Week In Review: Design, Low Power


Si2's Unified Power Model has been approved as IEEE 2416-2019, a new Standard for Power Modeling to Enable System Level Analysis, which complements UPF/IEEE 1801-2018. UPM/IEEE 2416-2019 provides a set of power modeling semantics enabling system designers to model entire systems with flexibility. It supports power modeling from abstract design description to gate level implementation, providing... » read more

Applied Buys Kokusai For $2.2B


Applied Materials has signed a definitive agreement to acquire Kokusai Electric for $2.2 billion in cash from investment firm KKR. For years, Kokusai Electric was a subsidiary of Hitachi. It sells epitaxial, thermal processing and other equipment. Then, as part of a complex business deal, KKR in 2017 acquired the semiconductor equipment business of Hitachi Kokusai Electric from Hitachi. ... » read more

Week In Review: Manufacturing, Test


Market research What’s the CapEx outlook for 2020? Semiconductor capital spending is down in 2019, but the industry faces another slump in 2020, according to IC Insights. The firm sees a 15% decline in CapEx for 2019 with a 5% drop expected in 2020. New 300mm fab construction in Korea is still going strong despite the memory downturn, according to SEMI. “Korea’s fab construction spen... » read more

Manufacturing Bits: June 25


Panel-level consortium Fraunhofer is moving forward with the next phase of its consortium to develop technologies for panel-level packaging. In 2016, Fraunhofer launched the original effort, dubbed the Panel Level Packaging Consortium. The consortium, which had 17 partners, developed various equipment and materials in the arena. Several test layouts were designed for process development on ... » read more

5nm Vs. 3nm


Foundry vendors are readying the next wave of advanced processes, but their customers will face a myriad of confusing options—including whether to develop chips at 5nm, wait until 3nm, or opt for something in between. The path to 5nm is well-defined compared with 3nm. After that, the landscape becomes more convoluted because foundries are adding half-node processes to the mix, such as 6nm ... » read more

What’s Next In Advanced Packaging


Packaging houses are readying the next wave of advanced IC packages, hoping to gain a bigger foothold in the race to develop next-generation chip designs. At a recent event, ASE, Leti/STMicroelectronics, TSMC and others described some of their new and advanced IC packaging technologies, which involve various product categories, such as 2.5D, 3D and fan-out. Some new packaging technologies ar... » read more

Power, Reliability And Security In Packaging


Semiconductor Engineering sat down to discuss advanced packaging with Ajay Lalwani, vice president of global manufacturing operations at eSilicon; Vic Kulkarni, vice president and chief strategist in the office of the CTO at ANSYS; Calvin Cheung, vice president of engineering at ASE; Walter Ng, vice president of business management at UMC; and Tien Shiah, senior manager for memory at Samsun... » read more

Playing Into China’s Hands


The fallout over blacklisting Huawei in particular, and China in general, has set the tone for a nasty global race. But it is almost certain to produce a different result than the proponents of a trade war are expecting. The idea behind tariffs and the blacklisting of Huawei is to starve China of vital technology. So far, the impact has been minimal. Reports from inside of China are equa... » read more

HBM2 Vs. GDDR6: Tradeoffs In DRAM


Semiconductor Engineering sat down to talk about new DRAM options and considerations with Frank Ferro, senior director of product management at Rambus; Marc Greenberg, group director for product marketing at Cadence; Graham Allan, senior product marketing manager for DDR PHYs at Synopsys; and Tien Shiah, senior manager for memory marketing at Samsung Electronics. What follows are excerpts of th... » read more

Accelerating Endpoint Inferencing


Chipmakers are getting ready to debut inference chips for endpoint devices, even though the rest of the machine-learning ecosystem has yet to be established. Whatever infrastructure does exist today is mostly in the cloud, on edge-computing gateways, or in company-specific data centers, which most companies continue to use. For example, Tesla has its own data center. So do most major carmake... » read more

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