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For nearly two decades, Sean Ding, CTO and chief scientist of Alibaba Cloud IoT, has worked in software and algorithm architectures, sensing, semiconductors, systems and cloud computing – all areas that have contributed to the rise of the Internet of Things (IoT). It’s no surprise, then, that Alibaba is leading next-generation innovation for the IoT. Ding will bring his expertise to his role as moderator of Brave New World - MSIG Conference on AI+IoT 2019, a half-day forum March 20, 2019, at SEMICON China in Shanghai, China. Maria Vetrano of SEMI spoke with Ding about technologies key to the IoT era including MEMS, sensors, artificial intelligence (AI), edge gateways and cloud computing. SEMI: MEMS sensors are widely used in IoT devices. What is the relationship between AI and MEMS sensors?DING: While MEMS sensors and AI will increasingly co-reside in end-user devices, I do not recommend adding AI next to the sensor (in the same package). That’s because designers continue to use the ASIC for signal conditioning, so A/D converters are still required. Rather, we should look to edge gateways to carry the majority of the workload, including deep learning, because this reduces system complexity and power consumption.SEMI: Why are smarter sensors shifting data processing and analytics to the edge of IoT devices?DING: Data processing and analytics are very important for IoT devices, but we need to focus on understanding the data, parameter calibration and more. The MEMS sensor industry should leave big data analytics to edge computing and cloud computing because AI requires deep learning, demanding a huge amount of data.The challenge is to find the sweet spot for data processing right next to the sensor element.SEMI: What is China’s evolving role in innovation in MEMS sensors for IoT devices?DING: At present, the MEMS community in China needs to figure out how to innovate instead of copying existing technologies, a low-margin business that will not help to grow the industry. One reason why I am so pleased to see the MSIG Conference on AI+IoT in China is that it will encourage greater creativity in the MEMS community in China, and this will ultimately lead to Chinese companies and R D institutions leading innovation rather than copying it.SEMI: What is the right approach to combining smart MEMS sensors with AI in IoT devices? Why is this important for both domestic Chinese and international markets?DING: Combining data from sensors with cloud-edge computing is the right approach. As sensor companies increasingly provide end-to-end solutions, such as “sensor+ firmware + SaaS + app,” we will realize easier and faster integration of sensors in IoT applications.This is incredibly important because China today is the world’s biggest market for IoT hardware. China has 2,000-plus design houses, 200-plus OEMs and thousands of distributors. That said, we still see a highly fragmented market that will benefit from a faster integration methodology.Faster integration of MEMS sensors and AI/machine learning for IoT hardware will benefit designers in international markets as well.SEMI: What do you hope MISG Conference on AI+IoT attendees will take away from the forum? DING: MEMS sensors are highly fragmented, reflecting the highly fragmented applications in which they play. The MEMS sensors industry should figure out how to provide one-stop-shopping solutions for vertical markets. This will speed the scalability of applications and expedite the growth of sensor production. Sean Ding (柯镇) will moderate Brave New World - MSIG Conference on AI+IoT 2019 at SEMICON China on Wednesday, March 20, 2019, at Kerry Hotel Pudong in Shanghai, China.This conference has been organized by the MEMS Sensors Industry Group (MSIG). Register today to connect with Sean Ding and featured speakers at the event.Speakers at the MSIG Conference on AI+IoT 2019 at SEMICON China include: Welcome and Introduction / 欢迎辞Carmelo Sansone, Director, MEMS Sensors Industry Group (MSIG), a SEMI technology community AI Needs Accurate Data – MEMS Sensors Can Provide It / MEMS传感器为人工智能提供真实数据Andrea Onetti, Group VP of Analog MEMS Group, GM of MEMS Sensor Division, STMicroelectronics Enhanced IoT Edge by Smart Sensors / 智能传感器助力IoT边缘智Bennini Fouad, Regional President Asia Pacific, Bosch Sensortec Horizon AI Processor Solution, Enable Industries in AI Time / 地平线AI芯片解决方案,赋能千万业Carl Zhang 张永谦, General Manager/VP, Smart Chip Solutions Division, Horizon Robotics Inertial Sensors in AI Applications / 运动传感器AI应用案例Ben Lee 李彬 , CEO, mCube Ultra-Low-Power Solutions: an Ecosystem Approach / 超低功耗的生态链解决方案Carlos Mazure, IEEE Fellow, Chairman Executive Director, SOI Industry Consortium High-Integrity, Fault-Tolerant Open Inertial Measurement Platform for AI-based Vehicle Automation / 适用于人工智能车辆自动控制的高集成及容错的惯性测量开放平台Dan Dempsey, Senior Director of Automotive, ACEINNA Maria Vetrano is a public relations consultant at SEMI.
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This year, SEMI ISS covered it all – from a high-level semiconductor market and global geopolitical overview down to the neuro morphic and quantum level. Here are key takeaways from the Day 1 keynote and Economic Trends and Market Perspectives presentations.In the opening keynote, Anne Kelleher from Intel pointed to the huge growth of data, with fabs collecting more than 5 billion sensor data points each day. The challenge, Kelleher noted, is to turn massive amounts of data into valuable information. Moore’s law is not dead. New models of computing benefit still from Moore’s law and advances in Si/CMOS technologies for conventional, deep learning, neuro morphic and quantum computing.With customers expecting continual improvements in applications, the question is whether the chip industry is moving fast enough to meet these expectations, Kelleher said. A broad supply chain, equipment and materials innovations, and attracting the “best of the best” college graduates to fuel innovation is key, she said.In the economic trends session, Nicholas Burns (ambassador ret.) from Harvard University pointed out that we will see a major shift in power. The U.S. will remain the major world power over the next 10 years, but we will see a major shift in power in the next coming decades as the gap with countries like China, Russia and India continues to narrow.Duncan Meldrum from Hilltop Economics said that we are passing the peak growth of economic cycle. He warns that a more likely outlook is that a global growth recession is developing. Although semiconductor MSI growth will see a noticeable slowdown in 2019 and 2020, the semiconductor industry is still healthy over the longer term.Bob Johnson from Gartner sees demand shifting from consumer to commercial applications with higher ROIs and budgets. AI, IoT and 5D are the major enablers. He sees structural changes in the semiconductor industry especially for memory but also for Moore’s law with increasing costs and fewer players.The DRAM markets shows volatility and NAND market may be negative in 2019 but non-memory are expected to accelerate mainly because of increasing content and some price hikes.Overall Gartner expects good long-term growth with a CAGR (2017 to 2022) of 5.1%, outpacing 2011 to 2016 CAGR of 2.6%. After a strong 2018 with 13.4% revenue, he forecasts a slower 2019 with 2.6% growth followed by a 8% growth in 2020 and negative growth rate in 2021.Andrea Lati of VLSI went “Back to fundamentals” in his presentation about the industry. VLSI sees a downside bias due to slowing global economy, tariffs, and trade wars. Future drivers are data economy, cloud, AI and automotive.As memory leads the 2019 slowdown, analog, power, logic and other sectors remain in positive territory. VLSI lowered its semiconductor equipment forecast for 2018 from 20% (Jan. 2018) to 14% (Dec. 2018) but increased its sales outlook from 8% to 15% in 2018. VLSI expects revenue to slow into the first half of 2019 but increase to over 4% in the second half of the year, resulting in total 2019 drop of 2.7%. Semiconductor equipment sales are expected to drop from 14% in 2018 to -10% in 2019.Michael Corbett of Linz Consulting, covering wafer fab materials in the years of 3D scaling, sees these as good times for the industry. His outlook for wafer fab materials is bullish based on strong MSI and because wafer fab materials suppliers are getting bigger because of M As.In the Market Perspective session, Sujeet Chand of Rockwell Automation pointed out that as more and more data is generated, the problem is how to get value of all the data collected. There is a need to create the right architecture for machine learning and AI and big data is increasingly being replaced by contextual/structured data. He expects Industry 4.0 to drive foundries to become smaller, more flexible and more productive.In the Technology and Manufacturing session, Aki Sekiguchi of TEL addressed process challenges in the age of co-optimization. The semiconductor industry continues to expand, driven by massive growth of interconnected devices, with heavy demand for processing power and storage. He expects an exponential increase of data from about 40ZB in 2018 to 50ZB in 2020 to 163 ZB in 2026.Major technologies such as DRAM, 3D NAND and logic are dealing with scaling challenges. The density of DRAM (Mb/chip) is plateauing according to 2015 to 2020 trend data, with DRAM is in need of EUV. Memory capacity demand is leading to increasing layers and higher aspect ratios that is concern for 3D NAND and mainly for plasma etch. With Logic already implementing 3D structures, it appears to be in a solid position. Buddy Nicoson of Micron talked about his 50 years in the industry and looked ahead to the next 50. The anchors – quality, cost, scale and speed – won’t change. It has been a great journey so far with unprecedented opportunities and challenges ahead of us. We are getting into a convergence (specialization, integration) and solution-based phase. We will see some inflection points in the coming years, with the best yet to come.Christian G. Dieseldorff is senior principal analyst in the Industry Research and Analysis group at SEMI in Milpitas, California.
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I really don’t know clouds at all. – Joni MitchellThe semiconductor industry is finally on the cusp of joining the cloud revolution. The cloud has offered the promise of greatly expanded resources for years, but adoption has been slow due to lingering concerns. The biggest contributing factor for the concern over moving from on-premise EDA servers to cloud-based servers is, surprisingly, the rise of third-party IP. In the old days, if you were developing 100 percent of your own IP, and if you put that IP on a public cloud, and it somehow leaked out, well shame on you. That would certainly be bad for business. It might hurt your reputation a bit. But these days, with so much third-party IP being embedded into chips, if that third-party IP leaks out, that’s a lawsuit-fest in the making.Consequently, semiconductor companies now have even more incentive to protect IP with advanced security. Surprisingly, cloud-based security is far, far better than on-premise security. Why? Because keeping customers’ data secure is the central mission of cloud service suppliers, so they’ve developed a rich set of security tools to protect the data that’s entrusted to them by their clients. In many ways, you can maintain much better security in the cloud than you can with on-premise tools. Image credit: Markus Spiske temporausch.com from Pexels Amazon Web Services: Exemplifying the benefits of cloud computingTake Amazon Web Services (AWS) as an example. (Note: AWS is not the only vendor in the cloud space, but it’s one I’m very familiar with.)AWS has developed the concept of security groups – firewalls that you throw up around any network interface to allow only specific traffic into that secured network. You can do that for just one server or for a fleet of servers, in just seconds. Most on-premise server networks won’t let you work that quickly, or as easily, or with such fine control because most such networks lack the security tools to do this.In addition, AWS allows you to encrypt every bit of data stored on and flowing through its cloud-based storage systems. You can encrypt data at rest in on-premise storage but it’s a lot harder to encrypt data flying through the on-premise network. Amazon’s Elastic File System (EFS), a managed NFS file service, offers the ability to easily encrypt NFS traffic on the wire, a difficult feat at best with an on-premise solution.AWS built-in encryption key-management service can rotate encryption keys automatically. The cloud also allows you to have key policies that are easy to implement and maintain.Internal corporate networks rely heavily on perimeter firewalls for security. Perimeter defense just cannot deliver sufficient security against determined hackers and everyone realizes this. We’ve built big, open, on-premise networks that are just not well-suited to implementing adequate security protocols. Trying to retrofit these network architectures with additional security is time-consuming and costly, and it hurts engineering productivity. Moving to the cloud gives you a greenfield opportunity to right some of the wrongs of the past.Continuing with AWS as an example, here are some additional advantages of EDA in the cloud: AWS provides physical security that’s far above and beyond on-premise security. It doesn’t publish the physical locations of its data centers. It also has professional security staff 24/7, keycard access, and additional security features that far exceed typical on-premise physical security. AWS automatically manages security patches and access controls for their managed services such as database services. AWS gives you plenty of security tools to automate security processes, audits, and so forth to protect your data. AWS gives you so much flexibility that you can get yourself in trouble in you are not careful. If you want, you can create the same sorts of security holes that already exist with on-premise networks. You shouldn’t of course, but you can if you’re not thoughtful about things. You just need to hire the right people to implement and maintain your cloud security.Here are five very big differences between AWS (cloud-based) and on-premise server networking: Elasticity: Cloud-based systems enable you to scale up in minutes. That ability has pluses and minuses depending on how disciplined you are. On the plus side, you can quickly grow your EDA infrastructure as big as you want and then shrink it back down when you no longer need the additional capacity. All you need to do is tell the cloud service that you need more capacity and it will bring that extra capacity online for you in minutes – and will charge you for it. (That’s the minus side.) When you’re done, you can turn off the extra capacity (and stop paying for it) with the same speed. If you want to provision more EDA capacity for your on-premise network, you’ll need to beg, borrow, or steal existing capacity from someone else on your network, or you can order more servers, get the vendor to build and ship them, install them in your server room, provision them, and bring them online. That will take months. Fault tolerance: On-premise networks rely on large, monolithic service architectures, which saddle EDA vendors with more than 30 years of technical debt. The cloud operates on a different model, one that’s based on containers and microservices. This is inherently a redundant, fault-tolerant computing model if you write your code correctly. The difference between redundancy in the cloud and in on-premise networks is night and day. There’s no comparison. No private networks can match the available and growing redundancy of cloud systems, which have redundant servers inside of a data center and redundant data centers in multiple, worldwide geographic locations, which protects your data from natural and man-made disasters. Network segmentation: Many semiconductor developers have several design centers distributed around the world and there may be IP in use on a project that cannot be shared with certain geographic locations either by law or by contract. Cloud networks are already set up with automated tools for network segmentation that can enforce geography-specific rules through VPCs (Virtual Private Clouds), which are easy to set up. VPCs allow you to set up subnets with restrictions based on routing tables so that IP management and control become highly automated. Removal of single points of failure: The typical EDA grid configuration has several built-in single points of failure. For example, a central job dispatcher generally runs on one single node. If that node dies, all EDA work halts. The same is true for EDA license servers and for configuration-management and version-control servers. Again, because cloud networks are based on the microservices concept, the cloud simply doesn’t need to have the same single-point-of-failure vulnerabilities that on-premise networks have. On-premise networksTo get these same advantages with on-premise networks, the grid architecture must fundamentally be changed, starting with the replacement of NFS. EDA systems need to replace huge, monolithic file systems specifically developed for EDA with object storage. That's a tall order – one that requires the rewriting of fundamental assumptions that serve as EDA software’s foundation.In the 1980s, 1990s, and early 2000s, small EDA startups appeared to fill gaps in the offerings of the large EDA players. If they succeeded and grew, they’d eventually be gobbled up by a larger EDA vendor. That flowering of EDA startups seems to have damped down. The market has really matured.Next wave of EDA startups to offer cloud-first toolsGoing forward, I expect the next wave of EDA startups will be offering cloud-first tools that are not burdened by three decades of technical debt. They’ll be able to architect their tools specifically for the cloud.We’re starting to see this happen. For example, Metrics, a Canadian EDA startup, offers a pay-by-the-minute, cloud-based simulator and verification manager. Although one job on one cloud server might run slower than a monolithic simulator running an on-premise server, Metrics has architected its tools so that you can throw more servers at the problem, allowing you to run all of your jobs at once. Here, multiple simulation jobs running concurrently on multiple servers will ultimately finish faster than running the jobs serially on one slightly faster on-premise simulator.That’s the kind of innovation that we’re going to see. That’s the future of EDA.Derek Magill is executive director and president at HPC Pros. Derek has 20 years of experience supporting semiconductor engineering functions. His main focus has been in system architecture and technical management, but over the years he has been involved with technologies such as EDA licensing, ClearCase, HPC architecture, IP management and engineering software support. Derek spent 15 years at Texas Instruments in various technical and managerial roles. He is currently a senior manager, IT at Qualcomm managing the Global License Infrastructure team as well as the lead technical architect for the company's engineering cloud activities. The Electronic System Design (ESD) Alliance, a SEMI Strategic Association Partner, is the central voice to communicate and promote the value of the semiconductor design ecosystem as a vital component of the global electronics industry. As an international association of companies providing goods and services throughout the semiconductor design ecosystem, it provides a forum to address technical, marketing, economic and legislative issues affecting the entire industry. The ESD Alliance also stages events that promote networking, learning and collaboration among member companies. To learn more about the ESD Alliance and how to join the group, visit www.esd-alliance.org or contact Bob Smith at [email protected].
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SEMI FabView update for calendar year Q3 2018 Global fab construction investment shows continuing strength, with 19 new fab projects expected to begin construction in 2019 and 2020, based on the latest data published in SEMI’s World Fab Forecast. Fab investment is just one indicator of how growing demand in areas such as high-performance computing, data storage, artificial intelligence (AI), cloud computing, and automotive are driving the fourth consecutive year of spending growth in the semiconductor industry. Below are a few highlights* from September’s SEMI FabView: Memory: Not fading Micron plans to invest $3 billion by 2030 in Manassas, Virginia – These investments, driven by strong demand for automotive applications, are contemplated in Micron's long-term model. The production ramp is anticipated to be in the first half of 2020. SK Hynix to build new DRAM fab in Icheon (Gyeonggi Province), Korea – The construction, to be completed by the end of 2020, will adopt 1znm node (probably EUV). Total investment is estimated to exceed $13 billion. Nanya Technology doubles 2018 capex plan – The increase is for additional DRAM capacity and more 20nm DRAM conversion (from 30nm). 200mm and below: Not leading edge, but continues to draw investment Vanguard changes fab investment strategy – Vanguard will focus on 200 mm and has scrapped its plan for 300mm expansion. Murata to invest into 150mm expansion – Murata announced a 5 billion Yen investment (US$44.6 million) in a new fab extension in Vantaa, Finland. Investment, M A in Analog, Logic, Power and Opto Segments Texas Instruments is looking to invest $3.2 billion in new fab construction in 2019 – Texas Instruments is eyeing Richardson, Texas and also considering sites outside Texas. Bosch 300mm fab in Dresden, Germany – Bosch held a groundbreaking ceremony on April 24. Equipment installation is expected in 2H19. Microchip completes acquisition of Microsemi – Microchip closed its $8.45 billion acquisition of Microsemi on May 29. Microsemi has five fabs in the U.S. with a wide range of semiconductor products and system solutions. New fabs in China keep on coming Shanghai Jita Semiconductor/Huada Semiconductor – Shanghai Jita Semiconductor, a subsidiary of Huada Semiconductor and China Electronics Corporation (CEC), announced plans earlier this month to build both 200 mm and 300 mm semiconductor fabs for analog and power semiconductors in Shanghai. The combined fab investment will total $5.18 billion. Hamamatsu Photonics building 200 mm fab – Hamamatsu announced that it is building a new facility Investment of 2.8 billion Yen (US$25 million) to boost opto semiconductor capacity. Production is anticipated to start in late 2019. * Actual FabView updates provide more detail SEMI FabView, a mobile-friendly, interactive version of SEMI’s popular World Fab Forecast, delivers on-demand fab information such as fab spending and capacity for over 1,200 facilities, including over 60 planned facilities worldwide, across a wide range of product segments including Power, GPU, Memory, Foundry, MEMS and Sensors fabs. Fab data include region, start of construction, operation, construction and equipment spending, capacity, wafer sizes, product types and geometries. SEMI FabView subscribers receive forecast model updates through SEMI’s World Fab Database. Click here for a trial if you want to experience SEMI FabView first hand. Christian G. Dieseldorff is senior principal analyst and Eugenia Liu is senior product marketing manager, Industry Research and Statistics, SEMI, Milpitas, California.
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