Category Archives: Metrology

IC Insights is in the process of completing its forecast and analysis of the IC industry and will present its new findings in The McClean Report 2019, which will be published later this month.  Among the semiconductor industry data included in the new 500-page report is an analysis of the correlation between IC market growth and global GDP growth.

Figure 1 depicts the increasingly close correlation between worldwide GDP growth and IC market growth through 2018, as well as IC Insights’ forecast through 2023.

Figure 1

Over the 2010-2018 timeframe, the correlation coefficient between worldwide GDP growth and IC market growth was 0.86 (0.91 excluding memory in 2017 and 2018), a strong figure given that a perfect positive correlation is 1.0.  In the three decades previous to this timeperiod, the correlation coefficient ranged from a relatively weak 0.63 in the early 2000s to a negative correlation (i.e., essentially no correlation) of -0.10 in the 1990s.

IC Insights believes that the increasing number of mergers and acquisitions, leading to fewer major IC manufacturers and suppliers, is one of major changes in the supply base that illustrates the maturing of the industry and has helped foster a closer correlation between worldwide GDP growth and IC market growth.  Another reason for a better correlation between worldwide GDP growth and IC market growth is the continued movement to a more consumer driven IC market.  IC Insights believes that 20 years ago, about 60% of the IC market was driven by business applications and 40% by consumer applications with those percentages being reversed today.  As a result, with a more consumer-oriented environment driving electronic system sales, and in turn IC market growth, the health of the worldwide economy is increasingly important in gauging IC market trends.

By Rohit Sharma

Constant coverage of an invigorating topic like machine intelligence in the media often urges us to consider its use in EDA technology. As is often the case, there are many myths and falsehoods that consume our time and effort when trying to apply machine intelligence to EDA. This article aims to uncover the myths and to provide helpful advice on applying machine intelligence to your EDA project or product.

Value Proposition

First, there needs to be a clear value proposition for adding machine intelligence to an EDA product. Using machine intelligence to create a me-too product adds no value. EDA customers are too busy to understand or care about an EDA tool’s underlying technology. They just want to use the tool and get results. If the tool delivers value, if it delivers tangible benefits, then they’ll use it. Otherwise, they won’t.

Currently, EDA tool developers are already experimenting with AI and machine intelligence without considering this fundamental truth – without a higher-end objective. AI must deliver something better or new, whether a speed advantage, a performance advantage, new features, new insights, or perhaps even something pleasantly surprising. Before you write a single line of AI-enhanced code, you need to clearly understand how AI will enhance the product. What is the value proposition?

Use Model

There’s a major barrier to customer adoption of AI and machine intelligence technology for EDA tools: EDA users are averse to make decisions based on probabilistic results. Instead, half a century of EDA tool use has conditioned them to expect deterministic outcomes from their tools.

Back in 2003, a prominent visionary and EDA investor was quoted in an interview, saying: “If I open my eyes five years from now, all static analysis in VLSI will be statistical.” Many EDA luminaries have been proven wrong over time for betting that EDA users will accept statistical results. As enthusiastic as I am about using machine intelligence to improve EDA tools, I must urge caution based on the history of EDA failures that employed a probabilistic use model. Decision-makers and EDA tool users want to see deterministic answers to questions about yield or slack, not probabilistic ones.

Our experiences at Paripath in developing the PASER (Paripath Accelerated Simulation Environment) tool also bear this out. We discovered that delivering results 50x faster but with 92% accuracy was simply not good enough for end users. EDA users only started to use PASER when its answers became 98+% accurate. To be adopted in the production flow, the tool had to deliver 99% accuracy.

Data Engineering

There are specific ways to achieve these accuracy goals. The first is data engineering. Machine intelligence is a new approach to EDA tool development and it needs to be trained on a data set. If the data is poor or incomplete, training will create an inaccurate model. Fundamental software-development rules still apply. Garbage in, garbage out.

Without good training data, there’s no way for you to build good neural-network models. If you train a model with garbage data, you’ll get a garbage model. You must cleanse the data before you use it for training. Otherwise, the model will draw inaccurate conclusions and customers will not use your tool. The model is not to blame here. The model’s not wrong. The problem lies in poor data engineering, poor data cleansing, and a lack of discipline to prepare input data.

High Dimensionality

Next, machine intelligence has a unique ability to quickly solve problems of high dimensionality. Pure EDA problems often have high dimensionality. Over the years, EDA developers have perfected the art of segmenting the problems into sequencing solutions with lower dimension. Machine intelligence technology can handle problems with thousands of dimensions, but you need to be careful when tackling problems that have high dimensionality. Too many dimensions can produce confused or inaccurate results with AI and deep-learning technology.

It helps to visualize the problem and to analyze the data set before using the data to train an AI-enhanced EDA tool. Several visualization methods can help. For example, t-SNE (t-Distributed Stochastic Neighbor Embedding) lets you reduce a data set’s dimensionality from a very large number to a much lower number. Figure 1 shows a high-dimension dataset with a dimensionality of 2000, which has been reduced to a low dimensionality of 3.

Figure 1: Visualizing the Data Set with Lower Dimensionality

Reducing the dimensionality of a data set to 3 using t-SNE and visualization allows you to quickly see whether the data set defines an easy or a difficult problem. If the problem is difficult, you’ll likely need to lower the problem’s and the data set’s dimensionality before using the data to train a neural network.

Technology Selection

One factor that determines whether it will be easy or difficult to incorporate machine intelligence into your EDA tool is your choice of AI development tools. AI researchers have developed a long list of frameworks, libraries, and languages that they use to develop AI and machine-learning software. Frameworks and libraries such as TensorFlow, Caffe and MXNet are most popular for developing deep-learning models.

However, these tools are not yet popular with the EDA development community. The languages of choice in the EDA community are traditionally C and C++ for development and Tcl for prototyping and creating user interfaces. The rest of the software world has moved on to newer development languages such as Python, Java, R, and such. Moreover, machine-learning development segments into two distinct processes: training (i.e. generating the model) and inference (i.e. using the model).

Another question to consider is where to generate the model – at the vendor site or the customer site?

Consequently, fitting AI and deep-learning development into EDA development environments can feel like fitting a square peg into a round hole. You may need to create corners in your hole.

EDA is a very small player in the overall software market. Relatively few software developers are familiar with writing EDA tools. It’s best to select AI and deep-learning development tools that can provide some sort of interface that’s compatible with EDA’s development tools of choice. Some AI frameworks have lower-level C and C++ interface layers that provide a familiar entry point for experienced EDA developers.

At Paripath, we chose TensorFlow for exactly this reason. TensorFlow has a lower-level C/C++ interface. Although the resulting development path becomes a longer one using this approach, it’s a more familiar path for EDA developers and therefore it’s a path that can ultimately lead your EDA development team to success. An elaborate study of comparing these frameworks has been published in the book Machine Intelligence in Design Automation.

Integration into Legacy Systems

When you understand the value that you expect machine intelligence to add to your new EDA tool, when you’ve cleansed and then analyzed the data set, and when you have selected an appropriate set of development tools, you’re finally ready to add machine intelligence to your EDA development. There are two use models for AI-enhanced EDA tools. The first uses a trained model to guide the EDA tool’s decision-making. In this use case, the trained neural network doesn’t change. The software’s accuracy doesn’t improve with use unless the company that developed the EDA tool retrains the underlying neural network. This use case follows the familiar, existing use case associated with EDA tools developed using deterministic algorithms.

For the second use case, the end user is able to retrain the underlying neural network, which allows the EDA tool to produce better, more accurate results over time. This use case produces a win/win situation because end users are able to hone their tools and improve them over time, without help from the EDA tool vendor’s application engineers. If the retrained models are also sent back to the EDA developer for incorporation into newer versions of the tool, all users benefit from other users’ training data.

It’s not clear how you’d support this second use case in the current EDA business environment where most data sets are proprietary and are carefully guarded. Most large EDA tool customers want to keep their data in house under tight control. Even with this somewhat restrictive situation, however, EDA tools benefit from the incorporation of machine intelligence because each EDA tool customer can customize the tool and improve its results.

Machine intelligence has much to add to EDA tools’ capabilities. Only time will tell if the customers want and will accept these new capabilities.

Rohit Sharma, founder and CEO of Paripath Inc., is an engineer, author and entrepreneur. He has published many papers in international conferences and journals. He has contributed to electronic design automation domain for over 20 years learning, improvising and designing solutions. He is passionate about many technical topics including machine learning, analysis, characterization, and modeling. It led him to architect guna – an advanced characterization software for modern nodes. 

Sharma has written a book titled “Machine Intelligence for Design Automation.” You can download code examples and other information here.

This originally appeared on the SEMI blog.

IC Insights is in the process of completing its forecast and analysis of the IC industry and will present its new findings in The McClean Report 2019, which will be published later this month.  Among the semiconductor industry data included in the new 400+ page report is an analysis of semiconductor merger and acquisition agreements.

The historic flood of merger and acquisition agreements that swept through the semiconductor industry in 2015 and 2016 slowed significantly in 2017 and then eased back further in 2018, but the total value of M&A deals reached in the last year was still nearly more than twice the annual average during the first half of this decade.  Acquisition agreements reached in 2018 for semiconductor companies, business units, product lines, and related assets had a combined value of $23.2 billion compared to $28.1 billion in 2017, based on data compiled by IC Insights.  The values of M&A deals struck in these years were significantly less than the record-high $107.3 billion set in 2015 (Figure 1).

Figure 1

The original 2016 M&A total of $100.4 billion was lowered by $41.1 billion to $59.3 billion because several major acquisition agreements were not completed, including the largest proposed deal ever in semiconductor history—Qualcomm’s planned purchase of NXP Semiconductor for $39 billion, which was raised to $44 billion before being canceled in July 2018.  Prior to the explosion of semiconductor acquisitions that erupted four years ago, M&A agreements in the chip industry had a total annual average value of $12.6 billion in the 2010-2014 timeperiod.

The two largest acquisition agreements in 2018 accounted for about 65% of the M&A total in the year.  In March 2018, fabless mixed-signal IC and power discrete semiconductor supplier Microsemi agreed to be acquired by Microchip Technology for $8.35 billion in cash.  Microchip said the purchase of Microsemi would boost its position in computing, communications, and wireless systems applications.  The transaction was completed in May 2018.  Fabless mixed-signal IC supplier Integrated Device Technology (IDT) agreed in September 2018 to be purchased by Renesas Electronics for $6.7 billion in cash.  Renesas believes the IDT acquisition will strengthen its position in automotive ICs for advanced driver-assistance systems and autonomous vehicles.  The IDT purchase is expected to be completed by June 2019.

Just two other semiconductor acquisition announcements in 2018 had values of more than $1 billion.  In October 2018, memory maker Micron Technology said it would exercise an option to acquire full ownership of its IM Flash Technology joint venture from Intel for about $1.5 billion in cash. Micron has started the process of buying Intel’s non-controlling interest in the non-volatile memory manufacturing and development joint venture, located in Lehi, Utah.  The transaction is expected to be completed in 2H19.  In September 2018, China’s largest contract manufacturer of smartphones, Wingtech Technology, began acquiring shares of Nexperia, a Dutch-based supplier of standard logic and discrete semiconductors that was spun out of NXP in 2017 with the financial backing of Chinese investors.   Wingtech launched two rounds of share purchases from the Chinese owners of Nexperia with a combined value of nearly $3.8 billion.  The company hopes to take majority ownership of Nexperia (about 76% of the shares) in 2019.

Worldwide PC shipments totaled 68.6 million units in the fourth quarter of 2018, a 4.3 percent decline from the fourth quarter of 2017, according to preliminary results by Gartner, Inc. For the year, 2018 PC shipments surpassed 259.4 million units, a 1.3 percent decline from 2017. Gartner analysts said there were signs for optimism in 2018, but the industry was impacted by two key trends.

“Just when demand in the PC market started seeing positive results, a shortage of CPUs (central processing units) created supply chain issues. After two quarters of growth in 2Q18 and 3Q18, PC shipments declined in the fourth quarter,” said Mikako Kitagawa, senior principal analyst at Gartner. “The impact from the CPU shortage affected vendors’ ability to fulfill demand created by business PC upgrades. We expect this demand will be pushed forward into 2019 if CPU availability improves.”

“Political and economic uncertainties in some countries dampened PC demand,” Ms. Kitagawa said. “There was even uncertainty in the U.S. — where the overall economy has been strong — among vulnerable buyer groups, such as small and midsize businesses (SMBs). Consumer demand remained weak in the holiday season. Holiday sales are no longer a major factor driving consumer demand for PCs.”

The top 3 vendors boosted their share of the global PC market as Lenovo, HP Inc. and Dell accounted for 63 percent of PC shipments in the fourth quarter of 2018, up from 59 percent in the fourth quarter of 2017 (see Table 1).

Lenovo surpassed HP Inc. to move into the No. 1 position in the global PC market in the fourth quarter of 2018. A major factor for Lenovo’s share gain was credited to a joint venture with Fujitsu formed in May 2018. Lenovo also had a strong quarter in the U.S. The company has recorded three consecutive quarters of double-digit year-over-year shipment growth, despite the stagnant overall market.

Table 1. Preliminary Worldwide PC Vendor Unit Shipment Estimates for 4Q18 (Thousands of Units)

Company 4Q18 Shipments 4Q18 Market Share (%) 4Q17 Shipments 4Q17 Market Share (%) 4Q18-4Q17 Growth (%)
Lenovo 16,628 24.2 15,697 21.9 5.9
HP Inc. 15,380 22.4 16,092 22.4 -4.4
Dell 10,915 15.9 10,763 15.0 1.4
Apple 4,920 7.2 5,112 7.1 -3.8
ASUS 4,211 6.1 4,716 6.6 -10.7
Acer Group 3,861 5.6 4,726 6.6 -18.3
Others 12,710 18.5 14,590 20.3 -12.9
Total 68,626 100.0 71,696 100.0 -4.3

Notes: Data includes desk-based PCs, notebook PCs and ultramobile premiums (such as Microsoft Surface), but not Chromebooks or iPads (see “Market Definitions and Methodology: PCs, Ultramobiles and Mobile Phones”). All data is estimated based on a preliminary study. Final estimates will be subject to change. The statistics are based on shipments selling into channels.
Numbers may not add up to totals shown due to rounding.
*Lenovo’s results include Fujitsu units starting in 2Q18 to reflect the joint venture that closed in May 2018.

Source: Gartner (January 2019)

The fourth quarter of 2018 was a challenging one for HP Inc. The company experienced a shipment decline after four consecutive quarters of growth. HP Inc.’s shipments declined in most key regions, except Asia/Pacific and Japan. Dell registered positive growth as the company outperformed in EMEA and Japan, but it experienced a decline in Asia/Pacific and Latin America.

In the U.S., PC shipments totaled 14.2 million units in the fourth quarter of 2018, a 4.5 percent decline from the fourth quarter of 2017 (see Table 2). Four of the top six vendors experienced a decline in U.S. PC shipments in the fourth quarter of 2018. Lenovo’s growth was well above the U.S. average while Dell’s shipments increased slightly compared with a year ago. The overall decline in the U.S. was attributed to weak consumer demand despite holiday season sales as well as SMBs.

“The fourth quarter is typically a buying season for small office/home office (SOHO) and small business buyers in the U.S. as they want to use up the untouched budget before the tax year ends,” said Ms. Kitagawa. “Our early indicator showed that SOHO and small business buyers held off on some new PC purchases due to uncertainties around the political and economic conditions.”

Table 2. Preliminary U.S. PC Vendor Unit Shipment Estimates for 4Q18 (Thousands of Units)

Company 4Q18 Shipments 4Q18 Market Share (%) 4Q17 Shipments 4Q17 Market Share (%) 4Q18-4Q17 Growth (%)
HP Inc. 4,738 33.4 5,130 34.6 -7.6
Dell 3,645 25.7 3,613 24.3 0.9
Lenovo 2,150 15.2 1,743 11.7 23.4
Apple 1,762 12.4 1,800 12.1 -2.1
Microsoft 472 3.3 542 3.7 -12.9
Acer Group 458 3.2 587 4.0 -21.9
Others 953 6.7 1,430 9.6 -33.3
Total 14,178 100.0 14,843 100.0 -4.5

Notes: Data includes desk-based PCs, notebook PCs and ultramobile premiums (such as Microsoft Surface), but not Chromebooks or iPads. All data is estimated based on a preliminary study. Final estimates will be subject to change. The statistics are based on shipments selling into channels.

Source: Gartner (January 2019)

PC shipments in EMEA totaled 20.9 million units in the fourth quarter of 2018, a 3.8 percent decline year over year. There were some positive signs, such as in Western Europe’s demand for desktops and ultramobiles that fueled SMB shipments, while the government sector also benefited from further Windows 10 renewals. Demand in Russia continued to recover, and some parts of Eastern Europe, such as the Czech Republic and Hungary. However, demand was not strong enough to offset declining shipments to consumers.

The Asia/Pacific PC market totaled 24.2 million units in the fourth quarter of 2018, a 4.6 percent decline from the fourth quarter of 2017. Due to uncertainties of the U.S.-China trade relations, and the volatile equity market, there was cautionary demand, especially among consumers and the SMB segment. In the fourth quarter of 2018, PC shipments in China declined 2.5 percent year over year, but shipments grew 5.6 percent sequentially.

Seventh Consecutive Year of Worldwide PC Shipment Decline

For the year, worldwide PC shipments totaled 259.4 million units in 2018, a 1.3 percent decrease from 2017 (see Table 3). This was the seventh consecutive year of global PC shipment decline, but it was less steep compared with the past three years.

“The majority of the PC shipment decline in 2018 was due to weak consumer PC shipments. Consumer shipments accounted for approximately 40 percent of PC shipments in 2018 compared with representing 49 percent of shipments in 2014,” Kitagawa said. “The market stabilization in 2018 was attributed to consistent business PC growth, driven by Windows 10 upgrade.”

Table 3. Preliminary Worldwide PC Vendor Unit Shipment Estimates for 2018 (Thousands of Units)

Company 2018

Shipments

 2018 Market

Share (%)

 2017

Shipments

 2017 Market Share (%) 2018-2017 Growth (%)
Lenovo 58,467 22.5 54,669 20.8 6.9
HP Inc. 56,332 21.7 55,179 21.0 2.1
Dell 41,911 16.2 39,793 15.1 5.3
Apple 18,016 6.9 18,963 7.2 -5.0
Acer Group 15,729 6.1 17,087 6.5 -7.9
ASUS 15,537 6.0 17,952 6.8 -13.5
Others 53,393 20.6 59,034 22.5 -9.6
Total 259,385 100.0 262,676 100.0 -1.3

Notes: Data includes desk-based PCs, notebook PCs and ultramobile premiums (such as Microsoft Surface), but not Chromebooks or iPads. All data is estimated based on a preliminary study. Final estimates will be subject to change. The statistics are based on shipments selling into channels.

Source: Gartner (January 2019)

These results are preliminary. Final statistics will be available soon to clients of Gartner’s PC Quarterly Statistics Worldwide by Region program. This program offers a comprehensive and timely picture of the worldwide PC market, allowing product planning, distribution, marketing and sales organizations to keep abreast of key issues and their future implications around the globe.

It’s chilly!


January 16, 2019

By Walt Custer

4Q’18 World Electronic Supply Chain – Slowing Electronic Equipment Growth

Custer Consulting Group has its first estimate of global electronic equipment growth in 4Q’18 vs. 4Q’17. Chart 1 compares the combined sales of a 213-company OEM composite to regional electronic equipment shipments. The composite is based on individual company financial reports. While fourth-quarter results for this group won’t be available until February, the regional model (driven by early reported Taiwan/China results) points to world electronic end market growth declining from +10% in 3Q’18 vs. 3Q’17 to +2% in 4Q’18 vs. 4Q’17.

These results are still preliminary, but Chart 1 gives an early indication of the magnitude and trajectory of slowing electronic equipment growth.

Chart 2 shows consolidated monthly sales from our regional electronic equipment model where December 2018 global revenues declined 1.8% vs. December 2017 and were down 0.9% sequentially vs. November 2018. Note the very predictable seasonality and the apparent “peaking” of 2018 sales in November – with a likely sharp drop in early 2019.

Sources: Company financial reports and USA, Europe, Japan, China/Taiwan and South Korea regional data as analyzed by Custer Consulting Group.

Wafer Foundry Sales – Leading Indicator for Semiconductors and Semiconductor Equipment

December monthly sales have been reported by Taiwan-listed wafer fabs.

  • Wafer foundry revenues dropped in December, suggesting a coming decline in global semiconductor and semiconductor equipment shipments (Chart 3). Foundry sales have historically been a leading indicator for both chips and semiconductor equipment.

  • Taiwan wafer foundry revenues, world semiconductor sales and the Global Purchasing Managers Index 3/12 growth rates all point to further slowing ahead (Chart 4).

Source: Company financial reports

Semiconductor Industry Business Cycles

Semiconductor shipment growth (although still positive) peaked in early 2018 (Chart 5).  Globally it was up only 4.6% in November 2018 versus the same month a year earlier and its trajectory is pointing down. This compares to +23.7% growth in December 2017.

Semiconductor equipment shipments (Chart 6) actually contracted 0.6% globally for just the month of November 2018 vs. November 2017. They are traditionally more volatile than semiconductor sales.

The normal winter seasonal industry slowdown is upon us and it is being overlaid with economic softness, political uncertainty, product (memory) shifts and general industry weakening.

Walt Custer of Custer Consulting Group is an analyst focused on the global electronics industry. He can be reached at [email protected].

IC Insights is in the process of completing its forecast and analysis of the IC industry and will present its new findings in The McClean Report 2019, which will be published later this month.  Among the semiconductor industry data included in the new 400+ page report is an analysis of the top-50 semiconductor suppliers.

Research included in the new McClean Report shows that the world’s leading semiconductor suppliers significantly increased their marketshare over the past decade.  The top 5 semiconductor suppliers accounted for 47% of the world’s semiconductor sales in 2018, an increase of 14 percentage points from 10 years earlier (Figure 1).  In total, the 2018 top 50 suppliers represented 89% of the total $514.0 billion worldwide semiconductor market last year, up seven percentage points from the 82% share the top 50 companies held in 2008.

As shown, the top 5, top 10, and top 25 companies’ share of the 2018 worldwide semiconductor market increased 14, 15, and 11 percentage points, respectively, as compared to 10 years earlier in 2008.  With additional mergers and acquisitions expected over the next few years, IC Insights believes that the consolidation could raise the shares of the top suppliers to even loftier levels.

There was a wide 66-percentage point range of year-over-year growth rates among the top 50 semiconductor suppliers last year, from +56% for Nanya to -10% for Fujitsu.  Nanya rode a surge of demand for its DRAM devices to post its great full-year results.  However, evidence of a cool down in the memory market last year was evident in the company’s quarterly sales results, which saw its sales drop from $826 million in 2Q18 to $550 million in 4Q18 (a 33% plunge).  Overall, four of the top seven growth companies last year—Nanya, SK Hynix, Micron, and Samsung—were major memory suppliers.  Although Nanya registered the highest percentage increase, Samsung had the largest dollar volume semiconductor sales increase, a whopping one-year jump of $17.0 billion!

In total, only nine of the top 50 companies registered better growth as compared to the 2018 worldwide semiconductor market increase of 16%, with five companies logging increases of ≥30%.  In contrast, only three of the top 50 semiconductor companies logged a decline in sales last year, with Fujitsu being the only company to register a double-digit sales drop.

Figure 1

Broadcom Inc. (NASDAQ: AVGO) announced today that its board of directors has appointed Diane M. Bryant as an independent director, and as a member of its compensation committee.

Ms. Bryant has more than three decades of executive leadership in the global semiconductor, enterprise IT solution development and deployment, and cloud computing services industries. Most recently, Ms. Bryant served as the Chief Operating Officer of Google Cloud, where she focused on accelerating the scale and reach of Google Cloud’s business, including optimization of the global supply chain, acceleration of customer adoption, and development of next generation information technology solutions.

Prior to Google Cloud, Ms. Bryant spent 32 years at Intel, most recently serving as Group President of Intel’s Data Center Group, the worldwide organization that develops server, storage and network platforms for the digital services economy, in 2017, having led that group since 2012. Before becoming Group President, Ms. Bryant served as Intel’s Corporate Vice President and Chief Information Officer, responsible for the corporate-wide information technology solutions and services that enable Intel’s business.

Ms. Bryant also serves on the board of directors of United Technologies Corporation, and on its audit and finance committees, and on the U.C. Davis Chancellor’s Board of Advisors and U.C. Davis College of Engineering Board of Advisors.

“Diane is a deeply experienced technologist and proven business leader with tremendous operational and strategic knowledge in cloud computing and enterprise IT which will be invaluable to Broadcom as we continue to expand our product offerings,” said Henry Samueli, Chairman of Broadcom’s board of directors.

Ms. Bryant received her bachelor’s degree in electrical engineering from U.C. Davis in 1985. She attended Stanford Graduate School of Business, completing the Executive Program in 2011. Ms. Bryant holds four U.S. patents in mobile computing.

By Christian G. Dieseldorff

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 California.

This story first appeared on the SEMI blog.

SIA today filed comments to the Department of Commerce Bureau of Industry and Security (BIS) in response to an advanced notice of proposed rulemaking of controls for “emerging” technologies. In accordance with requirements of the Export Control Reform Act of 2018 (ECRA), enacted into law as part of the defense authorization bill, BIS is required to establish export controls on certain “emerging and foundational technologies.” The SIA comments respond to the request for comments on “emerging” technologies, and we expect BIS to commence a separate rulemaking on “foundational” technologies sometime this year.

Maintaining a strong U.S. semiconductor industry is critical to our country’s economic and national security. Semiconductors are America’s fourth-largest export, and the semiconductor industry has a highly complex, specialized, and geographically widespread global supply chain. For these reasons, it is important for government and industry to work together to ensure U.S. export control policies both enhance our national security and continue to allow the U.S. semiconductor industry to grow and innovate. SIA has long collaborated with the U.S. government to support reforms and modernization of export control policy, particularly with respect to semiconductors.

The SIA comments outline the statutory framework set forth in ECRA and call on BIS to carefully consider each of the factors set forth in the statute in crafting narrowly tailored controls on emerging technologies. Among other things, ECRA calls on BIS to consider controls only on technologies essential to national security, whether these technologies are exclusive to the U.S. or are available from foreign sources, and the effectiveness of proposed controls. It also directs BIS to consider the impact of unilateral controls on specified technologies on domestic research and development and the economy as a whole. SIA’s comments provide detailed recommendations on how BIS can best implement these statutory mandates.

We are confident BIS, by following the statutory criteria set forth in ECRA and considering the input of affected stakeholders, will enhance national security while at the same time enabling the semiconductor industry in the U.S. to grow and innovate.

The SEMI Industry Strategy Symposium (ISS) opened this week with the theme “Golden Age of Semiconductor: Enabling the Next Industrial Revolution.” The annual three-day conference of C-level executives gives the year’s first comprehensive outlook of the global electronics manufacturing industry.

For ISS 2019’s nearly 300 attendees, opening day highlighted market and technology opportunities and the high-water mark for semiconductor manufacturing supply chain investments in 2018. Deep discussions on applications, disruptions and Industrial Revolution 4.0 will mark today, Day 2. Day 3 will feature presentations on industry workforce development and the evolving U.S.-China relationship and convene an expert panel on “The Next Semiconductor Revolution: Filling the Gap Between Smart Speakers and Autonomous Vehicles” to culminate SEMI‘s business leader annual kick-off event.

Opening keynote speaker Ann Kellehere, Senior Vice President and General Manager of the Technology and Manufacturing Group at Intel, observed that data is powering the fourth industry revolution and the expansion of compute markets. Excellent customer experience and new technologies including Internet of Things (IoT), artificial intelligence (AI) and autonomous vehicles are key drivers of data growth.

Today, fabs collect more than 5 billion sensor data points each day. The challenge, Kellehere noted, is to turn massive amounts of data into valuable information. With customers expecting continual improvements in applications, the question is whether the chip industry is moving fast enough to meet these expectations. 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, presenters took on macroeconomic trends and detailed industry-specific forecasts:

Ambassador (Ret.) Nicholas Burns, Harvard Kennedy School of Government, noted the United States is trailing China in a battle for technological supremacy. By 2050, Indo-Pacific could become the world’s locus of economic power, potentially leading to conflict and instability. The rise of nationalism in China, India, Japan, Russia and the U.S. is a major trend, and the power gap between the U.S. and China, Russia and India is narrowing. From 1979 through last, China and the U.S. came together to solve big problems, he noted. The world has shifted ominously from strategic engagement to outright strategic competition.

Duncan Meldrum, Hilltop Economics, noted the world has passed the peak of its current economic expansion, with GDP peaking in 2018 and gradually slowing to 2.7 percent trend growth. The consensus outlook is for strong global economic growth. While an alternate outlook holds that a global recession will develop, a deep growth recession isn’t expected. The problem today is that global economic uncertainty is at an all-time high, suppressing investment and growth.

Bob Johnson, Gartner, forecasts businesses will get $5 trillion of value from AI by 2025 as businesses explore ways to implement AI to tap its tremendous potential. AI, IoT and 5G are major enablers of new value, with market demand shifting from consumer to commercial applications offering higher returns on investments, Johnson said. Future semiconductor market drivers include augmented analytics, digital twins, AI, autonomous things, blockchain, smart spaces and quantum computing.

Andrea Lati, VLSI Research, expects the semiconductor slowdown to continue into the first half of 2019 and said it could face a decline of as much as 35 percent. The strategic question for industry leaders is how to transition from a commodity provider to a value provider. In 2019, both semiconductor equipment and assembly sales are forecast to drop 13 percent, ending equipment’s strong run since 2016.

Michael Corbett, Linx Consulting, provided an upbeat outlook for the materials industry, which is enjoying a record expansion with MSI a key driver and record levels of capital expenditures reflecting very high utilization across both 200mm and 300mm. Materials market trends include a wafer fab materials CAGR of 6.9 percent from 2017 to 2022 and industry growth of $26 billion in 2018 to $33 billion in 2022.

The afternoon session focused on Market Perspectives, including smart manufacturing, human health, AI and 5G.

Sujeet Chand, Rockwell Automation, outlined Smart manufacturing best practices for semiconductor production. He envisions big data being increasingly replaced by data structured based on target factory outcomes that dictate whether to run analytics on the edge or in the cloud. Semiconductor fab productivity driven by digitization will grow faster in the next 10 years than in the past 50 as information and operational technology converge to speed the optimization of semiconductor fabs and supply networks, he said.

Igor Fisch, Selexis, focused on how the current golden age of semiconductors is shaping human health. He pointed to the critical importance of chips in biotechnology as big data becomes key to the analytics that will give rise to personalized diagnostics and therapies. Drug discovery and development will rely on massive computing power and data storage, with semiconductor and supercomputer technologies key enablers of precision medicine.

Eric Jones, Enthought, noted that semiconductor manufacturers must reimagine themselves over the next decade to power their own digital transformation. Data consolidation, automation and simulation will enable the predictive power – key to digital transformation – of AI and machine learning, he said. However, the greatest challenge is related to changing company culture, philosophy and organizational design.

Sree Koratala, Ericsson, forecasts 5G will evolve from initial use cases to mainstream adoption in 2024. Connectivity has reached an inflection point, with the focus shifting from consumers to businesses including the immersive experiences of virtual and augmented reality (AR/VR), autonomous control and cloud robotics. 4G and 5G will co-exist to deliver a much larger impact to people and businesses, she noted.

Sarah Cooper, Amazon Web Services, highlighting IoT trends, offered a vision of products learning from collected data to personalize functionality. Product differentiation is not about the specifications but about the customer experience. Coupling device data with machine learning can create a product that adapts to changing customer needs, eliminating the need to develop separate SKUs, she noted.

Days 2 and 3 at ISS will delve deeper into the industry with presentations by: Tokyo Electron Limited,Xperi, Micron Technology, Google, Applied Materials, McKinsey & Company, Brewer Science, DECA Technologies, Carbon, Bank of America Merrill Lynch and SEMI. 

The SEMI Industry Strategy Symposium (ISS) examines global economic, technology, market, business and geo-political developments influencing the global electronics manufacturing industry along with their implications for your strategic business decisions. For more than 35 years, ISS has been the premier semiconductor conference for senior executives to acquire the latest trend data, technology highlights and industry perspective to support business decisions, customer strategies and the pursuit of greater profitability.