Author's Latest Posts


Stacking Memory On Logic, Take Two


True 3D-ICs, where a memory die is stacked on top of a logic die using through-silicon vias, appear to be gaining momentum. There are a couple reasons why this is happening, and a handful of issues that need to be considered before even seriously considering this option. None of this is easy. On a scale of 1 to 10, this ranks somewhere around 9.99, in part because the EDA tools needed to rem... » read more

Why DRAM Won’t Go Away


Semiconductor Engineering sat down to talk about DRAM's future 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 that conversation. Part ... » read more

The New CXL Standard


Gary Ruggles, senior staff product marketing manager at Synopsys, digs into the new Compute Express Link standard, why it’s important for high bandwidth in AI/ML applications, where it came from, and how to apply it in current and future designs. » read more

Making Better Use Of Memory In AI


Steven Woo, Rambus fellow and distinguished inventor, talks about using number formats to extend memory bandwidth, what the impact can be on fractional precision, how modifications of precision can play into that without sacrificing accuracy, and what role stochastic rounding can play. » read more

Another Brick Or Two In The Chip Design Wall


Physical challenges come and go in the semiconductor world. But increasingly, they also stick around, showing up in inconvenient places at the worst time. The chip industry has confronted and solved some massive challenges over the years. There was the 1 micron lithography wall, which was supposed to be impenetrable. That was followed by the 193nm litho challenge, which cost many billions of... » read more

Machine Learning Inferencing At The Edge


Ian Bratt, fellow in Arm's machine learning group, talks about why machine learning inferencing at the edge is so difficult, what are the tradeoffs, how to optimize data movement, how to accelerate that movement, and how it differs from developing other types of processors. » read more

Improving Quality Through Data Analytics


Doug Elder, vice president and general manager at OptimalPlus, explains how to utilize data to improve reliability, how it applies to different manufacturing processes, and what happens when that data is made available to more people within an organization. » read more

The Critical But Less Obvious Risks In AI


AI has been the subject of intense debate since it was first introduced back in the mid-1950s, but the real threat is a lot more mundane and potentially even more serious than the fear-inducing picture painted by its critics. Replacing jobs with technology has been a controversial subject for more than a century. AI is a relative newcomer in that debate. While the term "artificial intelligen... » read more

How Hardware Can Bias AI Data


Clean data is essential to good results in AI and machine learning, but data can become biased and less accurate at multiple stages in its lifetime—from moment it is generated all the way through to when it is processed—and it can happen in ways that are not always obvious and often difficult to discern. Blatant data corruption produces erroneous results that are relatively easy to ident... » read more

Ensuring A 5G Design Is Viable


Ron Squiers, network solutions specialist at Mentor, a Siemens Business, explains what’s different in 5G chips versus 4G, how to construct a front haul and back haul system so it is testable in the network stack. » read more

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