Author's Latest Posts


Cracking The Auto IC Market


The market for automotive electronics is booming, and it has set off a global scramble among established chipmakers and startups. What's becoming clear, though, is that not everyone understands just how different automotive is from the mobile market. Mobile is still the highest-volume market for semiconductors, but the growth has flattened. In contrast, the value of the automotive electronic... » read more

System Bits: Sept. 4


Quantum material is both conductor, insulator University of Michigan researchers reminded that quantum materials are a type of odd substance that could be many times more efficient at conducting electricity through a mobile device like an iPhone than the commonly used conductor silicon if physicists could figure out how they work. Now, a University of Michigan physicist has taken a step clo... » read more

Variation In Low-Power FinFET Designs


One of the biggest advantages of moving to the a leading edge process node is ultra-low voltage operation, where devices can achieve better performance using less power. But the latest generation process nodes also introduce a number of new challenges due to increased variation that can affect everything from signal integrity to manufacturing yield. While variation is generally well understo... » read more

Partitioning Drives Architectural Considerations


There are multiple reasons for design partitioning. One is complexity, because it’s faster and simpler to divide and conquer, particularly with third-party IP. A second reason involves power, where it may be more efficient to divide up functionality so each function be right-sized. A third involves performance, where memory utilization and processing can be split up according to functional pr... » read more

System Bits: Aug. 28


Characterizing quantum computers To accelerate and simplify the imposing task of diagnosing quantum computers, a Rice University computer scientist and his colleagues have proposed a method to do just this. The development of a nonconventional method as a diagnostic tool for powerful, next-generation computers that depend on the spooky actions of quantum bits — aka qubits — which are sw... » read more

Gaps In Verification Metrics


As design complexity has exploded, the verification effort has likewise grown exponentially, with many different types of verification being applied to different classes of design. A recent panel discussion with leading chipmakers examined this topic in an effort to shed light on design health and quality, measuring the success of verification, knowing when verification is complete, being on... » read more

System Bits: Aug. 21


Two types of computers create faster, less energy-intensive image processor for autonomous cars, security cameras, medical devices Stanford University researchers reminded that the image recognition technology that underlies today’s autonomous cars and aerial drones depends on artificial intelligence. These are the computers that essentially teach themselves to recognize objects like a dog, ... » read more

System Bits: Aug. 14


Machine-learning system determines the fewest, smallest doses that could still shrink brain tumors In an effort to improve the quality of life for patients by reducing toxic chemotherapy and radiotherapy dosing for glioblastoma, the most aggressive form of brain cancer, MIT researchers are employing novel machine-learning techniques. According to the team, glioblastoma is a malignant tumor ... » read more

Process Variation Not A Solved Issue


Semiconductor Engineering sat down to talk about process variation in advanced nodes, and how design teams are coping, with Christoph Sohrmann, a member of the Advanced Physical Verification group in Fraunhofer’s Division of Engineering of Adaptive Systems (EAS); Juan Rey, vice president of engineering at Mentor, A Siemens Business; and Stephen Crosher, CEO of Moortec Semiconductor. What foll... » read more

System Bits: Aug. 7


ML leverages existing hospital patient data to detect trouble Focusing on emergency and critical care patients, a University of Michigan spinout, Fifth Eye, has developed a system that combines a machine learning algorithm with signal processing to monitor the autonomic nervous system of hospital patients and interprets the data every two minutes, which can sometimes be almost two days faster ... » read more

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