Power/Performance Bits: Oct. 18

Speeding up memory with T-rays Scientists at the Moscow Institute of Physics and Technology (MIPT), the University of Regensburg in Germany, Radboud University Nijmegen in the Netherlands, and Moscow Technological University proposed a way to improve the performance of memory through using T-waves, or terahertz radiation, as a means of resetting memory cells. This process is several thousand... » read more

What’s Missing From Machine Learning

Machine learning is everywhere. It's being used to optimize complex chips, balance power and performance inside of data centers, program robots, and to keep expensive electronics updated and operating. What's less obvious, though, is there are no commercially available tools to validate, verify and debug these systems once machines evolve beyond the final specification. The expectation is th... » read more

Decoding The Brain

At the Design Automation Conference this year, Lou Scheffer, principal scientist for the Howard Hughes Medical Institute, gave a visionary talk entitled Learning from Life: Biologically Inspired Electronic Design. Scheffer is an IC design guy who came through Stanford and Caltech and worked for HP and [getentity id="22032" e_name="Cadence"] before switching to the medical field eight years a... » read more

Plotting The Next Semiconductor Road Map

The semiconductor industry is retrenching around new technologies and markets as Moore's Law becomes harder to sustain and growth rates in smart phones continue to flatten. In the past, it was a sure bet that pushing to the next process node would provide improvements in power, performance and cost. But after 22nm, the economics change due to the need for multi-patterning and finFETs, and th... » read more

System Bits: May 3

Neural network synapses In a development that could potentially be used as a basis for the hardware implementation of artificial neural networks, Moscow Institute of Physics and Technology (MIPT) researchers have created prototypes of electronic synapses based on ultra-thin films of hafnium oxide (HfO2). The team made the HfO2-based memristors measuring just 40x40 nm2, which exhibit propert... » read more

Power/Performance Bits: Feb. 9

Molybdenum disulfide memristors Researchers at Michigan Technological University constructed an ideal memristor based on molybdenum disulfide nanosheets. "Different from an electrical resistor that has a fixed resistance, a memristor possesses a voltage-dependent resistance," said Yun Hang Hu, professor of materials science and engineering at MTU, adding that a material's electric propert... » read more

Inside Neuromorphic Computing

Semiconductor Engineering sat down to talk about neuromorphic technology with Guy Paillet, chief executive of General Vision. The fabless IC design house is a pioneer and supplier of neuromorphic chips. What follows are excerpts of that conversation. SE: In 1993, you invented and co-patented a neural networking chip with IBM. Then, you joined General Vision in 1999. Briefly tell us about Gen... » read more

Inside AI And Deep Learning

Semiconductor Engineering sat down to talk with Dave Schubmehl, research director for content analytics, discovery and cognitive systems at International Data Corp. (IDC), a market research firm. Schubmehl’s research covers information access, artificial intelligence, cognitive computing, deep learning, machine learning and other topics. He also addressed neuromorphic technology. What follows... » read more

Integration Or Segregation

In the Electronics Butterfly Effect story, the observation was made that the electronics industry has gone non-linear, no longer supported by incremental density and cost-reducing improvements that Moore’s Law promised with each new node. Those incremental changes, over several decades, have meant that design and architecture have followed a predictable path with very few new ideas coming in ... » read more

Embedded Vision Becoming Ubiquitous

Embedded vision is becoming a topic of heated conversation thanks to the emergence of neural networks and their ability to make computer systems learn by example. Neural networks are a very different kind of processing element compared to the other kind of processors we have in the IP arsenal today in that they are not programmed in the same manner. They do not have a stream of instructions... » read more

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