1 Dominican Peso = 0.1785 Moroccan Dirham

1 Dominican Peso = 0.0151 Cayman Islands Dollar

NCAA Division II, Emporia State University served as the 2^ndmeet of the Outdoor Track and Field season for the Indians.  Highlights from the meet include:

Ian Stand, a sophomore from Bay Point, California returned to the discus ring and completed a toss of 36.52 meters, an improvement from his first meet.  Stand, also earned a seventh place finish in the shot put with a distance of 10.76 meters. 

1 Papua New Guinean Kina = 1.2982 Romanian Leu

1 Papua New Guinean Kina = 0.1118 Omani Rial

1 Papua New Guinean Kina = 1.2634 Malaysian Ringgit

1 Papua New Guinean Kina = 4.5195 Maldivian Rufiyaa

1 Papua New Guinean Kina = 11.5761 Mauritian Rupee

1 Papua New Guinean Kina = 16.5657 Macedonian Denar

1 Papua New Guinean Kina = 2.8641 Moroccan Dirham

1 Papua New Guinean Kina = 0.243 Cayman Islands Dollar

1 Brunei Dollar = 3.1512 Romanian Leu

1 Brunei Dollar = 0.2713 Omani Rial

1 Brunei Dollar = 3.0667 Malaysian Ringgit

1 Brunei Dollar = 10.9702 Maldivian Rufiyaa

1 Brunei Dollar = 28.0984 Mauritian Rupee

1 Brunei Dollar = 40.2097 Macedonian Denar

1 Brunei Dollar = 6.952 Moroccan Dirham

1 Brunei Dollar = 0.5898 Cayman Islands Dollar

With more and more SoCs employing sophisticated interconnect IP to link multiple processor cores, caches, memories, and dozens of other IP functions, the designs are enabling a new generation of low-power servers and high-performance mobile devices. The complexity of the interconnects and their advanced configurability contributes to already formidable design and verification challenges which lead to the following questions:

While your interconnect subsystem might have a correct functionality, are you starving your IP functions of the bandwidth they need? Are requests from latency-critical initiators processed on time? How can you ensure that all applications will receive the desired bandwidth in steady-state and corner use-cases?

To answer these questions, Cadence recommends the Performance Verification Methodology to ensure that the system performance meets requirements at the different levels:

1. Performance characterization: The first level of verification aims to verify the path-to-path traffic measuring the performance envelope. It targets integration bugs like clock frequency, buffer sizes, and bridge configuration. It requires to analyze the latency and bandwidth of design’s critical paths.
2. Steady state workloads: The second level of verification aims to verify the master-by-master defined loads using traffic profiles. It identifies the impact on bandwidth when running multi-master traffic with various Quality-of-Service (QoS) settings. It analyzes the DDR sub-system’s efficiency, measures bandwidth and checks whether masters’ QoS requirements are met.
3. Application specific use cases: The last level of verification simulates the use-cases and reaches the application performance corner cases. It analyzes the master-requested bandwidth as well as the DDR sub-system’s efficiency and bandwidth.

Cadence has developed a set of tools to assist customers in performance validation of their SoCs. Cadence Interconnect Workbench simplifies the setup and measurement of performance and verification testbenches and makes debugging of complex system behaviors a snap. The solution works with Cadence Verification IPs and executes on the Cadence Xcelium® Enterprise Simulator or Cadence Palladium® Accellerator/Emulator, with coverage results collected and analyzed in the Cadence vManager  Metric-Driven Signoff Platform.

To verify the performance of the Steady State Workloads, Arm has just released a new AMBA Adaptive Traffic Profile (ATP) specification which describes AMBA abstract traffic attributes and defines the behavior of the different traffic profiles in the system.

With the availability of Cadence Interconnect Workbench and AMBA VIP support of ATP, early adopters of the AMBA ATP specification can begin working immediately, ensuring compliance with the standard, and achieving the fastest path to SoC performance verification closure.

For more information on the AMBA Adaptive Traffic Profile, you can visit Dimitry's blog on AMBA Adaptive Traffic Profiles: Addressing The Challenge. 

More information on Cadence Interconnect Workbench solution is available at Cadence Interconnect Solution webpage.

Thierry

Who used to be known as Dileep Kumar, and is now married to Saira Banu?

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

“I am a small eye poet.” Who once wrote these words in a letter to his mother?

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

In the book “The World of _____” by Bennett Alan Weinberg and Bonnie K Bealer, there is a photograph of a label from a jar of pharmaceutical-grade crystals. It reads:

“WARNING: MAY BE HARMFUL IF INHALED OR SWALLOWED. HAS CAUSED MUTAGENIC AND REPRODUCTIVE EFFECTS IN LABORATORY ANIMALS. INHALATION CAUSES RAPID HEART RATE, EXCITEMENT, DIZZINESS, PAIN, COLLAPSE, HYPOTENSION, FEVER, SHORTNESS OF BREATH. MAY CAUSE HEADACHE, INSOMNIA, VOMITING, STOMACH PAIN, COLLAPSE AND CONVULSIONS.”

Fill in the blank.

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

Formal verification is a complex technology that has traditionally required experts or specialized teams who stood apart from the IC design and verification flow. Taking a different approach, a new release of the Cadence JasperGold formal verification platform (June 8, 2015) provides formal techniques that complement simulation, emulation, and debugging in the form of “Apps” or under-the-hood solutions that any design or verification engineer can use.

JasperGold was the initial (in fact only) product of Jasper Design Automation, acquired by Cadence in 2014. Jasper pioneered the formal Apps concept several years ago. While the company had previously sold JasperGold as a one-size-fits-all solution, Jasper began selling semi-automated JasperGold Apps that solved specific problems using formal analysis technology.

The new release is the next generation of JasperGold and will be available later this month. It includes three major improvements over previous Cadence and Jasper formal analysis offerings:

• A unified Cadence Incisive and JasperGold formal verification platform delivers up to 15X performance gain over previous solutions.
• JasperGold is integrated into the Cadence System Development Suite, where it provides formal-assisted simulation, emulation, and coverage. As a result, System Development Suite users can find bugs three months earlier than existing verification methods.
• JasperGold’s formal analysis engines are integrated with the recently announced Indago debug platform, automating root cause analysis and on-the-fly, what-if exploration.

Best of Both Formal Verification Worlds

Taking advantage of technologies from both Cadence and Jasper, the new JasperGold represents a “best of both worlds” solution, according to Pete Hardee, product management director at Cadence. This solution combines technologies from the Cadence Incisive Enterprise Verifier and Incisive Formal Verifier with JasperGold formal analysis engines.

For example, to ease migration from Incisive formal tools, Cadence has integrated an Incisive common front end into the JasperGold apps platform. Jasper formal engines can run within the Incisive run-time environment. Cadence has also brought some selected Incisive formal engines into JasperGold.

As shown to the right, the JasperGold platform supports both the existing JasperGold front-end parser and the Incisive front-end parser. Hardee observed that this dual parser arrangement simplifies migration from Incisive formal tools to JasperGold, and provides a common compilation environment for people who want to use JasperGold with Incisive simulation. Further, the common run-time environment enables formal-assisted simulation.

The combination of JasperGold engines and Incisive engines supports two use models for formal analysis: formal proofs and bug hunting. In the first case, formal engines try all combinations of inputs without a testbench. The test is driven by formal properties written in languages such as SVA (SystemVerilog assertions) or PSL (Property Specification Language). Completion of a property is exhaustive proof that something can or cannot happen. This provides a “much stronger result” than simulation, Hardee said.

He also noted that formal analysis doesn’t necessarily require that all properties are completed. “You can get a lot of value even if proofs don’t complete,” he said. “Proofs that run deep enough to find bugs are just fine.”

Bug hunting involves random searches, and JasperGold bug hunting engines are very fast. However, these engines don’t necessarily use the most optimal path to get to a bug. So, Cadence engineers brought a constraint solver from Incisive and integrated it into JasperGold. “It looks at the constraints in the environment and gives you a better starting point,” Hardee said. “It takes more up-front time, but once you’ve done that the bug hunting engines can actually take a shorter path and find a bug a lot quicker.”

Another new JasperGold capability from the Incisive Formal Verifier is called “search pointing.” This uses simulation to penetrate deeply into the state space, and then kicks off a random formal search from a given point that you’ve reached in simulation. This technique makes it possible to find bugs that are very deep in the design.

It is probably clear by now that a number of different formal “engines” may be required to solve a given verification problem. Traditionally, a formal tool (or user) will farm a problem out to many engines and see which one works best. To put more intelligence into that process, Cadence launched the Trident “multi-cooperating engine” a couple of years ago. That has now been brought into JasperGold, where it helps “orchestrate” the engines according to what will work best for the design. This is a big part of the reason for the 15X speedup noted earlier in this post.

Integration with System Development Suite

The Cadence System Development Suite is an integrated set of hardware/software development and verification engines, including virtual prototyping, Incisive simulation, emulation, and FPGA-based prototyping. As shown below, JasperGold technology is integrated into the System Development Suite in several places, including formal-assisted debug, formal-assisted verification closure, formal-assisted simulation, formal-assisted emulation, and the Incisive vManager verification planning tool.

Formal-assisted emulation sounds like it should be easy, especially since Cadence has both accelerated verification IP (VIP) and assertion-based VIP. However, there’s a complication. Accelerated VIP represents less verification content than simulation VIP, because you have to remove many checkers to get VIP to compile on a Palladium emulator. That’s because the Palladium requires synthesizable code.

What you can do, however, is use assertion-based VIP in “snoop mode” as shown below. Assertion-based VIP coded in synthesizable SystemVerilog can replace the missing checkers in accelerated VIP. In this diagram, everything in the green box is running in the emulator and is thus completely accelerated.

Another example of formal-assisted emulation has to do with deep traces. As Hardee noted, emulation will produce very long traces, and it can be very difficult to find a point of interest in the trace and determine what caused an error. With formal-assisted emulation, users can find interesting events within the traces and create properties that mark them, so a debugger can find these events and trace back to the root cause.

Formal-assisted verification closure is available with the new JasperGold release. This is possible because you can use the vManager product to determine which tasks were completed by formal engines. It’s important information for verification managers who are not used to formal tools, Hardee noted.

Another aspect of formal-assisted verification closure is the JasperGold Unreachability Analysis (UNR) App, which can save simulation users weeks of time and effort. This App takes in the simulation coverage database and RTL, and automatically generates properties to explore coverage holes and determine if holes are reachable or unreachable. The App then generates an unreachable coverage point database. If the unreachable code does something useful, there’s a bug in the design or the testbench; if not, you don’t have to worry about it. The diagram below shows how it works.

Formal-Assisted Debugging

The third major component of the JasperGold announcement is the integration of formal analysis into the Indago debugging platform. As shown below, this platform has several apps, including the Indago Debug Analyzer. Two formal debug capabilities from the Jasper Visualize environment have been added to the the Indago Debug Analyzer:

• Highlight Relevant Logic: This highlights the “cone of influence,” or the logic that is involved in reaching a given point
• Why: This button highlights the immediate causes for a given event, and allows users to trace backwards in time

More formal capabilities will come with the Indago Advanced Debug Analyzer app, scheduled for release towards the end of 2015. This includes Quiet Trace, a Jasper capability that reduces trace activity to transactions relevant to an event. Also, a what-if analysis allows on-the-fly trace editing and recalculation to explore effects and sensitivities, without having to re-compile and re-execute the simulation.

Finally, Cadence has a Superlint flow that is now fully integrated with the JasperGold Visualize debugger. This two-tiered flow includes a basic lint capability as well as automated formal analysis based on the JasperGold Structural Property Synthesis app. “This could be a very good entry point for designers to start using formal,” Hardee said.

“Formal is taking off,” Hardee concluded. “People are no longer talking about return on investment for formal—they have established that. Now they’re supporting a proliferation of formal in their companies such that a wider set of people experience the benefit from that proven return on investment.”

Further information is available at the JasperGold Formal Verification Platform (Apps) page.

Richard Goering

Related Blog Posts

- JUG Keynote—How Jasper Formal Verification Technology Fits into the Cadence Flow

- Why Cadence Bought Jasper—A New Era in Formal Analysis

- Q&A: An R&D Perspective on Formal Verification—Past, Present and Future

There has been so much hype about the “Internet of Things” (IoT) that it is refreshing to hear about a cutting-edge development project that can bring concrete benefits to millions of people. That project is the ongoing development of the Google Smart Contact Lens, and it was detailed in a keynote speech June 8 at the Design Automation Conference (DAC 2015).

The keynote speech was given by Brian Otis (right), a director at Google and a research associate professor at the University of Washington. The “smart lens” that the project envisions is essentially a disposable contact lens that fits on an eye and continuously monitors blood glucose levels. This is valuable information for anyone who has, or may someday have, diabetes.

Since he was speaking to an engineering audience, Otis focused on the challenges behind building such a device, and described some of the strategies taken by Google and its partner, Novartis. The project required new approaches to miniaturization, low-power design, and connectivity, as well as a comfortable and reliable silicon-to-human interface. Otis discussed the “why” as well and showed how the device could potentially save or improve millions of lives.

Millions of Users

First, a bit of background. Google announced the smart lens project in a blog post in January 2014. Since then it has been featured in news outlets including Forbes, Time, and the Wall Street Journal. In March 2015, Time reported that Google has been granted a patent for a smart contact lens.

The smart lens monitors the level of blood glucose by looking at its concentration in tears. The lens includes a wireless system on chip (SoC) and a miniaturized glucose sensor. A tiny pinhole in the lens allows tear fluid to seep into the sensor, and a wireless antenna handles communications to the wireless devices.

“We figure that if we can solve a huge problem, it is probably worth doing,” Otis said. “Diabetes is one example.” He noted 382 million people worldwide have diabetes today, and that 35% of the U.S. population may be pre-diabetic. Today, diabetics must *** their fingers to test blood glucose levels, a procedure that is invasive, painful, and subject to infrequent monitoring.

According to Otis, the smart contact lens represents a “new category of wearable devices that are comfortable, inexpensive, and empowering.” The lens does sensor data logging and uses a portable instrument to measure glucose levels. It is thin, cheap, and disposable, he said.

Moreover, the lens is not just for people already diagnosed with diabetes—it’s for anyone who is pre-diabetic, or may be at risk due to genetic predisposition. “If we are pro-active rather than re-active,” Otis said, “Instead of waiting until a person has full-fledged diabetes, we could make a huge difference in peoples’ lives and lower the costs of treating them.”

Technical Challenges

No one has built anything quite like the smart lens, so researchers at Google and Novartis are treading new ground. Otis identified three key challenges:

• Miniaturization: Everything must be really small—the SoC, the passive components, the power supply. Components must be flexible and cheap, and support thin-film integration.
• Platform: Google has developed a reusable platform that includes tiny, always-on wireless sensors, ultra low-power components, and standards-based interfaces.
• Data: Researchers are looking for the best ways to get the resulting data into a mobile device and onto the cloud.

Comfort is another concern. “This is not intended to be for the most severe cases,” Otis said. “This is intended to be for all of us as a pro-active way of improving our lifestyles.”

The platform provides a bidirectional encrypted wireless link, integrated power management, on-chip memory, standards-based RFID link, flexible sensor interface, high-resolution potentiostat sensor, and decoupling capacitors. Most of these capabilities are provided by the standard CMOS SoC, which is a couple hundred microns on a side and only “tens of microns” thick.

Otis noted that unpackaged ICs are typically 250 microns thick when they come back from the foundry. Thus, post-processing is needed so the IC will fit into a contact lens.

Furthermore, the design requires precision analog circuitry and additional environmental sensors. “Some of this stuff sounds mundane but it is really hard, especially when you find out you can’t throw large decoupling capacitors and bypass capacitors onto a board, and all that has to be re-integrated into the chip,” Otis said.

Sensor Challenges

Getting information from the human body is challenging. The smart lens sensor does a direct chemical measurement on the surface of the eye. The sensor is designed to work with very low glucose concentrations. This is because the concentration of glucose in tears is an order of magnitude lower than it is in blood.

In brief, the sensor has two parallel plates that are coated with an enzyme that converts glucose into hydrogen peroxide, which flows around the electrodes of the sensor. This is actually a fairly standard way of doing glucose monitoring. However, the smart lens sensor has two electrodes compared to the typical three.

In manufacturing, it is essential to keep costs low. Otis outlined a three-step manufacturing process:

• Start with the bottom layer, and mold a contact lens in the way you typically would.
• Add the electronics package on top of that layer.
• Build a second layer that encapsulates the electronics and provides the curvature needed for comfort and vision correction.

Beyond the technical challenges are the “clinical” challenges of working with human beings. The human body “is messy and very variable,” Otis said. This variability affects sensor performance and calibration, RF/electro-magnetic performance, system reliability, and comfort.

The final step is making use of the data. “We need to get the data from the device into a phone, and then display it so users can visualize the data,” Otis said. This provides “actionable feedback” to the person who needs it. Eventually, the data will need to be stored in the cloud.

As he concluded his talk, Otis noted that the platform his group developed may have many applications beyond glucose monitoring. “There is a lot you can do with a bunch of logic and sensing capability,” he said, “and there are hundreds of biomarkers beyond glucose.” Clearly this will be an interesting technology to watch.

Richard Goering

Related Blog Post

- Gary Smith at DAC 2015: How EDA Can Expand Into New Directions

HI, I have been using the Innovus GUI commands for several things and wonder if those command can be written to a log or cmd file so I can use it in my flow script? Is there such options that we can set?

Thanks

Hi All,

I have 1 huge project(day X) which has different reference power supply designs.

Now I start a new project and I require 1 specific reference power supply from X.

What is the easist way to do this, other than a copy paste.

Is there a way to create say symbols or something similar, so that multiple different people could use it if they need, in their projects

Thanks for your help and suggestions.