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Dominican Peso(DOP)/Nicaraguan Cordoba Oro(NIO)

1 Dominican Peso = 0.6251 Nicaraguan Cordoba Oro




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Dominican Peso(DOP)/Costa Rican Colon(CRC)

1 Dominican Peso = 10.3367 Costa Rican Colon




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Dominican Peso(DOP)/Colombian Peso(COP)

1 Dominican Peso = 70.7935 Colombian Peso




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[Men's Outdoor Track & Field] Indian Track & Field Competes at Northwest Open

Two Haskell men finish fourth, while one Indian woman places sixth




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[Men's Outdoor Track & Field] Men's Track & Field Team Earn a Third Place Conference Finish

Thomas Zunie, a junior from Zuni, NM takes first in the Men's 5000 meter run in a time of 17:21.41.  Zunie's finish in the 5000 garnered him a First Team All-Conference.  Zunie also earned a third place in the 1500 meter run with a time of 4:33.77.   




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[Men's Outdoor Track & Field] Track and Field shines in second meet of the Outdoor Season

Last week the weather disrupted the Indians as they opened the Outdoor Season at Pittsburg State University.  Thunderstorms and lightning prevented numerous races and events from running on schedule.  For many, the meet yesterday was their opportunity to finally compete.

 




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Papua New Guinean Kina(PGK)/Salvadoran Colon(SVC)

1 Papua New Guinean Kina = 2.5512 Salvadoran Colon



  • Papua New Guinean Kina

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Papua New Guinean Kina(PGK)/Nicaraguan Cordoba Oro(NIO)

1 Papua New Guinean Kina = 10.0291 Nicaraguan Cordoba Oro



  • Papua New Guinean Kina

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Papua New Guinean Kina(PGK)/Costa Rican Colon(CRC)

1 Papua New Guinean Kina = 165.8525 Costa Rican Colon



  • Papua New Guinean Kina

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Papua New Guinean Kina(PGK)/Colombian Peso(COP)

1 Papua New Guinean Kina = 1135.88 Colombian Peso



  • Papua New Guinean Kina

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Brunei Dollar(BND)/Salvadoran Colon(SVC)

1 Brunei Dollar = 6.1925 Salvadoran Colon




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Brunei Dollar(BND)/Nicaraguan Cordoba Oro(NIO)

1 Brunei Dollar = 24.3435 Nicaraguan Cordoba Oro




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Brunei Dollar(BND)/Costa Rican Colon(CRC)

1 Brunei Dollar = 402.5707 Costa Rican Colon




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Brunei Dollar(BND)/Colombian Peso(COP)

1 Brunei Dollar = 2757.1006 Colombian Peso




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[Men's Basketball] Central Christian College Men's Basketball Falls Short to Haskell

Final Score: 71-53




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[Men's Basketball] Fightin' Indians Fall Short on the Road to the Falcons




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[Men's Basketball] Men's Basketball Prepares for Game Against Nebraska Christian College




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[Men's Basketball] Haskell Men's Basketball Defeat Nebraska Christian College




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[Men's Basketball] Men's Basketball Advances to Conference Tournament as No.6 Seed




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[Men's Basketball] A.I.I. Men's Basketball Conference Banquet News Release




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[Men's Basketball] Loss to No.3 Seed Lincoln College Ends Men's Basketballs Post Season Play




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[Men's Basketball] Men's Basketball Athletes Rack Up Records on Statistics Board In Coffin ...




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How to Verify Performance of Complex Interconnect-Based Designs?

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




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PCI-SIG DevCon 2019 APAC Tour: All Around Latest Spec Updates and Solution Offering

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




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USB3, PCIe, DisplayPort Protocol Traffic Finding its Way Through USB4 Routers

USB4 can simultaneously tunnel USB3, PCIe and DisplayPort native protocol traffic through a hierarchy of USB4 routers. The key to tunneling of these protocols is routing table programmed at each ingress adapter. An entry of a routing table maps an incoming HopID, called Input/Ingress HopID to a corresponding pair of Output/Egress Adapter and Egress/Output HopID.

The responsibility of programming routing tables lies with the Connection Manager. Connection Manager, having the complete view of the hierarchy of the routers, programs the routing tables at all relevant adapter ports. Accordingly, the USB3, PCIe and DisplayPort protocol tunneled packets are routed, and reach their respective intended destinations.

The diagrammatic representation below is an example of tunneling of USB3 protocol traffic from USB4 Host Router to USB4 Peripheral Device Router through a USB4 Hub Router. The path from USB3 Host to USB3 Device is depicted by routing tables indicated at A -> B -> C -> D, and the one from USB3 Device to USB3 Host by routing tables indicated at E -> F -> G -> H . Note that the Input HopID from and Output HopID to all three protocol adapters for USB3, PCIe and DisplayPort Aux traffic, are fixed as 8, and for DisplayPort Main Link traffic are fixed as 9.

Once the native protocol traffic come into the transport layer of a USB4 router, the transport layer of it does not know to which native protocol a tunneled packet belongs to. The only way a transport layer tunneled packet is routed through the hierarchy of the routers is using the HopID values and the information programmed in the routing tables.

The figure below shows an example of tunneling of all the three USB3, PCIe and DisplayPort protocol traffic together. The transport layer tunneled packets of each of these native protocols are transported simultaneously through the routers hierarchy.

 Cadence has a mature Verification IP solution for the verification of USB3, PCIe and DisplayPort tunneling. This solution also employs the industry proven VIPs of each of these native protocols for native USB3, PCIe and DisplayPort traffic.




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Snogworthy jams + social commentary

Once while eating dinner in Montreal, our friendly, intoxicated waitress plopped herself in my lap and proceeded to tell us about how obsessed she was with the CD that was playing - singing out the lyrics at an ungodly volume and flinging her arms about. Wow, I thought to myself, people who listen to Morcheeba sure seem to have a lot of fun, and promised to check them out.

Several CDs later, they are firmly one of my favorites. And their trip hop meditation, 2003’s Charango remains one of my most played CDs.

Morcheeba (Mor = more, Cheeba = pot) are brothers Ross and Paul Godfrey with singer Skye Edwards (who has since been replaced). Part trance, part ambience, Charango is full of smooth, snogworthy jams. And just as you surrender to its seductive groove, Slick Rick shows up with a rap called “Women Lose Weight”.

Lamenting his wife putting on weight after having kids and stalled by his mistress who wants a clean break before she shacks up with him, he decides the easiest way out of it all is to kill the spouse. Considering different ways to do the deed, he finally rams his car into her Chevy over a long lunch break one fine day. It is an unexpected, stunning, tongue-in-cheek social commentary that makes it a CD you won’t forget easily.

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




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Here Is Why the Indian Voter Is Saddled With Bad Economics

This is the 15th installment of The Rationalist, my column for the Times of India.

It’s election season, and promises are raining down on voters like rose petals on naïve newlyweds. Earlier this week, the Congress party announced a minimum income guarantee for the poor. This Friday, the Modi government released a budget full of sops. As the days go by, the promises will get bolder, and you might feel important that so much attention is being given to you. Well, the joke is on you.

Every election, HL Mencken once said, is “an advance auction sale of stolen goods.” A bunch of competing mafias fight to rule over you for the next five years. You decide who wins, on the basis of who can bribe you better with your own money. This is an absurd situation, which I tried to express in a limerick I wrote for this page a couple of years ago:

POLITICS: A neta who loves currency notes/ Told me what his line of work denotes./ ‘It is kind of funny./ We steal people’s money/And use some of it to buy their votes.’

We’re the dupes here, and we pay far more to keep this circus going than this circus costs. It would be okay if the parties, once they came to power, provided good governance. But voters have given up on that, and now only want patronage and handouts. That leads to one of the biggest problems in Indian politics: We are stuck in an equilibrium where all good politics is bad economics, and vice versa.

For example, the minimum guarantee for the poor is good politics, because the optics are great. It’s basically Garibi Hatao: that slogan made Indira Gandhi a political juggernaut in the 1970s, at the same time that she unleashed a series of economic policies that kept millions of people in garibi for decades longer than they should have been.

This time, the Congress has released no details, and keeping it vague makes sense because I find it hard to see how it can make economic sense. Depending on how they define ‘poor’, how much income they offer and what the cost is, the plan will either be ineffective or unworkable.

The Modi government’s interim budget announced a handout for poor farmers that seemed rather pointless. Given our agricultural distress, offering a poor farmer 500 bucks a month seems almost like mockery.

Such condescending handouts solve nothing. The poor want jobs and opportunities. Those come with growth, which requires structural reforms. Structural reforms don’t sound sexy as election promises. Handouts do.

A classic example is farm loan waivers. We have reached a stage in our politics where every party has to promise them to assuage farmers, who are a strong vote bank everywhere. You can’t blame farmers for wanting them – they are a necessary anaesthetic. But no government has yet made a serious attempt at tackling the root causes of our agricultural crisis.

Why is it that Good Politics in India is always Bad Economics? Let me put forth some possible reasons. One, voters tend to think in zero-sum ways, as if the pie is fixed, and the only way to bring people out of poverty is to redistribute. The truth is that trade is a positive-sum game, and nations can only be lifted out of poverty when the whole pie grows. But this is unintuitive.

Two, Indian politics revolves around identity and patronage. The spoils of power are limited – that is indeed a zero-sum game – so you’re likely to vote for whoever can look after the interests of your in-group rather than care about the economy as a whole.

Three, voters tend to stay uninformed for good reasons, because of what Public Choice economists call Rational Ignorance. A single vote is unlikely to make a difference in an election, so why put in the effort to understand the nuances of economics and governance? Just ask, what is in it for me, and go with whatever seems to be the best answer.

Four, Politicians have a short-term horizon, geared towards winning the next election. A good policy that may take years to play out is unattractive. A policy that will win them votes in the short term is preferable.

Sadly, no Indian party has shown a willingness to aim for the long term. The Congress has produced new Gandhis, but not new ideas. And while the BJP did make some solid promises in 2014, they did not walk that talk, and have proved to be, as Arun Shourie once called them, UPA + Cow. Even the Congress is adopting the cow, in fact, so maybe the BJP will add Temple to that mix?

Benjamin Franklin once said, “Democracy is two wolves and a lamb voting on what to have for lunch.” This election season, my friends, the people of India are on the menu. You have been deveined and deboned, marinated with rhetoric, seasoned with narrative – now enter the oven and vote.



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




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DAC 2015: Google Smart Contact Lens Project Stretches Limits of IC Design

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




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DAC 2015: Lip-Bu Tan, Cadence CEO, Sees Profound Changes in Semiconductors and EDA

As a leading venture capitalist in the electronics technology, as well as CEO of Cadence, Lip-Bu Tan has unique insights into ongoing changes that will impact EDA providers and users. Tan shared some of those insights in a “fireside chat” with Ed Sperling, editor in chief of Semiconductor Engineering, at the Design Automation Conference (DAC 2015) on June 9.

Topics of this discussion included industry consolidation, the need for more talent and more startups, Internet of Things (IoT) opportunities and challenges, the shift from ICs to full product development, and the challenges of advanced nodes. Following are some excerpts from this conversation, held at the DAC Pavilion theater on the exhibit floor.

 

Ed Sperling (left) and Lip-Bu Tan (right) discuss trends in semiconductors and EDA

Q: As you look out over the semiconductor and EDA industries these days, what worries you most?

Tan: At the top of my list is all the consolidation that is going on. Secondly, chip design complexity is increasing substantially. Time-to-market pressure is growing and advanced nodes have challenges.

The other thing I worry about is that we need to have more startups. There’s a lot of innovation that needs to happen. And this industry needs more top talent. At Cadence, we have a program to recruit over 10% of new hires every year from college graduates. We need new blood and new ideas.

Q: EDA vendors were acquiring companies for many years, but now the startups are pretty much gone. Where does the next wave of innovation come from?

Tan: I’ve been an EDA CEO for the last seven years and I really enjoy it because so much innovation is needed. System providers have very big challenges and very different needs. You have to find the opportunities and go out and provide the solutions.

The opportunities are not just in basic tools. Massive parallelism is critical, and the power challenge is huge. Time to market is critical, and for the IoT companies, cost is going to be critical. If you want to take on some good engineering challenges, this is the most exciting time.

Q: You live two lives—you’re a CEO but you’re also an investor. Where are the investments going these days and where are we likely to see new startups?

Tan: Clearly everybody is chasing the IoT. There is a lot of opportunity in the cloud, in the data center. Also, I’m a big believer in video, so I back companies that are video related. A big area is automotive. ADAS [Advanced Driver Assistance Systems] is a tremendous opportunity.

These companies can help us understand how the industry is transforming, and then we can provide solutions, either in terms of IP, tools, or the PCB. Then we need to connect from the system level down to semiconductors. I think it’s a different way to design.

Q: What happens as we start moving from companies looking to design a semiconductor to system companies who are doing things from the perspective that we have this purpose for our software?

Tan: We are extending from EDA to what we call system design enablement, and we are becoming more application driven. The application at the system level will drive the silicon design. We need to help companies look at the whole system including the power envelope and signal integrity. You don’t want to be in a position where you design a chip all the way to fabrication and then find the power is too high.

We help the customers with hardware/software co-design and co-verification. We have a design suite and a verification suite that can provide customers with high-level abstractions, as well as verify IP blocks at the system level. Then we can break things down to the component level with system constraints in mind, and drive power-aware, system-aware design.

We are starting to move into vertical markets. For example, medical is a tremendous opportunity.

Q: How does this approach change what you provide to customers?

Tan: Every year I spend time meeting with customers. I think it is very important to understand what they are trying to design, and it is also important to know the customer’s customer requirements. We might say, “Wait a minute, for this design you may want to think about power or the library you’re using.” We help them understand what foundry they should use and what process they should use. They don’t view me as a vendorthey view me as a partner.

We also work very closely with our IP and foundry partners. We work as one teamthe ultimate goal is customer success.

Q: Is everybody going to say, FinFETs are beautiful, we’re going to go down to 10nm or 7nmor is it a smaller number of companies who will continue down that path?

Tan: Some of the analog/mixed-signal companies don’t need to go that far. We love those customerswe have close to 50% of that business. But we also have customers in the graphics or processor area who are really pushing the envelope, and need to be in 16nm, 14nm, or 10nm. We work very closely with those guys to make sure they can go into FinFETs.

We always want to work with the customer to make sure they have a first-time silicon success. If you have to do a re-spin, you miss the opportunity and it’s very costly.

Q: There’s a new market that is starting to explodeIoT. How real is that world to you? Everyone talks about large numbers, but is it showing up in terms of tools?

Tan: Everybody is talking about huge profits, but a lot of the time I think it is just connecting old devices that you have. Billions of units, absolutely yes, but if you look close enough the silicon percentage of that revenue is very tiny. A lot of the profit is on the service side. So you really need to look at the service killer app you are trying to provide.

What’s most important to us in the IoT market is the IP business. That’s why we bought Tensilicait’s programmable, so you can find the killer app more quickly. The other challenges are time to market, low power, and low cost.

Q: Where is system design enablement going? Does it expand outside the traditional market for EDA?

Tan: It’s not just about tools. IP is now 11% of our revenue. At the PCB level, we acquired a company called Sigrity, and through that we are able to drive system analysis for power, signal integrity, and thermal. And then we look at some of the verticals and provide modeling all the way from the system level to the component level. We make sure that we provide a solution to the end customer, rather than something piecemeal.

Q: What do you think DAC will look like in five years?

Tan: It’s getting smaller. We need to see more startups and innovative IP solutions. I saw a few here this year, and that’s good. We need to encourage small startups.

Q: Where do we get the people to pull this off? I don’t see too many people coming into EDA.

Tan: I talk to a lot of university students, and I tell them that this small industry is a gold mine. A lot of innovation is needed. We need them to come in [to EDA] rather than join Google or Facebook. Those are great companies, but there is a lot of fundamental physical innovation we need.

Richard Goering

Related Blog Posts

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

DAC 2015: Google Smart Contact Lens Project Stretches Limits of IC Design

Q&A with Nimish Modi: Going Beyond Traditional EDA




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DAC 2015: How Academia and Industry Collaboration Can Revitalize EDA

Let’s face it – the EDA industry needs new people and new ideas. One of the best places to find both is academia, and a presentation at the Cadence Theater at the recent Design Automation Conference (DAC 2015) described collaboration models that are working today.

The presentation was titled “Industry/Academia Engagement Models – From PhD Contests to R&D Collaborations.” It included these speakers, shown from left to right in the photo below:

  • Prof. Xin Li, Electrical and Computer Engineering, Carnegie-Mellon University (CMU)
  • Chuck Alpert, Senior Software Architect, Cadence
  • Prof. Laleh Behjat, Department of Electrical and Computer Engineering, University of Calgary

 

Alpert, who was filling in for Zhuo Li, Software Architect at Cadence, was the vice chair of DAC 2015 and will be the general chair of DAC 2016 in Austin, Texas. “My team at Cadence really likes to collaborate with universities,” he said. “We’re a big proponent of education because we really need the best and brightest students in our industry.”

Contests Boost EDA Research

One way that Cadence collaborates with academia is participation in contests. “It’s a great way to formulate problems to academia,” Alpert said. “We can have the universities work on these problems and get some strategic direction.”

For example, Cadence has been involved with the annual CAD contest at the International Conference on Computer-Aided Design (ICCAD) since the contest was launched in 2012. This is the largest worldwide EDA R&D contest, and it is sponsored by the IEEE Council on EDA (CEDA) and the Taiwan Ministry of Education. Its goals are to boost EDA research in advanced real-world problems and to foster industry-academia collaboration.

Contestants can participate in one of more problems in the three areas of system design, logic synthesis and verification, and physical design. The 2015 contest has attracted 112 teams from 12 regions. Cadence contributes one problem per year in the logic synthesis area. Zhuo Li was the 2012 co-chair and the 2013 chair. The awards will be given at ICCAD in November 2015.

Another step that Cadence has taken, Alpert said, is to “hire lots of interns.” His own team has four interns at the moment. One advantage to interning at Cadence, he said, is that students get to see real-world designs and understand how the tools work. “It helps you drive your research in a more practical and useful direction,” he said.

The Cadence Academic Network co-sponsors the ACM SIGDA PhD Forum at DAC, and Xin Li and Zhuo Li are on the organizing committee. This event is a poster session for PhD students to present and discuss their dissertation research with people in the EDA community. This year’s forum was “packed,” Alpert said, and it’s clear that the event needs a bigger room.

Finally, Alpert noted, Cadence researchers write and publish technical papers at DAC and other conferences, and Cadence people serve on the DAC technical program committee. “We try to be involved with the academic community on a regular basis,” Alpert said. “We want the best and the brightest people to go into EDA because there is still so much innovation that’s needed. It’s a really cool place to be.”

Research Collaboration Exposes Failure Rates

Xin Li presented an example of a successful research collaboration between CMU and Cadence. The challenge was to find a better way to estimate potential failure rates in memory. As noted in a previous blog post, PhD student Shupeng Sun met this challenge with a new statistical methodology that won a Best Poster award at the ACM SIGDA PhD Forum at DAC 2014.

The new methodology is called Scaled-Sigma Sampling (SSS). It calculates the failure rate and accounts for variability in the manufacturing process while only requiring a few hundred, or a few thousand, sample circuit blocks. Previously, millions of samples were required for an accurate validation of a new design, and each sample could take minutes or hours to simulate. It could take a few weeks or months to run one validation.

The SSS methodology requires greatly reduced simulation times. It makes it possible, Li noted, to run simulations overnight and see the results in the morning.

Li shared his secret for success in collaborations. “I want to emphasize that before the collaboration, you have to understand the goal. If you don’t have a clear goal, don’t collaborate. Once you define the goal, stick to it and make it happen.”

Contest Provides Learning Experience

Last year Laleh Behjat handed two of her new PhD students a challenge. “I told them there is an ISPD [International Symposium for Physical Design] contest on placement, and I expect you to participate and I expect you to win. Not knowing anything about placement, I don’t think they realized what I was asking them.”

The 2015 contest was called the Blockage-Aware Detailed Routing-Driven Placement Contest. Results were announced at the end of March at ISPD. And the University of Calgary team, despite its lack of placement experience, took second place.

Such contests provide a good learning tool, according to Behjat. Graduate students in EDA, she said, “have to be good programmers. They have to work in teams and be collaborative, be able to innovate, and solve the hardest problems I have seen in engineering and science. And they have to think outside the box.” A contest can bring out all these attributes, she said.

Further, Behjat noted, contest participants had access to benchmarks and to a placement tool. They didn’t have to write tools to find out if their results were good. Industry sponsors, meanwhile, got access to good students and new approaches for solving problems.

“You can see Cadence putting a big amount of time, effort and money to get students here and get them excited about doing contests,” she said. She advised students in the theater audience to “talk to people in the Cadence booth and see if you can have more ideas for collaboration.”

Richard Goering

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BSIM-CMG FinFET Model – How Academia and Industry Empowered the Next Transistor




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EDA Retrospective: 30+ Years of Highlights and Lowlights, and What Comes Next

In 1985, as a relatively new editor at Computer Design magazine, I was asked to go forth and cover a new business called CAE (computer-aided engineering). I knew nothing about it, but I had been writing about design for test, so there seemed to be somewhat of a connection. Little did I know that “CAE” would turn into “EDA” and that I’d write about it for the next 30 years, for Computer Design, EE Times, Cadence, and a few others.

Now that I’m about to retire, I’m looking back over those 30 years. What a ride it has been! By the numbers I covered 31 Design Automation Conferences (DACs), hundreds of new products, dozens of acquisitions and startups, dozens of lawsuits, and some blind alleys that didn’t work out (like “silicon compilation”). Chip design went from gate arrays and PLDs with a few thousand gates to processors and SoCs with billions of transistors.

In 1985 there were three big CAE vendors – Daisy Systems, Mentor Graphics, and Valid Logic. All sold bundled packages that included workstations and CAE software; in fact, Daisy and Valid designed and manufactured their own workstations. In the early 1980s a workstation with schematic capture and gate-level logic simulation might have set you back $120,000. In 1985 OrCAD, now part of Cadence, came out with a $500 schematic capture package running on IBM PCs.

Cadence and Synopsys emerged in the late 1980s, and by the 1990s the EDA industry was pretty much a software-only business (apart from specialized machines like simulation accelerators). Since the early 1990s the “big three” EDA vendors have been Cadence, Synopsys, and Mentor, giving the industry stability but allowing for competition and innovation.

Here, in my view, are some of the highlights that occurred during the past 30 years of EDA.

EDA is a Highlight

The biggest highlight in EDA is the existence of a commercial EDA industry! Marching hand in hand with the fabless semiconductor revolution, commercial EDA made it possible for hundreds of companies to design semiconductors, as opposed to a small handful that could afford large internal CAD operations and fabs. With hundreds of semiconductor companies as opposed to a half-dozen, there’s a lot more creativity, and you get the level of sophistication and intelligence that you see in your smartphone, video camera, tablet, gaming console, and car today.

CAE + CAD = EDA. This is not just a terminology issue. By the mid-1980s it became clear that front-end design (CAE) and physical design (CAD) belonged together. The big CAE vendors got involved in IC and PCB CAD, and presented increasingly integrated solutions. People got tired of writing “CAE/CAD” and “EDA” was born.

The move from gate-level design to RTL. This move happened around 1990, and in my view this is EDA’s primary technology success story during the past 30 years. Moving up in abstraction made the design and verification of much larger chips possible. Going from gate-level schematics to a hardware description language (HDL) revolutionized logic design and verification. Which would you rather do – draw all the gates that form an adder, or write a few lines of code and let a synthesis tool find an adder in your chosen technology?

Two developments made this shift in design possible. One was the emergence of commercial RTL synthesis (or “logic synthesis”) tools from Synopsys and other companies, which happened around 1990. Another was the availability of Verilog, developed by Gateway Design Automation and purchased by Cadence in 1989, as a standard RTL HDL. Although most EDA vendors at the time were pushing VHDL, designers wanted Verilog and that’s what most still use (with SystemVerilog coming on strong in the verification space).

IC functional verification underwent huge changes in the late 1990s and early 2000s, largely due to new technology developed by Verisity, which was acquired by Cadence in 2005. Before Verisity, verification engineers were writing and running directed tests in an ad-hoc manner. Verisity introduced or improved technologies such as pseudo-random test generation, coverage metrics, reusable verification IP, and semi-automated verification planning. The Verisity “e” language became a widely used hardware verification language (HVL).

The biggest way that EDA has expanded its focus has been through semiconductor IP. Today Synopsys and Cadence are leading providers in this area. Thanks to the availability of design and verification IP, many SoC designs today reuse as much as 80% of previous content. This makes it much, much faster to design the remaining portion. While IP began with fairly simple elements, today commercially available IP can include whole subsystems along with the software that runs on them. With IP, EDA vendors are providing not only design tools but design content.

Finally, the EDA industry has done an amazing job of keeping up with SoC complexity and with advanced process nodes. Thanks to intense and early collaboration between foundries, IP, and EDA providers, tools and IP have been ready for process nodes going down to 10nm.

Where Does ESL Fit?

In some ways, electronic system level (ESL) design is both a lowlight and a highlight. It’s a lowlight because people have been talking about it for 30 years and the acceptance and adoption have come very slowly. ESL is a highlight because it’s finally starting to happen, and its impact on design and verification flows could be dramatic. Still, ESL is vaguely defined and can be used to describe almost anything that happens at a higher abstraction level than RTL.

High-level synthesis (HLS) is an ESL technology that is seeing increasing use in production environments. Current HLS tools are not restricted to datapaths, and they produce RTL code that gives better quality of results than hand-written RTL. Another ESL methodology that’s catching on is virtual prototyping, which lets software developers write software pre-silicon using SystemC models. Both HLS and virtual prototyping are made possible by the standardization of SystemC and transaction-level modeling (TLM). However, it’s still not easy to use the same SystemC code for HLS and virtual prototyping.

And Now, Some Lowlights

Every new industry has some twists and turns, and EDA is no exception. For example, the EDA industry in the 1980s and 1990s sparked a lot of lawsuits. At EE Times my colleagues and I wrote a number of articles about EDA legal disputes, mostly about intellectual property, trade secrets, or patent issues. Over the past decade, fortunately, there have been far fewer EDA lawsuits than we had before the turn of the century.

Another issue that was troublesome in the 1980s and 1990s was so-called “standards wars.” These would occur as EDA vendors picked one side or the other in a standards dispute. For example, power intent formats were a point of conflict in the early 2000s, but the Common Power Format (CPF) and the Unified Power Format (UPF) are on the road to convergence today with the IEEE 1801 effort. As mentioned previously, Verilog and VHDL were competing for adoption in the early 1990s. For the most part, Verilog won, showing that the designer community makes the final decision about which standards will be used.

How on earth did there get to be something like 30 DFM (design for manufacturability) companies 10-12 years ago? To my knowledge, none of these companies are around today. A few were acquired, but most simply faded away. A lot of investors lost money. Today, VCs and angel investors are funding very few EDA or IP startups. There are fewer EDA startups than there used to be, and that’s too bad, because that’s where a lot of the innovation comes from.

Here’s another current lowlight -- not enough bright engineering or computer science students are joining EDA companies. They’re going to Google, Apple, Facebook, and the like. EDA is perceived as a mature industry that is still technically very difficult. We need to bring some excitement back into EDA.

Where Is EDA Headed?

Now we come to what you might call “headlights” and look at what’s coming. My list includes:

  • System Design Enablement. This term has been coined by Cadence to describe a focus on whole systems or end products including chips, packages, boards, embedded software, and mechanical components. There are far more systems companies than semiconductor companies, leaving a large untapped market that’s looking for solutions.
  • New frontiers for EDA. At a 2015 Design Automation Conference speech, analyst Gary Smith suggested that EDA can move into markets such as embedded software, mechanical CAD, biomedical, optics, and more.
  • Vertical markets. EDA has until now been “horizontal,” providing the same solution for all market segments. Going forward, markets like consumer, automotive, and industrial will have differing needs and will need optimized tools and IP.
  • Internet of Things. This is a current buzzword, but the impact on EDA remains uncertain. Many IoT devices will be heavily analog, use mature process nodes, and be dirt cheap. Lip-Bu Tan, Cadence CEO, recently pointed out that the silicon percentage of IoT revenue will be small and that a lot of the profits will be on the service side.

Moving On

For the past six years I’ve been writing the Industry Insights blog at Cadence.com. All things change, and with this post comes a farewell – I am retiring in late June and will be pursuing a variety of interests other than EDA. I’ll be watching, though, to see what happens next in this small but vital industry. Thanks for reading!

Richard Goering

 




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Special Route not connecting to Power Rings

Hi,

I'm a newbie and I'm working on a mixed-signal chip in Innovus. I've got a few analog LEF files that I've imported into my floorplan as macros.

My chip has got two power domains - VCC and VBAT.

One of the macro in the VBAT domain uses VBAT and GND as power rails myloweslife.com.

On doing Special-Route, I've got a lot of minute power rails for the standard cells, as expected.

But, the VBAT power rails are not getting extended till the outer power rings. Only the GND rails are correctly getting extended till the outer power rings.

A screen shot is attached for reference.

Thanks for any help




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Special Route not connecting to Power Rings

Hi,

I'm a newbie and I'm working on a mixed-signal chip in Innovus. I've got a few analog LEF files that I've imported into my floorplan as macros.

My chip has got two power domains - VCC and VBAT.

One of the macro in the VBAT domain uses VBAT and GND as power rails KrogerFeedback.com.

On doing Special-Route, I've got a lot of minute power rails for the standard cells, as expected.

But, the VBAT power rails are not getting extended till the outer power rings. Only the GND rails are correctly getting extended till the outer power rings.

A screen shot is attached for reference.

Thanks for any help




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Cadence SoC Encounter 8.1 - Keyboard is not working

Hello, I am using Encounter 8.1. My mouse is working fine, but my keyboard is not working well in Encounter. I can type in some boxes, but in many boxes I cannot type. The binding key is also not responding. How do I fix this issue? Thanks.




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Innovus Stylus Common UI

How can I make innovus start with common UI instead of legacy? When I launch Innovus with command "innovus", I get the legacy UI. I have Innovus version 17.11 installed. 

Thanks in advance.




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Verilog Code to Custom IC Layout generation

Hello everyone,

I am Vinay and I am currently developing some digital circuits for my chip design for my master's thesis at University at Buffalo.

I am fairly very new to Verilog and I don't seem to follow some of the things others find very easy.

Following are the things that I want to do to which I have no clue:

1. Develop certain arithmetic functionality in Verilog

2. Generate netlist for the verilog code

3. Feed the netlist file to Cadence encounter to be able to generate Digital Circuits' layout for my chip

I can use Cadence Virtuoso and Encounter for this but I don't know the exact procedure to get this done.

Could someone please describe the detailed process for doing the things mentioned above.

Thank you.




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About modus design constraints

Hi! 

In my design, there is an one hold violation on scan path, test data is corrupted during scan cycles (when i run verilog simulation of test vectors). I created constraint 'falsepath' to 'TI' input of violated flop and load it into Modus, but this does not have effect.

Can enyone explain to me, does 'falsepath' constraint affects scan path (from Q to TI/SI input, i.e. during SCAN procedure) or this constraint is only for functional mode (ie affects TEST cycle only - to 'D' input)?

I hope resolve this problem this by using some modus design constraints or any other method.




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In power pins unconnected

Hi,

When I import the top level Verilog file generated by Genus into Virtuoso, the power pins are left unconnected. I tried different configurations in "Global Net Options" tab. However, nothing changed. 

The cell is imported with three views, namely functional, schematic, and symbol. In www krogerfeedback com functional view everything looks OK, that is the top level Verilog file. In schematic, I can see the digital cells but VDD and VSS pins of the blocks are not connected. In the symbol view there are no pins for VDD and VSS. 

On top, we are trying to implement a digital block into Virtuoso. The technology is TSMC 65nm. On Genus and Innovus, everything goes straight and layout is generated successfully.

Thanks.




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How to write Innovus Gui command to a cmd/log file?

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




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checkRoute or VerifyConnectivity

Hello Everyone,

I was finishing the layout via Innovus and ran verifyConnectivity followed by checkRoute.

verifyConnectivity was okay and it showed no errors and no warnings, whereas checkRoute showed there are 3 unrouted nets.

When i ran the checkRoute command again immediately, it showed no unrouted/unconnected nets.

Which of these commands should we trust or is this really unrouted nets issue?

Looking forward for a response, thanks in advance.

Regards,

Vijay




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Viewing RTL Code Coverage reports with XCELIUM

Hi,

There was tool available with INCISIV called imc to view the coverage reports.

The question is: How can we view the code coverage reports generated with XCELIUM? I think imc is not available with XCELIUM?

Thanks in advance.




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How to customize default_hdl_checks/rules in CCD conformal constraint designer

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.




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Force cell equivalence between same-footprint and same-functionality hard-macros in Conformal LEC

For a netlist vs. netlist LEC flow we have to solve the following problem:

- in the RTL code we replicate a large array of N x M all-identical hard-macros, let call them MACRO_A

- MACRO_A is pre-assembled in Innovus and contains digital parts and analog parts (bottom-up hierarchical flow)

- at top-level (full-chip) we instantiate this array of all-identical macros

- in the top-level place-and-route flow we perform ecoChangeCell to remaster the top row of this array with MACRO_B

- MACRO_B is just a copy of the original MACRO_A cell containing same pins position, same internal digital functionality and also same digital layout, only slight differences in one analog block inside the macro

- MACRO_A and MACRO_B have the same .lib file generated with the do_extract_model command at the end of the Innovus flow, they only differ in the name of the macro

- when performing post-synthesis netlist vs post-place-and-route we load .lib files of both macros in Conformal LEC

- the LEC flow fails because Conformal LEC sees only MACRO_A instantiated in the post-synthesis netlist and both MACRO_A and MACRO_B in the post-palce-and-route netlist

Since both digital functionality and STD cells layout are the same between MACRO_A and MACRO_B we don't want to keep track of this difference already at RTL stage, we just want to perform this ECO change in place-and-route and force Conformal to assume equivalence between MACRO_A and MACRO_B .

Basically what I'm searching for is something similar to the add_instance_equivalences Conformal command but that works between Golden and Revised designs on cell primitives/black-boxes .

Is this flow supported ?

Thanks in advance

Luca




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Multiple commands using ipcBeginProcess

Hi,

I am trying to use "sed -e 's " from SKILL code to edit unix file "FileA", to replace 3 words in the 2nd line.

How to run below multiple commands using  ipcBeginProcess, Should I use ipcWait or ipcCloseProcess ?

Using && to combine , will that work as I have to work serially on each command. ?

With below code only the first command gets executed. Please advise.

FileA="/user/tmp/text1.txt"

sprintf(Command1 "sed -e '2s/%s/%s/g' %s > %s" comment1 get(form concat("dComment" RDWn))->value FileA FileA)
cid = ipcBeginProcess(Command1)


sprintf(Command2 "sed -e '2s/%s/%s/g' %s > %s"  Time getCurrentTime() FileA FileA)
cid1 = ipcBeginProcess(Command2)


sprintf(Command3 "sed -e '2s/%s/%s/g' %s > %s"  comment2 get(form concat("Duser" RDWn))->value FileA FileA)
cid2 = ipcBeginProcess(Command3)

Thanks,

Ajay




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convert ircx to ict or emDataFile for Voltus-fi

Hi,

I want to convert ircx file(which is from TSMC,inclued EM Information) to ict or emDataFile for Voltus-fi.

I tried many way, but I can not make it. Can anyone give me some advice?

and I  do not installed QRC.

below is some tools installed my server. 

IC617-64b.500.21 is used.




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Select all members of a constraint with SKILL

I want to select a constraint, and then run a SKILL command that returns a list with the members of that constraint. Is this possible?

Thx,




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Displaying contents of a modeless dialog box during execution of a SKILL script

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




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Skill code to disable all callbacks

Can anybody assist with a Skill code /function to disable all callbacks




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Parasitic node coordinates

Howdy,

            In the netlist generated after parasitic extraction, nodes have been added at fracture points to add parasitic devices. For example, in the image below, I'm referring to the nodes IN#1 and IN#2. Is there a way to determine their co-ordinates relative to the layout co-ordinate system? I could not find them in the Skill command reference and when I query the parasitic elements in the extracted view, it gives the graphical pin locations of the elements rather than the physical.

Thanks

Audi




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When Arm meets Intel – Overcoming the Challenges of Merging Architectures on an SoC to Enable Machine Learning

As the stakes for winning server segment market share grow ever higher an increasing number of companies are seeking to grasp the latest Holy Grail of multi-chip coherence. The approach promises to better enable applications such as machine learning...(read more)