Chip Industry Week In Review


By Jesse Allen, Gregory Haley, and Liz Allan Synopsys acquired Imperas, pushing further into the RISC-V world with Imperas' virtual platform technology for verifying and emulating processors. Synopsys has been building up its RISC-V portfolio, starting with ARC-V processor IP and a full suite of tools introduced last month. The first high-NA EUV R&D center in the U.S. will be built at... » read more

Closing The Test And Metrology Gap In 3D-IC Packages


The industry is investing in more precise and productive inspection and testing to enable advanced packages and eventually, 3D ICs. The next generations of aerospace, automotive, smartphone, and wearable tech most likely will be powered by multiple layers of intricately connected silicon, a stark departure from the planar landscapes of traditional integrated circuits. These 3D-ICs, compos... » read more

Fingerprinting Chips For Traceability


Semiconductor components increasingly require unclonable and tamper resistant identifiers, which are especially necessary as devices become increasingly heterogeneous collections of chiplets and subsystems. These fingerprints provide traceability, which contributes to process improvements and yield learning and enable tracking for a tightly managed supply chain. While some of this technology... » read more

New Insights Into IC Process Defectivity


Finding critical defects in manufacturing is becoming more difficult due to tighter design margins, new processes, and shorter process windows. Process marginality and parametric outliers used to be problematic at each new node, but now they are persistent problems at several nodes and in advanced packaging, where there may be a mix of different technologies. In addition, there are more proc... » read more

Rebalancing Test And Yield In IC Manufacturing


Balancing yield and test is essential to semiconductor manufacturing, but it's becoming harder to determine how much weight to give one versus the other as chips become more specialized for different applications. Yield focuses on maximizing the number of functional chips from a production batch, while test aims to ensure that each chip meets rigorous quality and performance standards. And w... » read more

Why Curvy Design Now? Less Change Than You Think And Manufacturable Today


A curvilinear (curvy) chip, if magically made possible, would be smaller, faster, and use less power. Magic is no longer needed on the manufacturing side, as companies like Micron Technology are making photomasks with curvy shapes using state-of-the-art multi-beam mask writers today. Yet the entire chip-design infrastructure is based on the Manhattan assumption of 90-degree turns, even though i... » read more

Chip Industry Talent Shortage Drives Academic Partnerships


Universities around the world are forming partnerships with semiconductor companies and governments to help fill open and future positions, to keep curricula current and relevant, and to update and expand skills for working engineers. Talent shortages repeatedly have been cited as the number one challenge for the chip industry. Behind those concerns are several key drivers, and many more dom... » read more

Using Smart Data To Boost Semiconductor Reliability


The chip industry is looking to AI and data analytics to improve yield, operational efficiency, and reduce the overall cost of designing and manufacturing complex devices. In fact, SEMI estimates its members could capture more than $60B in revenues associated through smart data use and AI. Getting there, however, requires overcoming a number of persistent obstacles. Smart data utilization is... » read more

Data, System Reliability, and Privacy


Experts at the Table: Semiconductor Engineering sat down to discuss changes in test that address tracing device quality throughout a product’s lifetime, and over-arching concerns about data ownership and privacy, with Tom Katsioulas, CEO at Archon Design Solutions and U.S. Department of Commerce IoT advisory board member; Ming Zhang, vice president of R&D Acceleration at PDF Solutions; a... » read more

When And Where To Implement AI/ML In Fabs


Deciphering complex interactions between variables is where machine learning and deep learning shine, but figuring out exactly how ML-based systems will be most useful is the job of engineers. The challenge is in pairing their domain expertise with available ML tools to maximize the value of both. This depends on sufficient quantities of good data, highly optimized algorithms, and proper tra... » read more

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