The Week In Review: Design


Tools & IP Synopsys uncorked ASIL B, C, and D ready versions of its DesignWare EV6x Embedded Vision Processors for automotive SoCs. An included Safety Enhancement Package provides hardware safety features, safety monitors, and lockstep capabilities for safety-critical designs. The processors integrate scalar, vector DSP, and CNN processing units for automotive systems that require deep lea... » read more

The Week In Review: Design


M&A IoT-focused memory chipmaker Adesto Technologies acquired S3 Semiconductors, a provider of mixed-signal and RF ASICs and IP. Based in Ireland, S3 Semiconductors was founded in 1986. S3 Semiconductors will become a business unit of Adesto and will continue to operate under its current model in the $35 million deal. S3 Semiconductor's parent company, S3 Group, will continue as a separate... » read more

System-Level Power Modeling Takes Root


Power, heat, and their combined effects on aging and reliability, are becoming increasingly critical variables in the design of chips that will be used across a variety of new and existing markets. As more processing moves to edge, where sensors are generating a tsunami of data, there are a number of factors that need to be considered in designs. On one side, power budgets need to reflect th... » read more

The Week In Review: Design


M&A ANSYS finalized its acquisition of OPTIS. Founded in 1989, OPTIS provided software for scientific simulation of light, human vision and physics-based visualization. The acquisition boosts the company's automotive simulation portfolio with radar, lidar and camera simulation. Terms were not disclosed. IP Arm debuted the Cortex-M35P processor. Aimed at IoT applications, the IP combine... » read more

Partitioning Becomes More Difficult


The divide-and-conquer approach that has been the backbone of verification for decades is becoming more difficult at advanced nodes. There are more interactions from different blocks and features, more power domains, more physical effects to track, and far more complex design rules to follow. This helps explain why the number of tools required on each design—simulation, prototyping, em... » read more

More Nodes, New Problems


The rollout of leading-edge process nodes is accelerating rather than slowing down, defying predictions that device scaling would begin to subside due to rising costs and the increased difficulty of developing chips at those nodes. Costs are indeed rising. So are the number of design rules, which reflect skyrocketing complexity stemming from multiple patterning, more devices on a chip, and m... » read more

Processing Moves To The Edge


Edge computing is evolving from a relatively obscure concept into an increasingly complex component of a distributed computing architecture, in which processing is being shifted toward end devices and satellite data facilities and away from the cloud. Edge computing has gained attention in two main areas. One is the [getkc id="78" kc_name="industrial IoT"], where it serves as a do-it-yoursel... » read more

Mesh Networking Grows For ICs


Mesh networks were invented to create rich interaction among groups of almost-unrelated peers, but now they are showing up in everything from advanced chip packages to IoT networks. The flexibility of a many-to-many peer-connection model made the mesh approach a favorite for two-dimensional network-on-a-chip topologies, to the point where they began to supplant data-bus connections during th... » read more

Looking For The Elephant In The Valley


As a new arrival in the Silicon Valley and a woman, my head is full of statistics and charts. Not the kind that data scientists use to power their decision-making, but the kind that has made its way into the public discourse more and more in the last few years—diversity numbers in the tech industry. Armed with this data, I set out to talk to my company’s female CEO, Sundari Mitra, as wel... » read more

When AI Goes Awry


The race is on to develop intelligent systems that can drive cars, diagnose and treat complex medical conditions, and even train other machines. The problem is that no one is quite sure how to diagnose latent or less-obvious flaws in these systems—or better yet, to prevent them from occurring in the first place. While machines can do some things very well, it's still up to humans to devise... » read more

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