Intel and Tower Announce Foundry Agreement

Photo above: Intel’s Fab 11X in Rio Rancho, New Mexico. Credit: Intel Inc.

Less than a month after the termination of a planned merger between Intel and Tower Seniconductor, the two companies announced a largescale production agreement: Intel will provide foundry services and 300mm manufacturing capacity to help Tower serve its customers globally. Tower will utilize Intel’s manufacturing facility in Rio Rancho, New Mexico (Fab 11X), and will invest up to $300 million to acquire and own equipment and other fixed assets to be installed in the facility.

The rearranement of the fab will provide production capacity of over 600,000 photo layers per month. Intel will manufacture Tower’s 65-nanometer power management BCD (bipolar-CMOS-DMOS) and radio frequency silicon on insulator (RF SOI) solutions flows. Stuart Pann, Intel senior vice president and general manager of Intel Foundry Services (IFS) explained during Goldman Sachs Communacopia & Technology Conference this week, that intel had unused capacity in Fab 11X, because it is an older factory for older technologies.

Initial Production in 2025

Pann: “We found a way to do contract manufacturing to take advantage of that extra space. Those older tools that we aren’t using, taking some investment from Tower to finish out the line.” The parties plan to achieve full process flow qualification in 2024, and to begin with full mass production in 2025. Tower CEO Russell Ellwanger said: “We see this collaboration as a first step towards multiple unique synergistic solutions with Intel.”

Tower provides foundry services for Analog semicinductor devices. It offers a broad range of customizable process platforms such as SiGe, BiCMOS, mixed-signal/CMOS, RF CMOS, CMOS image sensor, non-imaging sensors, integrated power management (BCD and 700V), and MEMS. Tower owns two manufacturing facilities in Israel (150mm and 200mm), two in the U.S. (200mm), two facilities in Japan (200mm and 300mm) which it owns through its 51% holdings in TPSCo and is sharing with ST a 300mm manufacturing facility in Italy .

Intel Announced the Termination of Tower’s Acquisition

After it had failed to recieve the needed approval of Chinese regulators, , Intel Corporation announced that it has mutually agreed with Tower Semiconductor to terminate its previously disclosed agreement to acquire Tower. On February 15, 2022 Intel and Tower Semiconductor announced a definitive agreement under which Intel will acquire Tower for $53 per share in cash, representing a total enterprise value of approximately $5.4 billion. The aimed to strenthen Intel’s IDM 2.0 strategy to become a leading chip production services provider (foundry).

But during the last 18 months, the US-China tension proved to be a stronger force than Intel’s ambitions, and even after the deal had received across the board approvals, the Chinese authorities made no effort to proceed, and actually waited until it will be clear that no approvel is expexted to be given in the near future. “Our respect for Tower has only grown through this process” said Pat Gelsinger, CEO of Intel, “and we will continue to look for opportunities to work together in the future.”

Russell Ellwanger, Tower Semiconductor CEO, said: “We appreciate the efforts by all parties.  During the past 18 months, we’ve made significant technological, operational, and business advancements. We are well positioned to continue to drive our strategic priorities and short-, mid- and long-term tactics with a continued focus on top and bottom-line growth.”

Tower Semiconductor provides a broad range of customizable process platforms such as SiGe, BiCMOS, mixed-signal/CMOS, RF CMOS, CMOS image sensor, non-imaging sensors, integrated power management (BCD and 700V), and MEMS. It owns two manufacturing facilities in Israel (150mm and 200mm), two in the U.S. (200mm), three facilities in Japan (two 200mm and one 300mm) which it owns through its 51% holdings in TPSCo and is sharing a 300mm manufacturing facility being established in Italy with ST.

During the last year it faced a slight decline in sales, from $847 millions in H1 2022, to approximately $713 million in H1 2023. until this morning Tower was traded in NASDAQ in valuation of 3.85 billion – 20% below the deal valuation. It means that many investors preculated the deal will fail. Following the deal termination, Tower’s share lost additional 10%, bringing its valuation to approximately $3.5 billion


Intel Names Shlomit Weiss GM of Design Engineering

Intel announced that Shlomit Weiss, senior vice president and co-general manager (GM) of the Design Engineering Group (DEG), will replace senior vice president Sunil Shenoy, who will retire at the end of the year. Weiss will lead the company’s design, development, validation and manufacturing support of intellectual properties (IPs) and system-on-chips (SoCs), reporting directly to Intel CEO Pat Gelsinger and joining the company’s executive leadership team.

Weiss has spent 28 years at Intel in engineering and leadership roles, including as leader of cross-site teams responsible for IP and discrete data center products, and general manager of data center group silicon development. She played a major role in the development of some of Intel’s most successful processors, including Sandy Bridge (2006) and Sky Lake (2015). In 2017 she joined Mellanox, now part of Nvidia, as Senior VP for Silicon Engineering.

Last year Shlomit had returned to Intel as co-GM of DEG with Shenoy, specifically leading client product design engineering and the Intel architecture core portfolio used across client, data center and other segments. “The design engineering organization requires a leader with deep technical expertise and passion for engineering excellence, and Shlomit has that in spades,” Gelsinger said.

Intel to Acquire Israel-based Granulate

Intel Corporation announced an agreement to acquire Granulate Cloud Solutions, an Israel-based developer of real-time continuous optimization software. The acquisition of Granulate will help cloud and data center customers maximize compute workload performance and reduce infrastructure and cloud costs. Deal terms are not being disclosed, but it is expected to close in the second quarter of 2022. At that time, Granulate’s 120 employees will be integrated into Intel’s Datacenter and AI business unit.

Sandra Rivera, GM of the Datacenter and AI Group at Intel, said that Granulate’s autonomous optimization software can be applied to production workloads without the need to make changes in the customer’s code. Greg Lavender, GM of the Software and Advanced Technology Group at Intel, explained that Granulate’s real-time optimization software complements Intel’s capabilities by helping customers to gain performance and reduce Cloud costs.

How It Works

Granulate’s real-time continuous optimization is a new approach to optimizing production workloads by leveraging resource usage patterns and dataflow to automatically adapt kernel level and runtime level resource management to better fit the application needs. It automatically learns the application’s specific resource usage patterns and data flow to identify contended resources, bottlenecks and prioritization opportunities, and then tailors OS-level scheduling and prioritization decisions to improve the infrastructure’s application specific performance.

Accelerating Legacy Packages

While cloud computing and microservices have created a new era of flexibility in distributed applications and deployment scalability, modern architectures have introduced more complex performance issues that are not easily managed by traditional operating systems and runtimes. Additionally, customers often deploy older Linux distributions and application libraries that are not up to date with the latest advancements in today’s high-performance CPUs.

Granulate’s autonomous optimization service solves these issues by reducing CPU utilization and application latencies, by learning the customer’s application and deploying a customized set of continuous optimizations at runtime. This enables deployment on smaller compute clusters and instance types to improve application performance and drive down cloud and data center costs, without the developer intervention. Thus, optimizations for the latest CPUs can be applied even on legacy Linux distributions and runtimes.

Optimizing Xeon deployments

Asaf Ezra, co-founder and CEO of Granulate, said: “As a part of Intel, Granulate will be able to deliver autonomous optimization capabilities to even more customers globally and rapidly expand its offering with the help of Intel’s 19,000 software engineers.” Intel and Granulate’s relationship began in late 2019, when Granulate was part of the first graduating class of Intel® Ignite, the startup accelerator program that taps into Intel’s resources.

Over the past year, Intel and Granulate have worked together under a commercial agreement to collaborate on workload optimization on Xeon deployments. This collaboration resulted in gains in performance and decreases in costs for customers running on Intel processors. With the acquisition of Granulate, Intel will rapidly scale Granulate’s optimization software, including across Intel’s data center portfolio.

Deci launches new models for enhancing Deep Learning on CPU 

Photo above:Deci’s founders (from left to right): Jonathan Elial- COO, Yonatan Giefman- CEO and Ran El Yaniv- Chief scientist. Credit: Deci

Deci, the deep learning company harnessing Artificial Intelligence (AI) to build AI, announced a new set of image classification models, dubbed DeciNets, for Intel Cascade Lake CPUs. According to Deci, its proprietary Automated Neural Architecture Construction (AutoNAC) technology automatically generated the new image classification models that significantly improve all published models and deliver more than 2x improvement in runtime, coupled with improved accuracy, as compared to the most powerful models publicly available such as EfficientNets, developed by Google.

While GPUs have traditionally been the hardware of choice for running convolutional neural networks (CNNs), CPUs, already more commonly utilized for various computing tasks, would serve as a much cheaper alternative. Although it is possible to run deep learning inference on CPUs, generally they are significantly less powerful than GPUs. Consequently, deep learning models typically perform 3-10X slower on a CPU than on a GPU.

As explained by Deci, its DeciNets closes the gap significantly between GPU and CPU performance for CNNs. With DeciNets, tasks that previously could not be carried out on a CPU because they were too resource intensive are now possible. Additionally, these tasks will see a marked performance improvement: by leveraging DeciNets, the gap between a model’s inference performance on a GPU versus a CPU is cut in half, without sacrificing the model’s accuracy.

“As deep learning practitioners, our goal is not only to find the most accurate models, but  to uncover the most resource-efficient models which work seamlessly in production – this combination of effectiveness and accuracy constitutes the ‘holy grail’ of deep learning,” said Yonatan Geifman, co-founder and CEO of Deci. “AutoNAC creates the best computer vision models to date, and now, the new class of DeciNets can be applied and effectively run AI applications on CPUs.”

All networks were compiled and quantized using OpenVino, with latency measured on AWS instance c5.4xlarge with Cascade Lake CPU (16 vCPUs, batch size = 1)

“There is a commercial, as well as academic desire, to tackle increasingly difficult AI challenges. The result is a rapid increase in the complexity and size of deep neural models that are capable of handling those challenges,” said Prof. Ran El-Yaniv, co-founder and Chief Scientist of Deci and Professor of Computer Science at the Technion – Israel Institute of Technology. The hardware industry is in a race to develop dedicated AI chips that will provide sufficient compute to run such models; however, with model complexity increasing at a staggering pace, we are approaching the limit of what hardware can support using current chip technology. Deci’s AutoNAC creates powerful models automatically, giving users superior accuracy and inference speed even on low-cost devices, including  traditional CPUs.”

In March 2021, Deci and Intel announced a broad strategic collaboration to optimize deep learning inference on Intel Architecture (IA) CPUs. Prior to this, Deci and Intel worked together at MLPerf, where on several popular Intel CPUs, Deci’s AutoNAC technology accelerated the inference speed of the well-known ResNet50 neural network, reducing the submitted models’ latency by a factor of up to 11.8x and increasing throughput by up to 11x.

Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company’s end-to-end deep learning development platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to revolutionize industries with innovative products.  The platform is powered by Deci’s proprietary automated Neural Architecture Construction technology (AutoNAC), which automatically generates and optimizes deep learning models’ architecture and allows teams to accelerate inference performance, enable new use cases on limited hardware, shorten development cycles and reduce computing costs. Founded by Yonatan Geifman, Jonathan Elial, and Professor Ran El-Yaniv, Deci’s team of deep learning engineers and scientists are dedicated to eliminating production-related bottlenecks across the AI lifecycle.

Intel to Acquire Tower for $5.4 Billion

Intel and Tower Semiconductor (based in Migdal Haemek, Israel), announced a definitive agreement under which Intel will acquire Tower for $53 per share in cash, representing a total enterprise value of approximately $5.4 billion. The acquisition supports Intel’s IDM 2.0 strategy to build a foundry services business. “Tower’s specialty technology portfolio, geographic reach and deep customer relationships will help scale Intel’s foundry services and advance our goal of becoming a major provider of foundry capacity globally,” said Pat Gelsinger, Intel CEO.

As a key part of its IDM 2.0 strategy, Intel established Intel Foundry Services (IFS) in March 2021 to become a major provider of U.S.- and Europe-based foundry capacity to serve customers globally. IFS currently offers leading-edge process and packaging technology, and a broad intellectual property (IP) portfolio. The transaction is expected to close in approximately 12 months. It has been unanimously approved by Intel’s and Tower’s boards of directors and is subject to regulatory approvals, including the approval of Tower’s stockholders.

Tower Semiconductor provides a broad range of customizable process platforms such as SiGe, BiCMOS, mixed-signal/CMOS, RF CMOS, CMOS image sensor, non-imaging sensors, integrated power management (BCD and 700V), and MEMS. It owns two manufacturing facilities in Israel (150mm and 200mm), two in the U.S. (200mm), three facilities in Japan (two 200mm and one 300mm) which it owns through its 51% holdings in TPSCo and is sharing a 300mm manufacturing facility being established in Italy with ST.

“With the addition of Tower, Intel is strongly positioned to bring more value to customers across the nearly $100 billion addressable foundry market.”

“Taking Mobileye public is admitting Intel’s failure”

Intel’s intention to take Mobileye public in mid 2022, less than 5 years after its acquisition, continues to resonate and raises questions regarding the direction its current CEO, Pat Gelsinger, is leading the company. In light of the major importance Intel attributed to Mobileye in its future plans, it seems that the expected offering is not a single move; rather it is a sharp u-turn from the strategy led in the past years by the two former CEOs.

In a recent conversation with Techtime, Sergey Vastchenok – Senior Equity Analyst at Oppenheimer Israel explained that the expected offering is the price Intel pays for its mistakes in recent years. “In the recent years, Intel lagged behind its major competitors in the manufacturing world, mainly TSMC and Samsung, with regard to capital expenditures (Capex). This process led Intel to lose its technological advantage”.  

“New CEO, Pat Gelsinger, who grew within Intel and is part of its genetics, came with a vision of reviving its past market dominance, and he did so by massively increasing investments in the company’s organic capabilities”.

Sergey Vastchenok, Oppenheimer Israel

The diminution in Intel’s status is reflected very clearly in its share performance in recent years. In the past 5 years, Intel’s share raised by only 47% whiles the Philadelphia Stock Exchange (PHLX) index, grouping leading chip companies, raised by 354%. Nvidia and AMD, Intel direct competitors, raised by 1300% within the same period.

Vastchenok: “Intel plans to invest 20-25 billion annually in the coming years to restore the lost advantage. Since the company is deficient with cash, the main question is how to finance the planned increase in investments.  Increasing its debt may harm the company’s credit rating, while additional offering in the stock market may weaken its already weak share. The best method of raising funds is to start selling assets”.

Mobileye is a perfect asset to sell

According to Vastchenok, selling Mobileye is a rational step, since its market value is considerably high, and since there was never a real synergy between the two companies’ core activities. Not only there was no real synergy, one may say that it was even a negative one, since Mobileye buy its chips from TSMC and not from Intel. This led to the situation where Intel financed Mobileye’s development strategy, while TSMC benefit the production orders”.   

“Mobileye is a growing business, and is considered a pioneer and a leader in the advanced driver-assistance systems (ADAS) world. Yet, it is still difficult to forecast its revenues and its market share in the future autonomous vehicle world, since there are many competitors nowadays. Every technology giant is joining the game. At this situation, if the market is willing to pay a good price for your assets – you better sell. If Intel is going to make it public at the mentioned price, it could significantly enlarge its cash reserves. This move will do well for both Intel and Mobileye. Mobileye has better chance to prosper outside Intel’s wings. As we can see, since it was acquired by Intel they have lost plenty of quality human resources, the same way Intel lost human resources for its competitors”.

What is the future of Moovit?

Selling Mobileye raises questions regarding the future of other companies bought by Intel in the recent years. In May 2020 Intel acquired Moovit – the Israeli public transport platform – for $900 million. This surprising acquisition presented as another step in Intel’s vision to provide Mobility-as-a-Service (MaaS) services in the future, based on Mobileye’s autonomous vehicles and Moovit’s application. In fact, it seems that the real synergy is between Mobileye and Moovit. “Almost all the acquisitions made by Intel at the past years, to include FPGA vendor Altera, were not related to the core activities of Intel. Taking Mobileye public is an admission of the failure of the acquisition strategy of recent years. It looks like the current CEO is being aware of Intel core expertise and what should they focus at”.