JEDEC and the Open Compute Project rolled out a new set of guidelines for standardizing chiplet characterization details, such as thermal properties, physical and mechanical requirements, and behavior specs. Those details have been a sticking point for commercial chiplets, because without them it’s not possible to choose the best chiplet for a particular application or workload. The guidelines are a prerequisite for a multi-vendor chiplet marketplace.

AMD, Broadcom, Cisco, Google, HPE, Intel, Meta, and Microsoft proposed a new high-speed, low-latency interconnect specification, Ultra Accelerator Link (UALink), between accelerators and switches in AI computing pods. The 1.0 specification will enable the connection of up to 1,024 accelerators within a pod and allow for direct loads and stores between the memory attached to accelerators.

Arm debuted a range of new CPUs, including the Cortex-X925 for on-device generative AI, and the Cortex-A725 with improved efficiency for AI and mobile gaming. It also announced the Immortalis-G925 GPU for flagship smartphones, and the Mali-G725/625 GPUs for consumer devices. Additionally, Arm announced Compute Subsystems (CSS) for Client to provide foundational computing elements for AI smartphone and PC SoCs, and it introduced KleidiAI, a set of compute kernels for developers of AI frameworks. The Armv9-A architecture also added support for the Scalable Matrix Extension to accelerate AI workloads.

TSMC said its 2nm process is on target to begin mass production in 2025. Meanwhile, Samsung is expected to release its 1nm plan next month, targeting mass production for 2026 — a year ahead of schedule, reports Business Korea.

CHIPs for America and NATCAST released a 2024 roadmap for the U.S. National Semiconductor Technology Center (NSTC), identifying priorities for facilities, research, workforce development, and membership.

China is investing CNY 344 billion (~$47.5 billion) into the third phase of its National Integrated Circuit Industry Investment Fund, also known as the Big Fund, to support its semiconductor sector and supply chain, according to numerous reports.

Malaysia plans to invest $5.3 billion in seed capital and support for semiconductor manufacturing in an effort to attract more than $100 billion in foreign investments, reports Reuters. Prime Minister Anwar Ibrahim announced the effort to create at least 10 companies focused on IC design, advanced packaging, and equipment manufacturing.

imec demonstrated a die-to-wafer hybrid bonding flow for Cu-Cu and SiCN-SiCN at pitches down to 2µm at the IEEE’s ECTC conference. This breakthrough could enable die and wafer-level optical interconnects.

The chip industry is racing to develop glass for advanced packaging, setting the stage for one of the biggest shifts in chip materials in decades — and one that will introduce a broad new set of challenges that will take years to fully resolve.

Quick links to more news:

In-Depth
Global
Product News
Markets and Money
Security
Research and Training
Quantum
Events and Further Reading

In-Depth

Semiconductor Engineering published its Systems & Design newsletter featuring these top stories:

• RISC-V Heralds New Era Of Cooperation
• AI For Data Management
• Trouble Ahead For IC Verification

Global

STMicroelectronics is building a fully integrated SiC facility in Catania, Italy.  The high-volume 200mm facility is projected to cost over $5 billion.

Siliconware Precision Industries Co. Ltd.(SPIL) broke ground on an RM 6 billion (~$1.3 billion) advanced packaging and testing facility in Malaysia. Also, Google will invest $2 billion in Malaysia for its first data center, and a Google Cloud hub to meet growing demand for cloud services and AI literacy programs, reports AP.

In an SEC filing, Applied Materials received additional subpoenas from the U.S. Department of Commerce’s (DoC) Bureau of Industry and Security related to shipments of advanced semiconductor equipment to China. This comes on the heels of similar subpoenas issued last year.

A Chinese contractor working for SK hynix was arrested in South Korea and is being charged with funneling more than 3,000 copies of a paper on solving process failure issues to Huawei, reports South Korea’s Union News.

VSORA, CEA-Grenoble, and Valeo were awarded $7 million from the French government to build low-latency, low-power AI inference co-processors for autonomous driving and other applications.

In the U.S., the National Highway Traffic Safety Administration (NHTSA) is investigating unexpected driving behaviors of vehicles equipped with Waymo‘s 5th Generation automated driving system (ADS), with details of nine new incidents on top of the first 22.

Product News

ASE introduced powerSIP, a power delivery platform designed to reduce signal and transmission loss while addressing current density challenges.

Infineon announced a roadmap for energy-efficient power supply units based on Si, SiC, and GaN to address the energy needs of AI data centers, featuring new 8 kW and 12 kW PSUs, in addition to the 3 kW and 3.3 kW units available today. The company also released its CoolSiC MOSFET 400 V family, specially developed for use in the AC/DC stage of AI servers, complementing the PSU roadmap.

Fig. 1: Infineon’s 8kW PSU. Source: Infineon

Infineon also introduced two new generations of high voltage (HV) and medium voltage (MV) CoolGaN TM devices, enabling customers to use GaN in voltage classes from 40 V to 700 V. The devices are built using Infineon’s 8-inch foundry processes.

Ansys launched Ansys Access on Microsoft Azure to provide pre-configured simulation products optimized for HPC on Azure infrastructure.

Foxconn Industrial Internet used Keysight Technology’s Open RAN Studio solution to certify an outdoor Open Radio Unit (O-RU).

Andes Technology announced an SoC and development board for the development and porting of large RISC-V applications.

MediaTek uncorked a pair of mobile chipsets built on a 4nm process that use an octa-core CPU consisting of 4X Arm Cortex-A78 cores operating at up to 2.5GHz paired with 4X Arm Cortex-A55 cores.

The NVIDIA H200 Blackwell platform is expected to begin shipping in Q3 of 2024 and will be available to data centers by Q4, according to TrendForce.

A room-temperature direct fusion hybrid bonding system from Be Semiconductor has shipped to the NHanced advanced packaging facility in North Carolina. The new system offers faster throughput for copper interconnects with submicron pad sizes, greater accuracy and reduced warpage.

Markets and Money

Frore Systems raised $80 million for its solid-state active cooling module, which removes heat from the top of a chip without fans. The device in systems ranging from notebooks and network edge gateways to data centers.

Axus Technology received $12.5 million in capital equity funding to make its chemical mechanical planarization (CMP) equipment for semiconductor wafer polishing, thinning, and cleaning, including of silicon carbide (SiC) wafers.

Elon Musk’s xAI announced a series B funding round of $6 billion.

Micron was ordered to pay $445 million in damages to Netlist for patent infringement of the company’s DDR4 memory module technology between 2021 and 2024.

Global revenue from AI semiconductors is predicted to total $71 billion in 2024, up 33% from 2023, according to Gartner. In 2025, it is expected to jump to $91.9 billion. The value of AI accelerators used in servers is expected to total $21 billion in 2024 and reach $33 billion by 2028.

NAND flash revenue was $14.71 billion in Q1 2024, an increase of 28.1%, according to TrendForce.

The optical transceiver market dipped from $11 billion in 2022 to $10.9 billion in 2023, but it is predicted to reach $22.4 billion by 2029, driven by AI, 800G applications, and the transition to 200G/lane ecosystem technologies, reports Yole.

Yole also found that ultra-wideband technical choices and packaging types used by NXP, Apple, and Qorvo vary considerably, ranging from 7nm to 90nm, with both CMOS and finFET transistors.

The global market share of GenAI-capable smartphones increased to 6% in Q1 2024 from 1.3% in the previous quarter, reports Counterpoint. The premium segment accounted for over 70% of sales with Samsung on top and contributing 58%. Meanwhile, global foldable smartphone shipments were up 49% YoY in Q1 2024, led by Huawei, HONOR, and Motorola.

Security

The National Science Foundation awarded Worcester Polytechnic Institute researcher Shahin Tajik almost $0.6 million to develop new technologies to address hardware security vulnerabilities.

The Hyperform consortium was formed to develop European sovereignty in post-quantum cryptography, funded by the French government and EU credits. Members include IDEMIA Secure Transactions, CEA Leti, and the French cybersecurity agency (ANSSI).

In security research:

• University of California Davis and University of Arizona researchers proposed a framework leveraging generative pre-trained transformer (GPT) models to automate the obfuscation process.
• Columbia University and Intel researchers presented a secure digital low dropout regulator that integrates an attack detector and a detection-driven protection scheme to mitigate correlation power analysis.
• Pohang University of Science and Technology (POSTECH) researchers analyzed threshold switch devices and their performance in hardware security.

The U.S. Defense Advanced Research Projects Agency (DARPA) seeks proposals for its AI Quantified program to develop technology to help deploy generative AI safely and effectively across the Department of Defense (DoD) and society.

Vanderbilt University and Oak Ridge National Laboratory (ORNL) partnered to develop dependable AI for national security applications.

The Cybersecurity and Infrastructure Security Agency (CISA) issued a number of alerts/advisories.

Research and Training

New York continues to amp up their semiconductor offerings. NY CREATES and Raytheon unveiled a semiconductor workforce training program. And Syracuse  University is hosting a free virtual course focused on the semiconductor industry this summer.

In research news:

• A team of researchers at MIT and other universities found that extreme temperatures up to 500°C did not significantly degrade GaN materials or contacts.
• University of Cambridge researchers developed adaptive and eco-friendly sensors that can be directly and imperceptibly printed onto biological surfaces, such as a finger or flower petal.
• Researchers at Rice University and Hanyang University developed an elastic material that moves like skin and can adjust its dielectric frequency to stabilize RF communications and counter disruptive frequency shifts that interfere with electronics when a substrate is twisted or stretched, with potential for stretchable wearable electronic devices.

The National Science Foundation (NSF) awarded $36 million to three projects chosen for their potential to revolutionize computing. The University of Texas at Austin-led project aims to create a next-gen open-source intelligent and adaptive OS. The Harvard University-led project targets sustainable computing. The University of Massachusetts Amherst-led project will develop computational decarbonization.

Quantum

Singapore will invest close to S$300 million (~$222 million) into its National Quantum Strategy to support the development and deployment of quantum technologies, including an initiative to design and build a quantum processor within the country.

Several quantum partnerships were announced:

• Riverlane and Alice & Bob will integrate Riverlane’s quantum error correction stack within Alice & Bob’s larger quantum computing system based on cat qubit technology.
• New York University and the University of Copenhagen will collaborate to explore the viability of hybrid superconductor-semiconductor quantum materials for the production of quantum chips and integration with CMOS processes.
• NXP, eleQtron, and ParityQC showed off a full-stack, ion-trap based quantum computer demonstrator for Germany’s DLR Quantum Computing Initiative.
• Photonic says it demonstrated distributed entanglement between quantum modules using optically-linked silicon spin qubits with a native telecom networking interface as part of a quantum internet effort with Microsoft.
• Classiq and HPE say they developed a rapid method for solving large-scale combinatorial optimization problems by combining quantum and classical HPC approaches.

Events and Further Reading

Find upcoming chip industry events here, including:

Upcoming webinars are here, including integrated SLM analytics solution, prototyping and validation of perception sensor systems, and improving PCB designs for performance and reliability.

Semiconductor Engineering’s latest newsletters:

Automotive, Security and Pervasive Computing
Systems and Design
Low Power-High Performance
Test, Measurement and Analytics
Manufacturing, Packaging and Materials

The post Chip Industry Week In Review appeared first on Semiconductor Engineering.

Enlarge (credit: Getty Images)

On Thursday, several major tech companies, including Google, Intel, Microsoft, Meta, AMD, Hewlett-Packard Enterprise, Cisco, and Broadcom, announced the formation of the Ultra Accelerator Link (UALink) Promoter Group to develop a new interconnect standard for AI accelerator chips in data centers. The group aims to create an alternative to Nvidia's proprietary NVLink interconnect technology, which links together multiple servers that power today's AI applications like ChatGPT.

The beating heart of AI these days lies in GPUs, which can perform massive numbers of matrix multiplications—necessary for running neural network architecture—in parallel. But one GPU often isn't enough for complex AI systems. NVLink can connect multiple AI accelerator chips within a server or across multiple servers. These interconnects enable faster data transfer and communication between the accelerators, allowing them to work together more efficiently on complex tasks like training large AI models.

This linkage is a key part of any modern AI data center system, and whoever controls the link standard can effectively dictate which hardware the tech companies will use. Along those lines, the UALink group seeks to establish an open standard that allows multiple companies to contribute and develop AI hardware advancements instead of being locked into Nvidia's proprietary ecosystem. This approach is similar to other open standards, such as Compute Express Link (CXL)—created by Intel in 2019—which provides high-speed, high-capacity connections between CPUs and devices or memory in data centers.

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The question on everyone's mind is what company is Intel's marquee foundry customer?
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The question on everyone's mind is what company is Intel's marquee foundry customer?
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The post Who is the first big customer for Intel’s foundry efforts? appeared first on SemiAccurate.

The question on everyone's mind is what company is Intel's marquee foundry customer?
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The post Who is the first big customer for Intel’s foundry efforts? appeared first on SemiAccurate.

Chiplets are gaining renewed attention in the automotive market, where increasing electrification and intense competition are forcing companies to accelerate their design and production schedules.

Electrification has lit a fire under some of the biggest and best-known carmakers, which are struggling to remain competitive in the face of very short market windows and constantly changing requirements. Unlike in the past, when carmakers typically ran on five- to seven-year design cycles, the latest technology in vehicles today may well be considered dated within several years. And if they cannot keep up, there is a whole new crop of startups producing cheap vehicles with the ability to update or change out features as quickly as a software update.

But software has speed, security, and reliability limitations, and being able to customize the hardware is where many automakers are now putting their efforts. This is where chiplets fit in, and the focus now is on how to build enough interoperability across large ecosystems to make this a plug-and-play market. The key factors to enable automotive chiplet interoperability include standardization, interconnect technologies, communication protocols, power and thermal management, security, testing, and ecosystem collaboration.

Similar to non-automotive applications at the board level, many design efforts are focusing on a die-to-die approach, which is driving a number of novel design considerations and tradeoffs. At the chip level, the interconnects between various processors, chips, memory, and I/O are becoming more complex due to increased design performance requirements, spurring a flurry of standards activities. Different interconnect and interface types have been proposed to serve varying purposes, while emerging chiplet technologies for dedicated functions — processors, memories, and I/Os, to name a few — are changing the approach to chip design.

“There is a realization by automotive OEMs that to control their own destiny, they’re going to have to control their own SoCs,” said David Fritz, vice president of virtual and hybrid systems at Siemens EDA. “However, they don’t understand how far along EDA has come since they were in college in 1982. Also, they believe they need to go to the latest process node, where a mask set is going to cost $100 million. They can’t afford that. They also don’t have access to talent because the talent pool is fairly small. With all that together comes the realization by the OEMs that to control their destiny, they need a technology that’s developed by others, but which can be combined however needed to have a unique differentiated product they are confident is future-proof for at least a few model years. Then it becomes economically viable. The only thing that fits the bill is chiplets.”

Chiplets can be optimized for specific functions, which can help automakers meet reliability, safety, security requirements with technology that has been proven across multiple vehicle designs. In addition, they can shorten time to market and ultimately reduce the cost of different features and functions.

Demand for chips has been on the rise for the past decade. According to Allied Market Research, global automotive chip demand will grow from $49.8 billion in 2021 to $121.3 billion by 2031. That growth will attract even more automotive chip innovation and investment, and chiplets are expected to be a big beneficiary.

But the marketplace for chiplets will take time to mature, and it will likely roll out in phases.  Initially, a vendor will provide different flavors of proprietary dies. Then, partners will work together to supply chiplets to support each other, as has already happened with some vendors. The final stage will be universally interoperable chiplets, as supported by UCIe or some other interconnect scheme.

Getting to the final stage will be the hardest, and it will require significant changes. To ensure interoperability, large enough portions of the automotive ecosystem and supply chain must come together, including hardware and software developers, foundries, OSATs, and material and equipment suppliers.

Momentum is building
On the plus side, not all of this is starting from scratch. At the board level, modules and sub-systems always have used onboard chip-to-chip interfaces, and they will continue to do so. Various chip and IP providers, including Cadence, Diode, Microchip, NXP, Renesas, Rambus, Infineon, Arm, and Synopsys, provide off-the-shelf interface chips or IP to create the interface silicon.

The Universal Chiplet Interconnect Express (UCIe) Consortium is the driving force behind the die-to-die, open interconnect standard. The group released its latest UCIe 1.1 specification in August 2023. Board members include Alibaba, AMD, Arm, ASE, Google Cloud, Intel, Meta, Microsoft, NVIDIA, Qualcomm, Samsung, and others. Industry partners are showing widespread support. AIB and Bunch of Wires (BoW) also have been proposed. In addition, Arm just released its own Chiplet System Architecture, along with an updated AMBA spec to standardize protocols for chiplets.

“Chiplets are already here, driven by necessity,” said Arif Khan, senior product marketing group director for design IP at Cadence. “The growing processor and SoC sizes are hitting the reticle limit and the diseconomies of scale. Incremental gains from process technology advances are lower than rising cost per transistor and design. The advances in packaging technology (2.5D/3D) and interface standardization at a die-to-die level, such as UCIe, will facilitate chiplet development.”

Nearly all of the chiplets used today are developed in-house by big chipmakers such as Intel, AMD, and Marvell, because they can tightly control the characteristics and behavior of those chiplets. But there is work underway at every level to open this market to more players. When that happens, smaller companies can begin capitalizing on what the high-profile trailblazers have accomplished so far, and innovating around those developments.

“Many of us believe the dream of having an off-the-shelf, interoperable chiplet portfolio will likely take years before becoming a reality,” said Guillaume Boillet, senior director strategic marketing at Arteris, adding that interoperability will emerge from groups of partners who are addressing the risk of incomplete specifications.

This also is raising the attractiveness of FPGAs and eFPGAs, which can provide a level of customization and updates for hardware in the field. “Chiplets are a real thing,” said Geoff Tate, CEO of Flex Logix. “Right now, a company building two or more chiplets can operate much more economically than a company building near-reticle-size die with almost no yield. Chiplet standardization still appears to be far away. Even UCIe is not a fixed standard yet. Not all agree on UCIe, bare die testing, and who owns the problem when the integrated package doesn’t work, etc. We do have some customers who use or are evaluating eFPGA for interfaces where standards are in flux like UCIe. They can implement silicon now and use the eFPGA to conform to standards changes later.”

There are other efforts supporting chiplets, as well, although for somewhat different reasons — notably, the rising cost of device scaling and the need to incorporate more features into chips, which are reticle-constrained at the most advanced nodes. But those efforts also pave the way for chiplets in automotive, and there is strong industry backing to make this all work. For example, under the sponsorship of SEMI, ASME, and three IEEE Societies, the new Heterogeneous Integration Roadmap (HIR) looks at various microelectronics design, materials, and packaging issues to come up with a roadmap for the semiconductor industry. Their current focus includes 2.5D, 3D-ICs, wafer-level packaging, integrated photonics, MEMS and sensors, and system-in-package (SiP), aerospace, automotive, and more.

At the recent Heterogeneous Integration Global Summit 2023, representatives from AMD, Applied Materials, ASE, Lam Research, MediaTek, Micron, Onto Innovation, TSMC, and others demonstrated strong support for chiplets. Another group that supports chiplets is the Chiplet Design Exchange (CDX) working group , which is part of the Open Domain Specific Architecture (ODSA) and the Open Compute Project Foundation (OCP). The Chiplet Design Exchange (CDX) charter focuses on the various characteristics of chiplet and chiplet integration, including electrical, mechanical, and thermal design exchange standards of the 2.5D stacked, and 3D Integrated Circuits (3D-ICs). Its representatives include Ansys, Applied Materials, Arm, Ayar Labs, Broadcom, Cadence, Intel, Macom, Marvell, Microsemi, NXP, Siemens EDA, Synopsys, and others.

“The things that automotive companies want in terms of what each chiplet does in terms of functionality is still in an upheaval mode,” Siemens’ Fritz noted. “One extreme has these problems, the other extreme has those problems. This is the sweet spot. This is what’s needed. And these are the types of companies that can go off and do that sort of work, and then you could put them together. Then this interoperability thing is not a big deal. The OEM can make it too complex by saying, ‘I have to handle that whole spectrum of possibilities.’ The alternative is that they could say, ‘It’s just like a high speed PCIe. If I want to communicate from one to the other, I already know how to do that. I’ve got drivers that are running my operating system. That would solve an awful lot of problems, and that’s where I believe it’s going to end up.”

One path to universal chiplet development?

Moving forward, chiplets are a focal point for both the automotive and chip industries, and that will involve everything from chiplet IP to memory interconnects and customization options and limitations.

For example, Renesas Electronics announced in November 2023 plans for its next-generation SoCs and MCUs. The company is targeting all major applications across the automotive digital domain, including advance information about its fifth-generation R-Car SoC for high-performance applications with advanced in-package chiplet integration technology, which is meant to provide automotive engineers greater flexibility to customize their designs.

Renesas noted that if more AI performance is required in Advanced Driver Assistance Systems (ADAS), engineers will have the capability to integrate AI accelerators into a single chip. The company said this roadmap comes after years of collaboration and discussions with Tier 1 and OEM customers, which have been clamoring for a way to accelerate development without compromising quality, including designing and verifying the software even before the hardware is available.

“Due to the ever increasing needs to increase compute on demand, and the increasing need for higher levels of autonomy in the cars of tomorrow, we see challenges in monolithic solutions scaling and providing the performance needs of the market in the upcoming years,” said Vasanth Waran, senior director for SoC Business & Strategies at Renesas. “Chiplets allows for the compute solutions to scale above and beyond the needs of the market.”

Renesas announced plans to create a chiplet-based product family specifically targeted at the automotive market starting in 2025.

Standard interfaces allow for SoC customization
It is not entirely clear how much overlap there will be between standard processors, which is where most chiplets are used today, and chiplets developed for automotive applications. But the underlying technologies and developments certainly will build off each other as this technology shifts into new markets.

“Whether it is an AI accelerator or ADAS automotive application, customers need standard interface IP blocks,” noted David Ridgeway, senior product manager, IP accelerated solutions group at Synopsys. “It is important to provide fully verified IP subsystems around their IP customization requirements to support the subsystem components used in the customers’ SoCs. When I say customization, you might not realize how customizable IP has become over the course of the last 10 to 20 years, on the PHY side as well as the controller side. For example, PCI Express has gone from PCIe Gen 3 to Gen 4 to Gen 5 and now Gen 6. The controller can be configured to support multiple bifurcation modes of smaller link widths, including one x16, two x8, or four x4. Our subsystem IP team works with customers to ensure all the customization requirements are met. For AI applications, signal and power integrity is extremely important to meet their performance requirements. Almost all our customers are seeking to push the envelope to achieve the highest memory bandwidth speeds possible so that their TPU can process many more transactions per second. Whenever the applications are cloud computing or artificial intelligence, customers want the fastest response rate possible.”

Fig 1: IP blocks including processor, digital, PHY, and verification help developers implement the entire SoC. Source: Synopsys

Optimizing PPA serves the ultimate goal of increasing efficiency, and this makes chiplets particularly attractive in automotive applications. When UCIe matures, it is expected to improve overall performance exponentially. For example, UCIe can deliver a shoreline bandwidth of 28 to 224 GB/s/mm in a standard package, and 165 to 1317 GB/s/mm in an advanced package. This represents a performance improvement of 20- to 100-fold. Bringing latency down from 20ns to 2ns represents a 10-fold improvement. Around 10 times greater power efficiency, at 0.5 pJ/b (standard package) and 0.25 pJ/b (advanced package), is another plus. The key is shortening the interface distance whenever possible.

To optimize chiplet designs, the UCIe Consortium provides some suggestions:

• Careful planning consideration of architectural cut-lines (i.e. chiplet boundaries), optimizing for power, latency, silicon area, and IP reuse. For example, customizing one chiplet that needs a leading-edge process node while re-using other chiplets on older nodes may impact cost and time.
• Thermal and mechanical packaging constraints need to be planned out for package thermal envelopes, hot spots, chiplet placements and I/O routing and breakouts.
• Process nodes need to be carefully selected, particularly in the context of the associated power delivery scheme.
• Test strategy for chiplets and packaged/assembled parts need to be developed up front to ensure silicon issues are caught at the chiplet-level testing phase rather than after they are assembled into a package.

Conclusion
The idea of standardizing die-to-die interfaces is catching on quickly but the path to get there will take time, effort, and a lot of collaboration among companies that rarely talk with each other. Building a vehicle takes one determine carmaker. Building a vehicle with chiplets requires an entire ecosystem that includes the developers, foundries, OSATs, and material and equipment suppliers to work together.

Automotive OEMs are experts at putting systems together and at finding innovative ways to cut costs. But it remains to seen how quickly and effectively they can build and leverage an ecosystem of interoperable chiplets to shrink design cycles, improve customization, and adapt to a world in which the leading edge technology may be outdated by the time it is fully designed, tested, and available to consumers.

— Ann Mutschler contributed to this report.

Related Reading
Automotive Relationships Shifting With Chiplets
As the automotive ecosystem balances the best approaches for designing in increasingly advanced features, how companies interact is still evolving.

The post Why Chiplets Are So Critical In Automotive appeared first on Semiconductor Engineering.

The question on everyone's mind is what company is Intel's marquee foundry customer?
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