147 million yuan, Guo Ju announced the acquisition of the United States Pusi Electronics!
According to the micro-network news, on May 22, 2018, Guoju announced the acquisition of a 100% stake in Pulse Electronics of the US for US$740 million (4.7 billion yuan).
Guo Jue purchases Pus Electronics
Guo Guo today held a temporary board of directors and announced that it will acquire 100% equity of Pulse Electronics in the form of cash in 100% of its subsidiary Pluto Merger Corporation, with a total transaction amount of US$740 million.
The two parties signed the contract today and will submit it to the auditing committee after completion of the various preparations. The competent authorities of the Mainland China, the United States, and the German Fair will review it. If successful, the merger will be completed in the fourth quarter as soon as possible. Think electronic performance.
It is understood that PSI Electronics was established in 1947, headquartered in San Diego, the United States, the main products for wireless components (such as 3D printed antenna, laser engraving antenna and various antenna modules), high-end transformers, integrated connector module , High-frequency ceramic inductors, power supplies and cable systems.
PSI Electronics has long been engaged in wireless communication, network equipment, power management, automotive electronics and industrial specifications, and specializes in the development of advanced technologies such as 5G and EV (Electric Vehicle). It has a number of patents in the global region. American Oak Capital The management company (Oaktree) manages the investment portfolio company in April 2015 through its investment fund holding the full equity of PSI Electronics, and in the same year, PSU applied for the New York Stock Exchange to go to the market and turn it into a privatization company.
At present, the company's competitors are all major international companies, among which the high-order transformer competitors are TDK, Delta Electronics and Sumida, the integrated connector competitors are Tyco, Molex and Amphenol, and the high-frequency ceramic resistors are competitors. TDK, Murata, wireless components, antenna components competitor Mitsubishi, Johanson and Jude, wireless module competitor Amphenol and Speed.
Strengthening Guoju Automotive and Industrial Products
According to Zhang Mingjing, a financial officer at Guoge, the acquisition hopes to strengthen Guo Da’s market share in automotive electronics and industrial specifications, and even 5G related applications will have comprehensive effects.
According to Song Zhixiang, the manager of the state-owned giant enterprise development department, PSI Electronics was introduced to the company by Western customers a year ago. After the company’s team assessment, Citi was asked to be the exclusive financial advisor for Guo Guo’s M&A deal. Referring to P&S’s finances, As well as the United States and Japan and other global market prices and corporate valuations, the resolution was purchased for 7.4 billion U.S. dollars in cash.
Guo Ju said that the acquisition of PSI Electronics will increase the company's giant product portfolio. In addition to providing complete passive components, it can also expand and provide customers with electronic components such as wireless components, high-end transformers, and integrated connector modules. Frequency ceramic inductors, power supplies and cable systems are all purchased once, increasing the size and market visibility of Guoju in the United States and Europe, and strengthening the complete layout of Guoju in the automotive electronics and industrial specification niche-based markets. The company's layout and sales channels in the global market will further expand the company's scale of electronic components and operations, and use each other's synergy in technology, process and management.
Giant country's global market layout
In addition to the acquisition of PSI Electronics, before this, Guo Ju held a temporary board of directors on April 27, announcing that it will publicly acquire the listed company Junyao Holdings, which will open the period from May 4 to June 21.
At that time, Guo Dajun's strategy to acquire Jun Yao was to increase the product mix and expand the provision of customer's one-stop shopping service for passive components. Through the layout and sales channels of Guo Ju in the global market, the protective elements of Jun Yao were originally The sales area dominated by China expands to the global market. Continuously strengthening the layout of Guoju in the automotive electronics and industrial specification niche-based market further leverages each other's synergy in technology, process, and management.
Compared with other manufacturers, Guoju is the world's purest chip resistor, MLCC shares, Murata MLCC only 33% of revenue, the business body is diluted by SawFilter, soft board and newly merged lithium-ion battery revenue. Kyocera in addition to MLCC also There are business machines, printers, solar energy, semiconductor packaging, etc. The giant ceramic resistors and MLCC's total revenue accounted for 80% of the total. Even if the current shortage of main products is the medium-to-low-capacity market, if the giant can make up for vehicles, A piece of puzzle will be conducive to medium and long-term operation.
Chairman Chen Taiming of Guoge once stated that in 2018, Guoju will continue to expand the proportion of niche-type products, focus on high-priced and high-mailisity-based products, expand automotive electronics, industrial products, power applications, and cloud-based Internet of Things. Artificial intelligence, virtual reality / augmented reality and other innovative technologies continue to optimize the combination of products and customers, and increase the proportion of high profit-producing products and customer sales.
Looking at these two mergers and acquisitions of Guo Ju, the key words are the product mix, globalization, and automotive and industrial use. It can be seen that the layout of Guo Ju in the automotive and industrial markets is being realized one by one! (Proofreading/Aki)
2.2018 Global Semiconductor Capital Expenditure Will Break Through the $100 Billion Passage for the First Time
Benefiting from the fact that the semiconductor industry is still in a high-end cycle, the market research organization IC insights report pointed out that in 2018, the capital expenditure of the global semiconductor industry will exceed 100 billion US dollars for the first time.
The report said that in March 2018, IC insight had expected that the semiconductor capital expenditure for the entire year of 2018 will grow by 8%. Now, less than a quarter of the time, IC insigh raised its estimate from the original 8%. To 14%. In this way, semiconductor spending in 2018 will break through the $100 billion mark for the first time, and the amount will increase by 53% from 2016.
The report further pointed out that South Korea's Samsung, which has been the leader in semiconductor capital spending for the past two years, has not announced its annual capital expenditure amount in 2018, but generally believes that it will not exceed the 2017 figure of US$24.2 billion. However, As far as the current observations are concerned, Samsung is still struggling to relax.
In fact, Samsung’s semiconductor capital expenditure in the first quarter of 2018 reached US$6.22 billion, slightly higher than the previous three quarters. However, if compared to the same period in 2016, it has grown by nearly four times the scale. Accumulated in the past four quarters , Samsung Semiconductor's capital expenditure has reached 26.6 billion U.S. dollars.
IC insight expects that Samsung Semiconductor's capital expenditure will be around 20 billion yuan in 2018, which is slightly lower than 2017's 24.2 billion US dollars. However, since the first quarter of 2018 had a slightly higher growth than before, the final result is very likely. Will be higher than the expected $20 billion.
In addition, because of the strong market demand for NAND Flash and DRAM, Korean memory maker SK hynix is expected to increase capital expenditures to US$11.5 billion in 2018, a 42% increase from US$8.1 billion in 2017.
The increased capital expenditure of SK hynix in 2018 will be mainly used for the construction of two large-scale memory factories in Cheongju, South Korea. In addition, the DRAM plant in Wuxi, China will also be expanded. The Cheongju plant will start before the end of 2018. Construction, and the expansion of the DRAM plant in Wuxi, China, is also planned to begin by the end of 2018, which will be a few months earlier than originally planned for the start of 2019. Technews
3. Global 5G RF chip business opportunities detonate RF SOI capacity war
As global 5G generations are approaching, continuously driving 8 and 12-inch wafer fabs' capacity demand, not only some wafer fabs will expand their 8-inch factory RF SOI (RF Silicon On Insulator) capacity in order to catch up with strong market demand. , Currently including TSMC, GlobalFoundries, TowerJazz, and UMC, etc., have also expanded or introduced 12-inch RF SOI processes at the same time to fully support the first wave of 5G RF chip order business opportunities. At present, about 95% of all RF SOI chips are manufactured by 8-inch plants. Mobile phone-related RF SOI chips are also mostly manufactured at the 8-inch factory. The vast majority of RF switches and related products are also built at the 8-inch plant, while the RF SOI process is scaled down from 0.18 micron. To 0.13 and 0.11 micron, some products have already switched to 12-inch fabs at this stage. International semiconductor giants include TSMC, GlobalFoundries, TowerJazz, UMC, Sony, SMIC, Huahong Hongli and STMicroelectronics And so on, all of them have 8′′ wafer fabs' RF SOI production capacity. It is noteworthy that recently large-scale foundries have actively introduced 12′′ RF SOI production capacity, including TSMC, GlobalFoundries, TowerJazz and UMC. All of them have started mass production at 12-inch plants and imported process nodes from 0.13 to 45 nm. Semiconductor industry experts pointed out that the chips created by the introduction of RF SOI processes can be locked into different application markets. The most important application is the RF front-end module for mobile phones. End modules), which integrates radio frequency components such as power amplifiers, antenna tuners, low noise amplifiers, radio frequency switches, etc., is responsible for handling functions such as mobile transmission and reception. Currently, the price of mobile radio frequency component chips is about 12~15 dollars, and the future 5G After the advent of smart phones, the price of related chips in mobile phones will reach 18~20 US dollars, which is also one of the reasons for the current RF SOI production capacity. The world's largest RF SOI substrate supplier Soitec, the market share of up to 70%, At the same time, 8 and 12-inch RF SOI substrates are produced. The other two suppliers are Japanese Shin-Etsu and Taichang Universal Wafers. They also supply 8-inch and 12-inch RF SOI substrates. As for Luchang Qinghua, only Supply 8-inch RF SOI substrates. Current RF SOI substrate production capacity is at a bottleneck stage. Whether 8-inch or 12-inch substrates are in a tight supply state, this has limited the ability of foundries to expand production. As for the introduction of RF SOI chips, 12 plant Production, still can not solve the overall RF SOI capacity tight, because the 12-inch plant capacity is mainly locked high-end 5G system applications, part of the production capacity configured in 4G mobile applications. The next 12-inch RF SOI production capacity will be the necessary conditions for the development of 5G applications, for RF SOI In terms of chips, 12-inch plant capacity has many better conditions, including providing more process control and full-automatic control in the fab, and is superior to the 8-inch plant capacity in terms of tolerance, repeatability, and yield. For the tight supply of RF SOI substrates, Thomas Piliszczuk, executive vice president of Soitec, stated that with the approval of partner Qinghua, the 8” RF SOI substrate production capacity is expected to improve in 2019. As for the 12” RF SOI substrate production capacity, Soitec, Shin-Etsu and Universal wafers will increase their capacity, and supply and demand will be tight in 2019. From the point of view of capacity expansion by wafer foundries, more 12-inch RF SOI substrate production capacity will be required, despite Substrate suppliers are willing to expand their production capacity. However, in the short term, 12-inch RF SOI substrate supply is still quite limited. In the face of 5G generations, the 12-foot plant RF SOI capacity competition has started, and wafer foundries have expanded production. In response to strong demand for orders, GlobalFoundries has already introduced RF SOI mass production at two 12-inch plants in East Fishkill, New York State and Singapore, including 0.13 micron and 45-nanometer processes. In fact, GlobalFoundries has pioneered operations in Burlington, Vermont and Singapore. Two 8吋8 plants introduced RF SOI mass production. The purpose was to first place supply chain requirements. While investing 12吋 plants of RF SOI production capacity, they also stabilized their 8吋 plant production capacity to maintain customer orders. TowerJazz already had Shipped 8吋RF SOI, currently launching mass production of RF SOI at its 12-inch plant in Japan, currently focusing on 65nm process, and is expected to shrink down to 45nm. TSMC and UMC have also shipped 8吋RF SOI, And plans to invest 12 吋 RF SOI capacity building competition. DIGITIMES
4. New start-up companies focus on a new computing architecture that combines AI and memory
There are dozens of engineers crowding between coffee shops and beauty salons in the redesignated area of Austin, Texas, to explore new directions in computing technology—this is a start-up company called Mythic. The goal is to have neural networks. The way is mapped to a NOR flash memory array to allow operation and storage of data in a manner that allows savings of two orders of magnitude of power consumption.
If they succeed, the start-up company can skip digital processors and cores from companies such as Intel or other IP providers and many wealthy Chinese start-up companies; the goals of these processors are to station A generation of security cameras, drones, factory equipment and other embedded systems that try to catch up with the artificial intelligence (AI) boom, and even future self-driving vehicles.
'As we learned from the Institute, mixed signal processing is very suitable for this kind of application;' David Fick, who founded Mythic with his colleague Mike Henry at the University of Michigan, said: 'You need to use its adjustable threshold voltage To store large amounts of data and flash memory - each transistor is very attractive.
The flash memory array developed by Mythic basically eliminates the need to move data from external memory into and out of the memory, resulting in significant power savings; Fick said that his advisors David Blaauw and Dennis Sylvester have already conducted some flash memory research. We also have some expertise in technology so it can be very easy to start a project quickly.
However, it is a tricky task to implement the decades-old concept of analog processors in memory. Fick said: 'You must consider many analog effects—mismath, noise, temperature, and memory cells. There are many similar significant effects; ' Unlike digital computers with well-defined memory, processing and storage subsystems, analog computers used in machine learning are basically an integrated and massive project.
'You need to design everything together at the same time, so you need to understand people in overlapping areas, such as understanding component-side design and neural network design engineers in each other's fields;' Fick explained: 'We have outperformed everyone else in this area because We have a super team that can complete the entire task. '
Indeed, the company just completed round B financing and received a sum of up to $50 million in funding, partly because they have a diverse team of director-level experts, including analogies from Texas Instruments. Expert, Microchip's Flash Memory Design Director, and Netronome's Physical Design Specialist.
Dave Fick and his pet dog Ellie at the Austin office; Ellie is director of unofficial emotional support at Mythic (Source: EE Times)
Mythic also won the favor of investors by gradually demonstrating its technological progress through a series of prototype films. Fick won a lot of reputation for VLSI design performance in schools; he said: 'When you design chips as an academic student, including Memory, synthesis, DRC variations... all steps have to be done by yourself; and if you are directly into the industry, you may never see the entire design process, so many independent start-ups from the school will It is easier to successfully mass-produce. '
The two founders of this company have been “geek” since childhood. Fick’s first job in high school was a web development engineer. When he studied at the institute, he entered AMD, IBM and Intel, etc. Born in. Henry is for fun, loves to participate in a variety of fast writing program contests.
Large and small competitors and software obstacles to overcome
These days, Mythic's duo encounters large and small competitors. At least 40 veteran and new IP providers or chip makers have expressed their intention to launch or plan some form of client AI accelerator chip. These competitors also include several wealthy start-up companies in China. Horizon Robotics, for example, is one of the most promising ones. It has introduced a low-power client AI accelerator with a more traditional digital architecture.
There is also a US startup company, Syntiant, who, like Mythic, is developing a processor-in-memory architecture that utilizes flash memory. The company's team includes several former Broadcom engineering managers and has received Intel Capital. In addition, IBM Research is also studying machine learning accelerators based on Resistive RAM (ReRAM), but Fick believes that the company used the wrong method.
He said: 'They are trying to make everything easy with the perfect memory, but we are leading through designing everything together... even if they find the ideal memory, there will always be a less than perfect memory to support Lower power consumption or faster speed. '
Innovative parallel memories have historically always failed because of too difficult programming. Emerging in-memory processor chips will certainly face the same problem, because machine learning itself requires a new, still developing programming model. Although Mythic's tools are To develop the platform, but to play a role like a compiler, it can convert the neural network described in the TensorFlow database into a machine language for its chips.
Fick said that the development platform uses PCI Express and chip connectivity to provide hints on how to obtain additional performance from the chip, as well as optimized networking examples for some common applications. Customers who want to use a framework other than TensorFlow will obviously Need to use ONNX format to translate its tasks; ONNX (Open Neural Network Exchange) is one of the few emerging tools used to translate several different AI software architectures.
Fick is also fully aware of the software barriers facing his customers: 'In order to enter this field, you need to employ several deep learning scientists, but such experts are very scarce, and the cost is very expensive... Establishing data sets and neural nets Roads and training are very time consuming and costly... these are all the limits to venture into and invest in this area.'
The good news is that, compared with competing solutions, the memory array of Mythic chips should be able to handle more diverse convolutional or recurrent neural networks, and its performance improvement is expected to be achieved in power consumption. Restricted edge systems perform more complex models.
Mythic has several test chips to date (Source: EE Times)
Mythic has several heavyweight partners, such as Lockheed Martin, who hopes that future drones can use the company's chips, and Fujitsu, the company's flash memory supplier. So far, there are two The application seems to be beyond its scope. One is a smart speaker with a budget of only a few dollars. Compared with Mythic's target application, it is too costly to control; the other is a self-driving vehicle. Because of the need for vehicle grade specifications, the company is currently unable to Born.
The start-up is expected to introduce a 40nm process chip later this year. This node supports embedded flash memory cell design and also meets low-cost targets. Fick pointed out that its flash memory cell has passed 28nm process quality certification. This will be the company's next step; after that, the foundry industry is developing embedded MRAN and ReRAM units.
Fick said: “There is no reason to stop us from moving forward with the smallest node. We can benefit from the process miniaturization; 'And if Mythic succeeds, it’s not because Moore’s Law or those digital processors make them Welcome, but it will be because they are pushing computing technology to a whole new direction. eettaiwan
Compilation: Judith Cheng
(Reference: Startup Maps AI into Flash Array, by Rick Merritt)
5. Intelligent sensing and identification technology multiple AIoT open application opportunities
The convergence of Artificial Intelligence (AI) and Internet of Things (IoT) convergence into AIoT, the driving force for the formation of intelligent applications has become a hot topic today. With the progress of machine vision, deep learning and various sensing and identification software and hardware technologies, IoT has been developed. The system gradually evokes human emotions and immediate reactions, and promotes the promotion of smart manufacturing related technologies and product services, and opens up more potential market application opportunities.
IEK of Taiwan ITRI and Yole Development, a well-known MEMS & Sensor research and consulting company in France, conducted international cooperation and organized the “AIoT Drive Intelligent Sensing and Identification Application Business Seminar” on 5/22 in order to achieve a complete and comprehensive analysis. What are the opportunities for intelligent sensing and identification of the market driven by the AIoT trend, how to carefully select the technologies that are suitable for future industrial development, and the key to finding potential applications?
Luo Zonghui, an IEK industrial analyst at the Industrial Technology Research Institute of ITRI, discussed the key technical aspects of image recognition. He stated that in the key components of image recognition, it includes cameras, image processors and sensors. It is estimated that in 2018 The demand for CIS will reach the number of 4.5 billion to 5 billion, the quality of the original data (such as sensitivity region, constituent factors, pixels, frame rate, energy consumption, etc.) and the correctness and efficiency of analysis (computer operations, algorithms, AI, etc.) will become the key to the competition among various manufacturers. After all, the user cares about the speed, resolution, accuracy and function, such as the clear and fast speed of the dynamic range.
As for the two major values brought by image analysis technology, such as vertical application in mobile devices, automotive applications, security monitoring, industrial applications, biomedicine, logistics and robotics, as well as solving problems, mainly defect detection and image segmentation. / Edge detection, dynamic analysis, position or direction analysis, etc. Among them, image inspection defects are common in industrial applications and biomedical fields.
Observed from various industries, real-time image analysis has been popularized in various products. Luo Zonghui proposed three characteristics of image recognition technology development: 1. Professionalism: Accuracy and immediacy are even higher: 2. Popularity: New applications Continuously Created: 3. Security: Privacy and Business Applications Pull.
With regard to the trend of emerging human-machine interface (HMI) sensing and identifying business opportunities, Xie Mengxi, senior industry analyst at ITRI, said that the human-machine interface has been transformed from simple device control to virtual reality integration/digital multiplex innovation application type, and the future five-sensing sensing function Will accelerate the introduction of more new-style wearable devices and smart machines to expand more business opportunities.
Xie Mengxi used the MIT Media Lab's wearable mind reading as an example to illustrate the future appearance of the human-machine interface. He hopes to achieve the control of using the 'heart (brain)' as he likes. This goal must be based on five senses (visual, auditory). Based on the combination of Bio-Electronics (Biomedical Detection) and biometrics technologies, will be able to fully initiate the innovative applications of emerging human-machine interface sensing and identification technologies in the next stage, such as Face / iris / eye pattern / retina recognition, speech / ear canal identification, fingerprint / gesture recognition, vein recognition, keyboard typing habit identification, gait recognition, etc. He believes that the future will not tend to a specific category of biometrics, and It is multiple recognition and can play a modest application in different situations.
Capacitance, optics, ultrasound, and three fingerprint identification technologies each outsmart the field. Among them, the capacitive cost/power consumption is the lowest, the optical penetration ability is the strongest, the ultrasonic anti-jamming effect is the best, and the optical and ultrasonic fingerprinting technology is already Began to integrate physiological monitoring functions, such as heart rate, blood flow, etc. Factors such as dry skin, finger pressure, skin contamination, and sweat all affect the fingerprint recognition rate, which in turn drives OLED microdisplay fingerprint recognition technology, for example, curved fingerprint recognition displays. , Live fingerprint identification, non-contact 3D fingerprints and other emerging technologies, the next generation of fingerprint recognition technology is poised to take off.
In addition to fingerprint recognition, Luo Zonghui said that face recognition will be the focus of the next vendor integration, such as the evolution of access control systems toward integrated face recognition. For example, Klacci, a traditional mechanical access control manufacturer, has been facing cross-cutting development and integrating many resources. Communication Technology.
With the continuous improvement of perception/AI technology, Xie believes that the combination of biometric recognition with behavior recognition and AI/deep learning will accelerate the human-computer interface into the new era of human-computer collaboration and human-computer emotion communication applications, and drive more software. The technological innovation of the algorithm. The influence of research institutions and new start-up companies with technological capabilities in the future will increase, attracting more international companies to cooperate, acquire or invest strategic layouts, in order to maintain the leading edge in the existing industry.
In addition, Jerome Mouly, Technical and Market Analyst, Life Sciences & Healthcare Division, Yole Development Consultant Company, conducted an in-depth discussion on the topic of "Analysis of Application Trends and Market Opportunities of Biomedical Sensors for Mobile Health Care Services" to analyze home medical materials, wear health management, and personalize diagnostics. All Bio Sensor technology application development priorities are required. He said that medical care will change with social evolution and new technologies. Low power consumption, miniaturized bioMEMS and sensors have been developed from other markets, but sensor performance (such as measurement accuracy ) Integration is the key to FDA-approved medical devices. Most technology blocks are available today, and the industry chain is becoming more and more mature. As for consumer healthcare, it is the key to developing specific medical sensors to reduce the acceptable cost of sensors. CTIMES