Author's Latest Posts


Monitoring Chips On Many Levels


Monitoring is an important trend for optimizing yield, performance, and uptime in systems that use complex integrated circuits, but not all monitoring is the same. In fact, there are multiple levels of monitors. In many cases, they can be used together to help solve problems when something is amiss. They also can be used to help identify who in the supply chain owns the fix. “If the sys... » read more

How To Measure ML Model Accuracy


Machine learning (ML) is about making predictions about new data based on old data. The quality of any machine-learning algorithm is ultimately determined by the quality of those predictions. However, there is no one universal way to measure that quality across all ML applications, and that has broad implications for the value and usefulness of machine learning. “Every industry, every d... » read more

MRAM Evolves In Multiple Directions


Magnetoresistive RAM (MRAM) is one of several new non-volatile memory technologies targeting broad commercial availability, but designing MRAM into chips and systems isn't as simple as adding other types of memory. MRAM isn’t an all-things-for-all-applications technology. It needs to be tuned for its intended purpose. MRAMs targeting flash will not do as well targeting SRAMs, and vice vers... » read more

Preventing Chips From Burning Up During Test


It’s become increasingly difficult to manage the heat generated during IC test. Absent the proper mitigations, it’s easy to generate so much heat that probe cards and chips literally can burn up. As a result, implementing temperature-management techniques is becoming a critical part of IC testing. “We talk about systems, saying the system is good,” said Arun Krishnamoorthy, senior... » read more

Making Sense Of New Edge-Inference Architectures


New edge-inference machine-learning architectures have been arriving at an astounding rate over the last year. Making sense of them all is a challenge. To begin with, not all ML architectures are alike. One of the complicating factors in understanding the different machine-learning architectures is the nomenclature used to describe them. You’ll see terms like “sea-of-MACs,” “systolic... » read more

Security Provisioning Moves Out Of The Factory


Security credentials traditionally have been provisioned during chip manufacturing, often as a final part of the testing process. That's starting to change. Logistics management can be improved by pushing that process out — even as far as the on-boarding process. And simpler on-boarding can hide most of the details from the user. “The IT approach to provisioning IoT devices has primar... » read more

FeFETs Bring Promise And Challenges


Ferroelectric FETs (FeFETs) and memory (FeRAM) are generating high levels of interest in the research community. Based on a physical mechanism that hasn’t yet been commercially exploited, they join the other interesting new physics ideas that are in various stages of commercialization. “FeRAM is very promising, but it's like all promising memory technologies — it takes a while to get b... » read more

DRAM’s Persistent Threat To Chip Security


A well-known DRAM vulnerability called "rowhammer," which allows an assailant to disrupt or take control of a system, continues to haunt the chip industry. Solutions have been tried, and new ones are being proposed, but the potential for a major attack persists. First discovered some five years ago, most of the efforts to eliminate the "rowhammer" threat have done little more than mitigate t... » read more

Automotive Test Moves In-System


With the electrification of automobiles, it’s not enough to test the new electronics thoroughly at the end of the manufacturing process. Safety standards now require that tests be performed live, in the field, with contingency plans should a test fail. “We see clear demand from the automotive semiconductor supply chain for design functionality specifically aimed at in-system monitoring,�... » read more

Edge-Inference Architectures Proliferate


First part of two parts. The second part will dive into basic architectural characteristics. The last year has seen a vast array of announcements of new machine-learning (ML) architectures for edge inference. Unburdened by the need to support training, but tasked with low latency, the devices exhibit extremely varied approaches to ML inference. “Architecture is changing both in the comp... » read more

← Older posts Newer posts →