Nvidia

Jay Vleeschhouwer, managing director of Griffin Securities, has followed the EDA industry as a leading financial analyst for 25 years and is a popular speaker at the annual Design Automation Conference. Vleeschhouwer discusses his DAC presentation The State of EDA: A View from Wall Street.

Alameda, Calif.-based Verific Design Automation, a member of the ESD Alliance, made its name in the electronic system design and semiconductor industry supporting companies ranging from startups to billion-dollar industry leaders such as Synopsys, Cadence, Siemens EDA, Xilinx, Microchip, NVidia, Infineon, Qualcomm, Renesas and Samsung. Its software is used as the front end to design automation tools such as synthesis, simulation, debug, and formal verification. I spoke with Verific president and COO Michiel Ligthart about homegrown and open-source EDA tools and other recent trends in chip design. Smith: What trends are you seeing in chip design? Ligthart: Semiconductor companies are starting to build a portfolio of intellectual property, including homegrown electronic design automation (EDA) tools, that they want to keep secure and differentiated from their competitors. The increased interest in internally developed and supported EDA tools is a trend we started to see about two years ago. It’s not simulation, synthesis or place and route (P R). Instead, it’s pieces of a chip design flow optimized for a company’s specific needs. In the past, a semiconductor company would either standardize on one EDA company’s chip design flow or mix and match best-in-class tools from different vendors. The common denominator was that they used off-the-shelf products. If they had a specific requirement, they went to the EDA provider for assistance. In today’s competitive landscape, semiconductor companies are figuring out ways to diversify themselves and their design flow became a way to do so. They may not build their own P R tool, but they will look at building their own power domain approach, for example. Is this a widespread trend? It could be. We hear about it within end-user applications ranging from 5G and AI to data center processors and there are probably others we don’t hear about. Power optimization is an example of the kind of specific internal need being addressed. Smith: What are your thoughts about open-source EDA tools? Ligthart: Our industry supports open source already with language reference manuals (LRMs) for VHDL, SystemVerilog, Unified Power Format (UPF) and the RISC-V Instruction Set. The LRMs and the instruction set are free. Moving to the development of actual tools becomes a question of who will implement, support and maintain the tools. Implementation is expensive. The Big Three (Cadence, Siemens EDA and Synopsys) invest about 35 to 40% of top-line revenue into R D. For smaller EDA companies, this number is even higher. The industry may come up with a business model that will have open-source components as well as a way to fairly reimburse companies that make these tools freely available. I have not seen it yet. Smith: Business Insider reports that Verilog HDL is among the top 10 tech skills that companies are desperate for their employees to learn right. Does Verific get asked about Verilog training? Ligthart: No. Our customers are experienced users. Nonetheless, it was great to read that article and it suggests the semiconductor industry is healthy, growing and hiring talented engineers. Smith: If an entrepreneur asked you for advice about starting an EDA or IP company, what advice would you provide? Ligthart: I would tell the entrepreneur to focus on the problem the startup is solving. Stick to the company’s core competency and try not to build in-house what can be purchased from a reputable supplier. In the end, it will save time and jump-start the development effort, and the engineering budget can be allocated to the startup’s core competency. The external supplier presumably has years of product validation, which brings a major QA gain. About Michiel Ligthart Michiel Ligthart, president and COO of Verific Design Automation, has an extensive background in engineering, product marketing and general management. Prior to joining Verific, Ligthart was vice president and general manager of West Coast operations for Theseus Logic, a startup in asynchronous logic. Before that, he spent eight years with Exemplar Logic in engineering and marketing roles. Ligthart started his career with Philips Research Labs in California and was a visiting scholar at the Center for Integrated Systems at Stanford University. He has a Master of Science degree in Electrical Engineering from Delft University of Technology, the Netherlands. Robert (Bob) Smith is executive director of the ESD Alliance, a SEMI Technology Community.

Companies around the world are increasingly turning to mergers and acquisitions, research and development, and corporate venture capital (CVC) investment to sustain growth. For many years, global semiconductor companies including Intel, Qualcomm and Samsung have been active CVC investors. However, the economic fallout from the COVID-19 pandemic has forced many venture capital (VC) and CVC investors to rethink their investment strategies as they look to an uncertain future. To help provide SEMI members with the latest market trend information, SEMI Taiwan held the webinar Challenges and Opportunities in Corporate Venturing during the Global Pandemic Crisis on April 28th. Featured speaker James Mawson, founder and editor in chief of Global Corporate Venturing, provided an analysis of the pandemic’s impact on deal flow, capital movement, sentiment and strategies among CVCs. CVC takes larger role in past decadeCorporations have been increasingly active direct and indirect venture investors over the past decade. From 2011-2019, more than US$1.3 trillion of venture capital was invested globally, with corporations accounting for more than half that total, according to data from Pitchbook/GCV Analytics.Semiconductor companies that have been active in corporate venturing include Intel, Samsung, Nvidia, ARM, AMD, SK Hynix, Broadcom and Qualcomm. Pure-play semiconductor and chip companies tend to make few investments in their start-up counterparts because sector saturation of powerful incumbents leaves little opportunity for growth, James said. “While it is hard to find entrepreneurs wanting to be engaged in pure play S C, once they do, they can be very valuable and often be able to bring disruptive forces to the whole ecosystem,” James said.S C corporate investors focus on chip applicationsSemiconductor companies looking beyond pure-play S C start-ups for investment opportunities often target applications or developers that require the additional data, processing power, and memory their chips provide. “There is lots of interest by the big chip companies such as Intel, Qualcomm, and Samsung in developing some of those chip applications, getting them used more and creating a whole ecosystem,” James said.For example, Intel Capital, based on its data-centric theme, has focused on areas like autonomous vehicles, data centers and artificial intelligence (AI) because of the sheer amount of data and processing power they require. In another notable trend, non-traditional S C players such as Apple and Alibaba are leveraging investments in start-ups to develop their own chips for competitive advantage, James said.March deal flow down 20% With COVID-19 slowing the global economy, James expects semiconductor and chip companies to scale back direct investments this year due to rising pressure on their balance sheets. Deal flow in March was down roughly 20% from February.James is hopeful corporates will focus on investing in innovation over the long term rather than target share buybacks to boost near-term earnings. James pointed out that investors can uncover opportunities by identifying future problems to be solved in areas such as quantum computing, biotech, energy, healthcare, communications and ICT. Still, in the near term, where there is a crisis, there is opportunity. While the pandemic hit some sectors hard, it benefits start-ups in industries including gaming, education and telemedicine. This time is different?James said corporates need to rethink the investment model they want to follow. One option is the approach taken by General Electric, which divested its investment team and sold all its portfolio companies last year. Another is to focus on the long term. For example, Intel Capital has been dedicated to investments in innovation for nearly 30 years and continues to invest during downturns.Compared with the internet bubble and global financial crisis, today there are more experienced and mature CVCs that better know how to negotiate a crisis. James also pointed out investors are interested in backing CVCs with sector investing experience. There are now more than 600 CVCs with a 10-year-plus track record.James expects a variety of funding models to emerge over the next decade as pressure on corporate balance sheets encourages corporate investors to consider models that allow third-party capital to effectively leverage their CVC units. Corporate investors are also open to other ways to efficiently deliver financial returns.For more information about the SEMI Taiwan Corporate Growth and Innovation Community, please contact Irene Lin at [email protected]. For GCV’s latest news and event, visit its website.Jo-Ann Su is senior director of the Corporate Growth and Innovation Community at SEMI Taiwan.

New system-on-chip (SoC) devices are driving new memory architectures and photonic interfaces, while specialized new intellectual property (IP) requires analysis down to the nanometer and atomic levels because of single nanometer process nodes. According to Babak Taheri, CTO and EVP of products at Silvaco, a leading EDA Software, semiconductor IP company, a member of SEMI and the ESD Alliance, a SEMI Strategic Association Partner, design technology co-optimization and proven IP are required for this analysis.Taheri recently discussed atoms to systems in next-generation SoC designs with Nanette Collins ahead of ES Design West, co-located with SEMICON West, July 9-11 at the Moscone Center in San Francisco.ESD Alliance: For years now, the assumption is that each new chip design is more complex than the last. Why are the latest SoC designs even more complex than before?Taheri: New SoC devices for mobile phones, automobiles, intelligent edge nodes, big data compute and storage are adopting artificial intelligence and machine learning technologies. This is driving new compute, data flow, as well as memory architectures that are bandwidth-limited and some require photonic interfaces.One common denominator in present SoC design are the numerous blocks of IP. On average, over 85% of these blocks are reused. It’s cost-prohibitive to make these chips over and over again with new IP. According to some estimates, 90% of IP used in an SoC design by 2025 will be reused – only 10% is new technologies. That 10% is significant.ESD Alliance: How so?Taheri: Complex new technologies including flash memory, other advanced non-volatile memory technologies such as MRAM, RRAM and SoCs such as NVIDIA’s Xavier and Apple’s A12 use and reuse design IP at the architectural level.New technologies mean new materials and new processes. Single nanometer process nodes require specialized new IP that needs to be simulated and analyzed down to the nanometer and atomic levels.ESD Alliance: Does the atomic level changes the design equation?Taheri: Yes, it does. Designers need to be able to simulate at the atomic level and understand properties of these materials, and how they behave in at-process and at-device levels. They need be able to simulate the material's nanometer geometries, how molecules behave and how they interact for device operations. When they put together a process and a device, they need to know how the pieces behave and simulate before production.In other words, they run quite a few design experiments and quite a bit of simulation before they finalize the circuits and devices to silicon to save money.ESD Alliance: It’s obvious design automation will continue to have a vital role in design.Taheri: Yes, absolutely. Design technology co-optimization (DTCO) using TCAD solutions and proven design IP are needed to address the span from architecture to device and process physics. The importance of simulation, emulation and design technology co-optimization, along with fully verified and proven IP for SoC design, cannot be overstated. As designers generate devices and processors, they take that up to circuit-level simulation and high-level simulation, schematic capture, extractions and back annotation. They can go from atoms to simulating systems to the ability to do that under the same umbrella in order to get better chips, better yield and lower cost.Taheri’s talk Next Generation of SoC Design: From Atoms to Systems will be part of the Meet the Experts More than Moore session Tuesday, July 9, at 11:30 a.m. at the ES Design West SMART Design Pavilion. SEMICON West attendees are invited to Moscone Center’s South Hall to learn more about electronic system and semiconductor design and its links to the electronic product manufacturing and supply chain. Register for ES Design West or SEMICON West.Babak Taheri is Silvaco’s CTO and EVP of products, has more than 25 years of design experience. His current role managing Silvaco’s Technology CAD (TCAD), electronic design automation (EDA) and IP product divisions makes him an expert on what’s needed for the design of next-generation system-on-chips (SoCs). Previously, he was the CEO and president of IBT working with investors, private equity firms, and startups on M A, technology and business diligence. Babak received his Ph.D. in biomedical engineering from the University of California Davis with Bachelor of Science degrees in Electrical Engineering and Computer Science and Neurosciences. He has published more than 20 articles and holds 28 issued patents.Nanette Collins is a public relations representative for the Electronic System Design Alliance.

Five young dancers bathed in a striking rainbow of colors with their silhouettes cast in the background dazzled SEMICON Japan 2018 attendees at the opening ceremony in mid-December. Gone were the standard opening keynotes and ribbon cutting, replaced by live performance and media art set against a dramatic black backdrop. There was no mistaking the wide-eyed looks of wonder in the audience.In its sheer vibrance, the opening ceremony thrilled with an excitement that seemed to embody the extraordinary growth expectations for the global semiconductor supply chain over the next five years, with the industry poised to double sales from $2 trillion to a staggering $4 trillion – a phenomena SEMI president and CEO Ajit Manocha has called The Rebirth of the Semiconductor Industry. Driving this unprecedented growth will be SMART applications that are transforming industries and applications worldwide, powered by artificial intelligence (AI) and Internet of Things (IoT) technologies.The dramatic scene at SEMICON Japan 2018 was staged by Rhizomatiks, a media arts company that produced the Rio Olympic Games closing ceremony and is famous for its pop music spectacles. The company’s CTO, Motoi Ishibashi, the event’s first keynote speaker, described his team’s development of drones and vehicles guided by motion and precision-control technologies. It was some of these SMART vehicles that maneuvered the opening ceremony performers from the dance company Elevenplay onstage. Only Rhizomatiks, Ishibashi said, has this capability. In its mission to enrich people’s lives through new media arts, Rhizomatiks uses the latest virtual and mixed-reality technologies to orchestrate not only dance performances but music videos, commercials, fashion shows and festivals.Toru Nishikawa, the second keynote speaker and CEO at Preferred Networks, a leading Japan-based developer of deep learning software programs, surprised the SEMICON Japan audience with his discussion of his company’s work to develop a specialized chip for deep learning processing, joining technology giants Apple, Google, Alibaba and Microsoft in chip design. As more IT and software companies develop specialized, differentiated chips, the devices are quickly becoming the heartbeat of SMART technologies. The company’s approach has taken hold. Only four years old, Preferred Networks is enjoying rapid growth by working with global powerhouses including Toyota, NTT, Panasonic, Fanuc, NVIDIA, Intel and Microsoft. Ishibashi’s and Nishikawa’s fresh visions and the media arts extravaganza reflected the success of SEMICON Japan, held again at Tokyo Big Sight: The event’s 1,881 booths – filled by 727 exhibitors from 14 regions – was the highest count in six years. With Japan home to companies that supply about 40 percent of semiconductor equipment and materials worldwide, top suppliers historically have occupied the largest spaces on the SEMICON Japan show floor.According to IDC, personal computers and smartphones, long the largest revenue sources for the semiconductor industry, will remain top revenue drivers in the coming years. But revenue from new SMART technologies for applications such as automotive and factory automation is growing, a trend expected to continue with a 2018-2022 CAGR of 9.5 percent for automotive and 5.2 percent for manufacturing, compared to 1.1 percent for PCs and 2.9 percent for smartphones.SEMICON Japan’s new SMART Applications zone highlighted these and other new market opportunities for semiconductor growth with product and technology exhibits from companies including Bosch, IBM, Microsoft, NEC, Preferred Networks, Sony, SAS, Siemens, Tesla and Toyota. But the zone wasn’t all work and no play. The ROBOT SQUARE and SPORTS x IOT robot exhibits took visitors back to their school days, with robot anime – from Astro Boy to Gundam and Evangelion – that they could ride and control! As the World Gets Smarter, So Must SEMICON and the IndustryWe all agree the world is getting smarter at a fast pace. New cars are easier to drive – some models are almost fully autonomous on highways and streets. Your SMART speaker has gone well beyond an audio playback device and is more like a home AI platform. Almost all storefronts are equipped with video cameras. Your workplace, whether an office or a factory, is driven by automation. The reliance of these environments and devices on semiconductors is driving exponential chip and changing the world. Businesses need to adapt and so do SEMICON events. We’re doing just that as SEMICON Japan 2018 demonstrated – from an opening ceremony enabled by technology innovation to new faces of the industry to the SMART Application zone. As the SEMICON Japan presidents’ reception concluded the first day of the show, a robot from the ROBOT SQUARE suddenly appeared in the reception hall in front of about 250 executives from the global industry. Everyone at the reception was impressed and stepped forward to the stage, reflecting the overall excitement about SEMICON Japan, which for many years showcased only chip manufacturing equipment and materials. This year, to keep pace with the changing world, it was much more than that.SEMICON Japan 2019 will again take place in December at Tokyo Big Sight. However, organizers of the Tokyo Olympics will be using the East Exhibit Hall usually occupied by SEMICON Japan to prepare for the games. As a result, SEMICON Japan will be held in the West and South Halls instead. Look for more changes to the event. I hope to see you next year!Jim Hamajima is president of SEMI Japan.

As artificial intelligence’s (AI) sprawling influence reshapes industries from logistics and healthcare to automotive and manufacturing, Taiwan is poised to leverage its cutting-edge capabilities and rich history in semiconductor manufacturing to stake out a leadership position in AI. Taiwan’s semiconductor manufacturing industry accounts for a major share of the region’s GDP and, with its manufacturing prowess, the region is fertile ground for using AI to optimize and even revolutionize chip manufacturing. In an AI and Semiconductor Smart Manufacturing Forum recently hosted by SEMI Taiwan, experts from Micronix, Advantech, Nvidia and the Ministry of Science and Technology of Taiwan (MOST) shared their insights on how deep learning, data analytics and edge computing will shape the future of semiconductor manufacturing. Here are four key takeaways.1. Monitor, Forecast, and PreventToday, tier 1 foundries use AI tools to combine equipment know-how and manufacturing statistics in managing massive Fault Detection (FD) data, much in the way that a car’s tire-pressure monitoring system helps maintain safe inflation levels and prevent accidents. For example, AI enables the real-time collection and monitoring of massive amounts of processing data, then alerts system administrators of any hardware failures or other manufacturing abnormalities.AI also makes it possible to adopt Run-to-Run (R2R) control to automate manufacturing process adjustments and corrections by providing feedback that can drive higher processing efficiency. In addition, virtual metrology replaces manual sampling inspection for comprehensive quality control, enabling foundries to improve yields, reduce costs, and strengthen their competitive advantage.2. Beyond Automation: Edge Computing The evolution of IoT is giving rise to a paradigm shift in the industry as the recognition grows that smart factories must go beyond automation to focus also on intelligence. All information – from equipment status and manufacturing process statistics to on-site environmental data – needs to be collected through sensors. In highly time-critical scenarios, returning all sensor data to the cloud for processing is time-consuming and impracticable. This is where edge computing’s real-time features and lower cost than cloud computing come into play.How does edge computing work in a smart factory? First, a rich trove of data from various devices is collected and integrated via Manufacturing Execution Systems (MES). Software analysis then produces a real-time factory production status before production data is visualized through a combination of system platforms and human-machine interfaces. In the end, the data is analyzed realtime in the cloud so failures can be predicted and prevented to help increase capacity and reduce costs. The approach is even capable of Bill of Materials (BOM) predictions, allowing better collaboration between upstream and downstream suppliers.3. Deep Learning Accelerates AI Deep learning enables autonomous driving, intelligent voice assistance and many other AI breakthroughs. The heart of deep learning is its ability to automatically process and learn data in various formats such as images, video and text with no human domain knowledge. This increases predictive accuracy and efficiency in processing massive amounts of data. Deep learning also enhances the efficiency of human-machine collaboration.4. Taiwan’s Competitive Niche: Industry 3.5Industry 4.0 is not just about improving production management. It also focuses on integrating supply chains, even among competitive companies. For Industry 4.0 to thrive, rival companies must grow together. The first and third industrial revolutions centered on disruptive technologies like steam engines, transistors and digital, while the second and fourth revolutions homed in on competition among various business models, platforms and industry ecosystems.While Taiwan’s strengths include innovation, short time-to-market, low manufacturing costs, and high supply chain management efficiency, the region still lags advanced countries in basic industry and research capabilities. Squeezed by Chinese supply chains and high-end manufacturers in advanced countries, Taiwan should start by carving out an Industry 3.5 niche for the island’s manufacturers. SEMI will continue to facilitate cross-industry connection, collaboration and innovation to help manufacturers seeking higher production efficiency and lower costs incorporate AI as a core competitive advantage. At SEMICON Taiwan 2018, SEMI will unveil its Smart Manufacturing Journey, an exhibition that gathers leading AI companies such as ABB, Advantech, Nvidia, Sony and UPS to demonstrate a comprehensive roadmap for smart manufacturing technologies and applications. For more information, please visit the SEMICON Taiwan website.Emmy Yi is a marketing specialist at SEMI Taiwan.

The fast-growing automotive semiconductor market means big change for the IC supply chain. Beyond the obvious demands for reliability and traceability, the sector is moving towards simpler and lower-cost solutions while facing the daunting challenge of automating driving in a complex world. The need for simpler and cheaper automotive intelligence will likely drive acquisitions to build complete platform solutions that are easier to integrate. This demand has already spawned a market for pre-configured test cars to save developers time and money, and is driving LiDAR (Light Detection And RADAR) towards lower-cost, solid state solutions. “The growth of the automotive electronics market provides a great opportunity for the IC supply chain to differentiate on specialty processes and quality for the high-volume automotive business with its long design cycles,” says Scott Jones, principal, strategy, at KPMG, who will speak in the automotive program at SEMICON West. “This differentiation is a chance to reduce chip suppliers’ dependence on scaling volume for the mobile phone world with its short-cycle volatility of winning and losing sockets.” He notes that increasing demand for automotive ICs is also reinvigorating the eight-inch supply chain and spurring opportunity for specialty products such as compound semiconductor devices for power efficiency. Supplying the automotive market also means addressing automotive reliability requirements, which can be 10 times more stringent than for consumer devices. At the same time, the industry must sustain fast-paced development cycles required for the volume and diversity of low-cost IoT devices, manage the segmented supply chain for both those markets, and still spread development costs. Another big challenge for the supply chain will be to automate testing and update vast amounts of embedded software in these automotive devices. “The more complete solution a company can put together, the more the automakers will gravitate to it. They want simplicity,” Jones suggests. Smaller players will need to differentiate with IP and acquire other IP provider to build a broader platform, or be acquired and folded into an all-in-one solution.AutonomouStuff helps accelerate and simplify development of autonomous driving solutionsAutonomouStuff is helping to speed development of these platforms. The company has grown from a sensor distributor into a supplier in the emerging niche of vehicles preconfigured with key interfaces for sensors and controls. These interfaces can then be customized by integrating different components for developers to test their applications. AutonomouStuff offers developers a lineup of vehicle models pre-configured with the interfaces needed to add desired chips, sensors and software to develop their autonomous vehicle systems. Source: AutonomouStuff.“Whether they’re major chipmakers or AI software startups, they don’t have a year to build their own vehicle platforms themselves for developing autonomous vehicle systems,” says Wolfgang Juchmann, VP sales and business development at AutonomouStuff. Juchmann, a SEMICON West speaker, will bring a demonstration vehicle to the show. “In four to six weeks we can prepare a custom test car with selected sensors, enabling users to start testing their computer platforms and software. It’s faster and more cost-effective for us to supply the car with the needed interfaces.” He notes that developers are using some 300 AutonomouStuff vehicles in the field. AutonomouStuff customers are starting to transition from testing on a single car or two to testing on mini-fleets with 50 to 100 vehicles. Beyond sensors and pre-configured vehicles, the next step will be to add more data intelligence services to help with capabilities like tagging the data for training, Juchmann says. AutonomouStuff already offers hardware to support Baidu’s Apollo open-source software stack and data set. The company was recently acquired by the Swedish holding company Hexagon to help support expansion.CMOS silicon LiDAR nears automotive qualificationInnovations in the hyper-competitive LiDAR market, where burgeoning demand is driving the race to develop various types of solid-state devices, may also help reduce the cost of autonomous vehicles. Among the roughly 40 LiDAR suppliers, at least one – Quanergy – is taking advantage of 45nm and 32nm foundry CMOS volume production. The company uses voltage through the semiconductor stack to change the refractive index, controlling the phases of optical beams and the resulting interference patterns of light exiting the chip to quickly steer the laser beam without the need for moving parts, much like the phased array radar its team developed earlier. Solid state LiDAR image with object recognition software. Source: QuanergySo far, most of the small LiDAR units have shipped to the security, industrial automation, drone, robots and 3D mapping markets. However, Quanergy CEO Louay Eldada, another SEMICON speaker, says the company is also winning automotive designs and expects automotive shipments to take off early next year, once automotive certification testing is completed. “We can get design wins because standard CMOS production at TSMC makes us a known entity,” says Eldada. To prevent component misalignment, the company produces its own specialized packaging to secure the laser, phase control ASIC, optical phased-array emitter, detector array, and receiver readout ASIC at its plant in Silicon Valley or the facility of its automotive partner Sensata. Through its software business, Quanergy offers an artificial intelligence (AI) perception program for object recognition and LiDAR tracking. The solution uses the people-tracker software the company acquired from Raytheon.SEMICON West this year expands to three full days of automotive electronics programming and features a Smart Transportation Pavilion. Other companies with experts who will speak as part of the program include XPT/NIO, Infineon, McKinsey, Voyage, GM Cruise, Bosch, Deepen AI, Airbus A3, Nvidia, Excelfore, Byton, Macronix, SK Hynix, SAP, Xilinx, Achronics, California Fuel Cell Partnership, Velodyne, Lam Research, KLA-Tencor, SCREEN, Rockwell, Versum Materials, TechSearch International, Entegris, ASE, Amazon, Continental and Wind River. www.semiconwest.orgPaul Doe, SEMI