Follow The Moving Money


Semiconductor economics are changing by market, by region, and by product node and packaging type, adding new complexity into decisions about which technology to use for which products and why. Money is the common denominator in all of these decisions, whether it's measured by return on invested capital, quarterly profits, or long-term investments that can include acquisitions, organic growt... » read more

Predictions: Manufacturing, Devices And Companies


Some predictions are just wishful thinking, but most of these are a lot more thoughtful. They project what needs to happen for various markets or products to become successful. Those far reaching predictions may not fully happen within 2018, but we give everyone the chance to note the progress made towards their predictions at the end of the year. (See Reflection On 2017: Design And EDA and Man... » read more

Mixed Messages For Mixed-Signal


There is no such thing as a purely digital design at advanced nodes today. Even designs that have no [getkc id="37" kc_name="analog"] content are likely relying on [getkc id="38" kc_name="mixed-signal"] components such as SerDes for communications, or voltage regulators for adaptive power control. But the days of purposely attempting to integrate everything including analog and RF onto a single... » read more

Litho Options For Panel Fan-out


Several packaging houses are inching closer to production of panel-level fan-out packaging, a next-generation technology that promises to reduce the cost of today’s fan-out packages. In fact, ASE, Nepes, Samsung and others already have installed the equipment in their panel-level fan-out lines with production slated for 2018 or so. But behind the scenes, panel-level packaging houses contin... » read more

Managing Peak Power


Peak power is becoming a serious design constraint across chips and entire electronic systems as more functionality is added into end devices and the compute and switching infrastructure needed to support them. The issues are a direct result of growing complexity in designs, fixed or shrinking power budgets, and the need to process more data more quickly. In mobile devices, the addition of m... » read more

What’s After 7nm?


The rollout of 10/7nm was a long time coming, and for good reason. It's hard stuff, and chipmakers have to be ready to take a giant step forward with new processes, tools, and to deal with a slew of physical effects that no longer can be handled by just guard-banding a design. The big question is what's next, when it will happen, and how much it will cost. Preparing for the next process node... » read more

Executive Insight: Lip-Bu Tan


Semiconductor Engineering sat down with Lip-Bu Tan, president and CEO of [getentity id="22032" e_name="Cadence"], to discuss disruptions and changes in the semiconductor industry, from machine learning and advance packaging to tools and business. What follows are excerpts of that conversation. SE: What do you see as the next big thing? Tan: Unlike mobility or cell phones, or PCs before th... » read more

Is Design Innovation Slowing?


Paul Teich, principal analyst for Tirias Research, gave a provocative talk at the recent DAC conference entitled, "Is Integration Leaving Less Room for Design Innovation?" The answer isn't as simple as the question might suggest. "Integration used to be a driver for increasing the functionality of silicon," Teich said. "Increasingly, it will be used to incorporate more features of an entire ... » read more

Challenges For Future Fan-Outs


The fan-out wafer-level packaging market is heating up. At the high end, for example, several packaging houses are developing new fan-out packages that could reach a new milestone and hit or break the magic 1µm line/space barrier. But the technology presents some challenges, as it may require more expensive process flows and equipment like lithography. Fig. 1: Redistribution layers. Source: L... » read more

Deep Learning Robust Grasps with Synthetic Point Clouds & Analytic Grasp Metrics (UC Berkeley)


Source: The research was the work of Jeffrey Mahler, Jacky Liang, Sherdil Niyaz, Michael Laskey, Richard Doan, Xinyu Liu, Juan Aparicio Ojea, and Ken Goldberg with support from the AUTOLAB team at UC Berkeley. Nimble-fingered robots enabled by deep learning Grabbing awkwardly shaped items that humans regularly pick up daily is not so easy for robots, as they don’t know where to apply grip... » read more

← Older posts