Chip Industry Week In Review


By Jesse Allen, Karen Heyman, and Liz Allan Renesas will acquire Transphorm, which designs and manufactures gallium nitride power devices, for about $339 million. GaN, which is a wide-bandgap technology, is used for high-voltage applications in a slew of markets, including EVs and EV fast chargers, as well as data centers and industrial applications. Cadence acquired Invecas, a provider o... » read more

Startup Funding: December 2023


Photonics and optics were strong in December, with investors funding two different companies using photonic technologies to develop AI chips and interconnects. Another key area — metaoptics — combines what traditionally would be separate lenses and optical components into a single, flat nanopatterned device. Metaoptics are being deployed in applications ranging from AI processing and sensor... » read more

Chip Industry Week In Review


By Susan Rambo, Jesse Allen, and Liz Allan The U.S. government will provide about $162 million in federal incentives, under the CHIPS and Science Act, to help Microchip onshore its semiconductor supply chain. The move is aimed at securing a reliable domestic supply of MCUs and mature-node chips. “Today’s announcement will help propel semiconductor manufacturing projects in Colorado and O... » read more

Money Pours Into New Fabs And Facilities


Fabs, packaging, test and assembly, and R&D all drew major funding in 2023. Companies poured money into offshore locations, such as India and Malaysia, to access a larger workforce and lower costs, while also partnering with governments to secure domestic supply chains amid ongoing geopolitical turmoil. Looking ahead, artificial intelligence (AI), quantum computing, and data applications... » read more

2023: A Good Year For Semiconductors


Looking back, 2023 has had more than its fair share of surprises, but who were the winners and losers? The good news is that by the end of the year, almost everyone was happy. That is not how we exited 2022, where there was overcapacity, inventories had built up in many parts of the industry, and few sectors — apart from data centers — were seeing much growth. The supposed new leaders we... » read more

3D-ICs May Be The Least-Cost Option


When 2.5D and 3D packaging were first conceived, the general consensus was that only the largest semiconductor houses would be able to afford them, but development costs are quickly coming under control. In some cases, these advanced packages actually may turn out to be the lowest-cost options. With stacked die [1], each die is considered to be a complete functional block or sub-system. In t... » read more

Chip Industry Week In Review


By Jesse Allen, Susan Rambo, and Liz Allan The U.S. government will invest about $3 billion for the National Advanced Packaging Manufacturing Program (NAPMP), including an advanced packaging piloting facility to help U.S. manufacturers adopt new technology and workforce training programs. It also will provide funding for projects concentrating on materials and substrates; equipment, tools, ... » read more

Chip Industry Week In Review


By Jesse Allen, Karen Heyman, and Liz Allan Japan's Rapidus and the University of Tokyo are teaming up with France's Leti to meet its previously announced mass production goal of 2nm chips by 2027, and chips in the 1nm range in the 2030s. Rapidus was formed in 2022 with the support of eight Japanese companies — Sony, Kioxia, Denso, NEC, NTT, SoftBank, Toyota, and Mitsubishi's banking arm, ... » read more

Technical Paper Roundup: November 14


New technical papers added to Semiconductor Engineering’s library this week. [table id=165 /] More Reading Technical Paper Library home » read more

Applications Of Large Language Models For Industrial Chip Design (NVIDIA)


A technical paper titled “ChipNeMo: Domain-Adapted LLMs for Chip Design” was published by researchers at NVIDIA. Abstract: "ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we instead adopt the following domain adaptation techniques: custom tokenizers, domain-ad... » read more

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