Author's Latest Posts


What Makes A Chip Tamper-Proof?


The cyber world is the next major battlefield, and attackers are busily looking for ways to disrupt critical infrastructure. There is widespread proof this is happening. “Twenty-six percent of the U.S. power grid was found to be hosting Trojans," said Haydn Povey, IAR Systems' general manager of embedded security solutions. "In a cyber-warfare situation, that's the first thing that would b... » read more

Spiking Neural Networks: Research Projects or Commercial Products?


Spiking neural networks (SNNs) often are touted as a way to get close to the power efficiency of the brain, but there is widespread confusion about what exactly that means. In fact, there is disagreement about how the brain actually works. Some SNN implementations are less brain-like than others. Depending on whom you talk to, SNNs are either a long way away or close to commercialization. Th... » read more

Auto Power Becoming Much More Complex


Rising electronics content in automobiles is putting increased focus on automotive power delivery networks (PDNs). Safety implications mean that thorough power design and verification, along with novel power isolation techniques, are needed at the vehicle level, involving both electrical and mechanical considerations. The electronic takeover can be measured by the percentage that electronic ... » read more

Inference Moves To The Network


Machine-learning inference started out as a data-center activity, but tremendous effort is being put into inference at the edge. At this point, the “edge” is not a well-defined concept, and future inference capabilities will reside not only at the extremes of the data center and a data-gathering device, but at multiple points in between. “Inference isn't a function that has to resid... » read more

Making Sense Of PUFs


As security becomes a principal design consideration, physically unclonable functions (PUFs) are seeing renewed interest as new players emerge onto the market. PUFs can play a central role in hardware roots of trust (HRoTs), but the messaging in the market can make it confusing to understand the different types of PUF as well as their pros and cons. PUFs leverage some uncertain aspect of som... » read more

Full-Duplex Wireless Remains A Promise And A Challenge


Wireless bandwidth capacity could double if we could use full-duplex communication. Unfortunately, that’s not as easy as it sounds. People are working hard on it, but we’re mostly not there yet. Full duplex seems easy. In fact, so easy that it was possible with the first basic telephones. There was one loop between each phone and the central office, and that one loop carried conversation... » read more

NVM Reliability Challenges And Tradeoffs


This second of two parts looks at different memories and possible solutions. Part one can be found here. While various NVM technologies, such as PCRAM, MRAM, ReRAM and NRAM share similar high-level traits, their physical renderings are quite different. That provides each with its own set of challenges and solutions. PCRAM has had a fraught history. Initially released by Samsung, Micron, a... » read more

What Is DRAM’s Future?


Memory — and DRAM in particular — has moved into the spotlight as it finds itself in the critical path to greater system performance. This isn't the first time DRAM has been the center of attention involving performance. The problem is that not everything progresses at the same rate, creating serial bottlenecks in everything from processor performance to transistor design, and even the t... » read more

Inside The New Non-Volatile Memories


The search continues for new non-volatile memories (NVMs) to challenge the existing incumbents, but before any technology can be accepted, it must be proven reliable. “Everyone is searching for a universal memory,” says TongSwan Pang, Fujitsu senior marketing manager. "Different technologies have different reliability challenges, and not all of them may be able to operate in automotive g... » read more

New Ways To Optimize Machine Learning


As more designers employ machine learning (ML) in their systems, they’re moving from simply getting the application to work to optimizing the power and performance of their implementations. Some techniques are available today. Others will take time to percolate through the design flow and tools before they become readily available to mainstream designers. Any new technology follows a basic... » read more

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