Author's Latest Posts


Preventing Failures Before They Occur


A decade or so ago, when MEMS sensors were in the limelight, one of the touted applications was to install them on industrial or other equipment to get an advance warning if the equipment was approaching failure. Today, in-circuit monitoring brings the same promise. Are these competing technologies? Or can they be made to work together? “Almost all advanced tool manufacturing companies ... » read more

Making PUFs Even More Secure


As security has become a must-have in most systems, hardware roots of trust (HRoTs) have started appearing in many chips. Critical to an HRoT is the ability to authenticate and to create keys – ideally from a reliable source that is unviewable and immutable. “We see hardware roots of trust deployed in two use models — providing a foundation to securely start a system, and enabling a se... » read more

Can Coherent Optics Reduce Data-Center Power?


As optical bandwidth requirements increase, system designers are turning to “coherent” modulation schemes that can place more data on the same laser light, and lower power over long connections. A newer question is whether those savings could be achieved for short connections within data centers, as well. “Coherent is the direction everything's moving, because for a given system and... » read more

Big Changes Ahead For Inside Auto Cabins


The space we occupy inside our vehicles is poised to change from mere enclosure to participant in the driving experience. Whether for safety or for comfort, a wide range of sensors are likely to appear that will monitor the “contents” of the vehicle. The overall approach is referred to as an in-cabin monitoring system (ICMS), but the specific applications vary widely. “In-cabin sensing... » read more

Speeding Up Scan-Based Volume Diagnosis


In the critical process known as new-product bring-up, it’s a race to get new products to yield as quickly as possible. But the interplay between increasingly complex aspects of designs and process makes it difficult to find root causes of yield issues so they can be fixed quickly. Advanced processes have very high defectivity, and learning must be fast and effective. While progress has be... » read more

Will Markets For ML Models Materialize?


Developers are spending increasing amounts of time and effort in creating machine-learning (ML) models for use in a wide variety of applications. While this will continue as the market matures, at some point some of these efforts might be seen as reinventing models over and over. Will developers of successful models ever have a marketplace in which they can sell those models as IP to other d... » read more

AI/ML Workloads Need Extra Security


The need for security is pervading all electronic systems. But given the growth in data-center machine-learning computing, which deals with extremely valuable data, some companies are paying particular attention to handling that data securely. All of the usual data-center security solutions must be brought to bear, but extra effort is needed to ensure that models and data sets are protected ... » read more

Changing Server Architectures In The Data Center


Data centers are undergoing a fundamental shift to boost server utilization and improve efficiency, optimizing architectures so available compute resources can be leveraged wherever they are needed. Traditionally, data centers were built with racks of servers, each server providing computing, memory, interconnect, and possibly acceleration resources. But when a server is selected, some of th... » read more

More Errors, More Correction in Memories


As memory bit cells of any type become smaller, bit error rates increase due to lower margins and process variation. This can be dealt with using error correction to account for and correct bit errors, but as more sophisticated error-correction codes (ECC) are used, it requires more silicon area, which in turn drives up the cost. Given this trend, the looming question is whether the cost of ... » read more

Easier And Faster Ways To Train AI


Training an AI model takes an extraordinary amount of effort and data. Leveraging existing training can save time and money, accelerating the release of new products that use the model. But there are a few ways this can be done, most notably through transfer and incremental learning, and each of them has its applications and tradeoffs. Transfer learning and incremental learning both take pre... » read more

← Older posts Newer posts →