Author's Latest Posts


Big Challenges, Changes For Debug


By Ann Steffora Mutschler & Ed Sperling Debugging a chip always has been difficult, but the problem is getting worse at 7nm and 5nm. The number of corner cases is exploding as complexity rises, and some bugs are not even on anyone's radar until well after devices are already in use by end customers. An estimated 39% of verification engineering time is spent on debugging activities the... » read more

Women In Power


This is not my usual, technically-focused report, but it's important sometimes to reflect on the human side of the industry, which can seem woefully absent at times in the scramble to get projects out the door and meet quarterly numbers. This past Tuesday, November 28, I moderated a panel of women who are truly inspirational for the achievements in their respective parts of the industry, an... » read more

Prototyping Partitioning Problems


Gaps are widening in the prototyping of large, complex chips because the speed and capacity of the FPGA is not keeping pace with rapid rollout pace of advanced ASICs. This is a new twist for a well-established market. Indeed, prototyping with FPGAs is as old as the [gettech id="31071" t_name="FPGAs"] themselves. Even before they were called FPGAs, logic accelerators or LCAs (logic cell ar... » read more

System Bits: Nov. 28


Better absorbing materials
 University of Illinois bioengineers have taken a new look at an old tool to help characterize a class of materials called metal organic frameworks (MOFs), used to detect, purify and store gases. The team believes these could help solve some of the world's most challenging energy, environmental and pharmaceutical challenges – and even pull water molecules straigh... » read more

System Bits: Nov. 21


MIT-Lamborghini to develop electric car Members of the MIT community were recently treated to a glimpse of the future as they passed through the Stata Center courtyard as the Lamborghini Terzo Millenio (Third Millennium) was in view, which is an automobile prototype for the third millennium. [caption id="attachment_429209" align="alignnone" width="300"] Lamborghini is relying on MIT to make i... » read more

The Return Of Body Biasing


Body biasing is making a comeback across a wide swath of process nodes as designers wrestle with how to build mobile devices with more functionality and longer battery life. Consider an ultra-low-power IoT device with a wireless sensor, for example, which is meant to last for years without changing a battery. Body biasing can be used to create an ultra-low-leakage sleep state. “In that ... » read more

System Bits: Nov. 14


Tracking cyber attacks According to Georgia Tech, assessing the extent and impact of network or computer system attacks has been largely a time-consuming manual process, until now since a new software system being developed by cybersecurity researchers here will largely automate that process, allowing investigators to quickly and accurately pinpoint how intruders entered the network, what data... » read more

Getting Power Management Right


Getting power management right in the era of heterogeneous SoCs is a multi-pronged effort, there's no getting around it. Engineering teams daily try to squeeze more and more power from their designs, which many times includes adding human resources and expertise to the project. Take an example where a design team leader gets the mandate to include high level synthesis in the design metho... » read more

Lots Of Little Knobs For Power


Dynamic power is becoming a much bigger worry at new nodes as more finFETs are packed on a die and wires shrink to the point where resistance and capacitance become first-order effects. Chipmakers began seeing dynamic power density issues with the first generation of [getkc id="185" kc_name="finFETs"]. While the 3D transistor structures reduced leakage current by providing better gate contro... » read more

System Bits: Nov. 7


Exposing logic errors in deep neural networks In a new approach meant to brings transparency to self-driving cars and other self-taught systems, researchers at Columbia and Lehigh universities have come up with a way to automatically error-check the thousands to millions of neurons in a deep learning neural network. Their tool — DeepXplore — feeds confusing, real-world inputs into the ... » read more

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