Category Archives: Semiconductors

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.

Integrated Device Technology, Inc. (IDT®) (NASDAQ: IDTI), a supplier of high-performance system-level analog/mixed-signal semiconductors, today announced that, at the Company’s special meeting of stockholders held on January 15, 2019, IDT stockholders voted to adopt the Agreement and Plan of Merger, dated September 10, 2018, by and between IDT and Renesas Electronics Corporation (“Renesas”, TSE: 6723), a premier global supplier of advanced semiconductor solutions.

Approximately 99% of all votes cast voted in favor of the adoption of the merger agreement, representing approximately 82% of all outstanding shares as of November 23, 2018, the record date for the special meeting. The final voting results for each of the proposals voted on at the special meeting of stockholders will be reported on a Current Report on Form 8-K, in accordance with the rules of the U.S. Securities and Exchange Commission.

Closing of the transaction remains subject to customary closing conditions and remaining regulatory approvals.

On December 21, 2018, IDT reported that the Committee on Foreign Investment in the United States (CFIUS) review regarding national security concerns relating to the Merger was underway and the initial 45-day review period would conclude by January 2, 2019. Due to the U.S. government shutdown that commenced in December 2018, this review period has been tolled pursuant to section 1709 of the Foreign Investment Risk Review Modernization Act of 2018, and will resume following the resumption of operations by the relevant U.S. government agencies.

As previously announced, the two companies have already received regulatory antitrust approval for the proposed transaction from China, Germany, Hungary, and Korea. In addition, the waiting period under the Hart-Scott-Rodino Antitrust Improvements Act of 1976, as amended, in connection with the proposed acquisition expired at 11:59 p.m., Eastern time, on October 22, 2018.

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.

Rambus Inc. today announced it has acquired the assets of Diablo Technologies to broaden its portfolio in the hybrid DRAM and Flash memory markets. These patented innovations augment the existing Rambus NVDIMM portfolio and complement its high-bandwidth, low-power memory technologies. Specific terms of the deal are not disclosed.

For over ten years, Diablo Technologies was a pioneer in the development of NVDIMM technologies for high-speed, low-power, and low-latency bridging and switching products targeted at the server and storage markets. Having developed memory buffer and software solutions leveraging an all-Flash memory sub-system, Diablo Technologies enabled an architecture to rewrite the rules of data center performance and economics. Rambus’ investment in these technology areas provide a foundation for integrating existing DRAM and Flash along with emerging memories into advanced hybrid memory systems in the future.

Expanding emerging memory technology for high memory bandwidth interfaces is key to Rambus’ strategic core business. The company has also been collaborating with IBM to research hybrid memory systems, as announced previously.

“Adding these breakthrough innovations from Diablo Technologies will continue to grow Rambus’ leadership in non-volatile and hybrid DRAM and Flash memory technologies with foundational patents,” said Kit Rodgers, SVP of Technology Partnerships and Corporate Development, Rambus. “Diablo Technology’s patented innovations were ahead of their time and nicely complement our offerings for existing and new customers.”

The absorption of light in semiconductor crystals without inversion symmetry can generate electric currents. Researchers at the Max Born Institute have now generated directed currents at terahertz (THz) frequencies, much higher than the clock rates of current electronics. They show that electronic charge transfer between neighboring atoms in the crystal lattice represents the underlying mechanism.

Solar cells convert the energy of light into an electric direct current (DC) which is fed into an electric supply grid. Key steps are the separation of charges after light absorption and their transport to the contacts of the device. The electric currents are carried by negative (electrons) and positive charge carriers (holes) performing so called intraband motions in various electronic bands of the semiconductor. From a physics point of view, the following questions are essential: what is the smallest unit in a crystal which can provide a photo-induced direct current (DC)? Up to which maximum frequency can one generate such currents? Which mechanisms at the atomic scale are responsible for such charge transport?

(a) Unit cell of the semiconductor gallium arsenide (GaAs). Chemical bonds (blue) connect every Ga atom to four neighboring As atoms and vice versa. Valence electron density in the grey plane of (a) in the (b) ground state (the electrons are in the valence band) and in the (c) excited state (electrons are in the conduction band). Apart from the valence electrons shown, there are tightly bound electrons near the nuclei. Credit: MBI Berlin

The smallest unit of a crystal is the so-called unit cell, a well-defined arrangement of atoms determined by chemical bonds. The unit cell of the prototype semiconductor GaAs is shown in Figure 1a and represents an arrangement of Ga and As atoms without a center of inversion. In the ground state of the crystal represented by the electronic valence band, the valence electrons are concentrated on the bonds between the Ga and the As atoms (Figure 1b). Upon absorption of near-infrared or visible light, an electron is promoted from the valence band to the next higher band, the conduction band. In the new state, the electron charge is shifted towards the Ga atoms (Figure 1b). This charge transfer corresponds to a local electric current, the interband or shift current, which is fundamentally different from the electron motions in intraband currents. Until recently, there has been a controversial debate among theoreticians whether the experimentally observed photo-induced currents are due to intraband or interband motions.

Researchers at the Max Born Institute in Berlin, Germany, have investigated optically induced shift currents in the semiconductor gallium arsenide (GaAs) for the first time on ultrafast time scales down to 50 femtoseconds (1 fs = 10 to the power of -15 seconds). They report their results in the current issue of the journal Physical Review Letters 121, 266602 (2018) . Using ultrashort, intense light pulses from the near infrared (λ = 900 nm) to the visible (λ = 650 nm, orange color), they generated shift currents in GaAs which oscillate and, thus, emit terahertz radiation with a bandwidth up to 20 THz (Figure 2). The properties of these currents and the underlying electron motions are fully reflected in the emitted THz waves which are detected in amplitude and phase. The THz radiation shows that the ultrashort current bursts of rectified light contain frequencies which are 5000 times higher than the highest clock rate of modern computer technology.

The properties of the observed shift currents definitely exclude an intraband motion of electrons or holes. In contrast, model calculations based on the interband transfer of electrons in a pseudo-potential band structure reproduce the experimental results and show that a real-space transfer of electrons over the distance on the order of a bond length represents the key mechanism. This process is operative within each unit cell of the crystal, i.e., on a sub-nanometer length scale, and causes the rectification of the optical field. The effect can be exploited at even higher frequencies, offering novel interesting applications in high frequency electronics.

Brooks Instrument, a developer of advanced flow, pressure, vacuum and vapor delivery solutions, has licensed its direct liquid injection (DLI) vaporizer technology to Ceres Technologies, Inc., headquartered in Saugerties, NY.

The Brooks Instrument DLI vaporizer incorporates unique atomization and heat exchanger technologies to deliver pure vapor for a wide range of processes, including chemical vapor deposition (CVD), metal organic chemical vapor deposition (MOCVD) and atomic layer deposition (ALD). This unique technology has been applied successfully for more than a decade for precise vaporization of a wide range of liquids and liquid precursors. It overcomes the weaknesses of flash vaporizers, which can include thermal decomposition and incomplete vaporization.

Ceres Technologies is a global manufacturer of ultra-high purity gas, vapor and liquid delivery solutions for the semiconductor, compound semiconductor, fiber optic and solar industries. Ceres’ products include gas cabinets, gas blending systems, valve manifold boxes (VMBs) and vapor delivery systems.Ceres’ bulk/centralized vapor delivery systems, such as its VaporGen products based on patented SMR (self-metering reservoir) flash evaporators, and VaporStation™ products based on patented smart bubbler technology, have been used in fabs for more than a decade.

“Ceres’ extensive fluid delivery experience and their broad range of vaporization solutions will continue to expand the market for Brooks Instrument flow control technology,” said Jarek Pisera, Semiconductor Business Unit Manager at Brooks Instrument. “With their system integration capabilities, Ceres is in the unique position of providing customized turnkey solutions for OEMs as well as end-users.”

The Brooks Instrument Quantim™ Coriolis liquid mass flow controller and GF100 Series gas mass flow controller are provided in conjunction with the DLI vaporizer for precise mass flow measurement with fast-response “vapor on demand.”

“Brooks Instrument products are known worldwide for their precision, quality and reliability,” added Kevin Brady, President of Ceres Technologies. “Ceres has incorporated Brooks Instrument products into many of our present product designs. Licensing their DLI vaporizer technology is a key component as we expand our vapor delivery product line into newer liquid precursors.”

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