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How We Found the Missing Memristor

The memristor—the functional equivalent of a synapse—could revolutionize circuit design

18 min read
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artist’s conception of a memristor

Thinking Machine: This artist’s conception of a memristor shows a stack of multiple crossbar arrays, the fundamental structure of R. Stanley Williams’s device. Because memristors behave functionally like synapses, replacing a few transistors in a circuit with memristors could lead to analog circuits that can think like a human brain.

Bryan Christie Design
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It’s time to stop shrinking. Moore’s Law, the semiconductor industry’s obsession with the shrinking of transistors and their commensurate steady doubling on a chip about every two years, has been the source of a 50-year technical and economic revolution. Whether this scaling paradigm lasts for five more years or 15, it will eventually come to an end. The emphasis in electronics design will have to shift to devices that are not just increasingly infinitesimal but increasingly capable.

Earlier this year, I and my colleagues at Hewlett-Packard Labs, in Palo Alto, Calif., surprised the electronics community with a fascinating candidate for such a device: the memristor. It had been theorized nearly 40 years ago, but because no one had managed to build one, it had long since become an esoteric curiosity. That all changed on 1 May, when my group published the details of the memristor in Nature.

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Artificial Synapses 10,000x Faster Than Real Thing

New protonic programmable resistors may help speed learning in deep neural networks

3 min read
Conceptual illustration shows a brain shape made of circuits on a multilayered chip structure.
Ella Maru Studio and Murat Onen

New artificial versions of the neurons and synapses in the human brain are up to 1,000 times smaller than neurons and at least 10,000 times faster than biological synapses, a study now finds.

These new devices may help improve the speed at which the increasingly common and powerful artificial intelligence systems known as deep neural networks learn, researchers say.

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Amazon to Acquire iRobot F​or $1.7 Billion

The deal will give the e-retail behemoth even more access to our homes

4 min read
A photo of an iRobot Roomba with an Amazon logo digitally added to it
Photo-illustration: iStockphoto/Amazon/IEEE Spectrum

This morning, Amazon and iRobot announced “a definitive merger agreement under which Amazon will acquire iRobot” for US $1.7 billion. The announcement was a surprise, to put it mildly, and we’ve barely had a chance to digest the news. But taking a look at what’s already known can still yield initial (if incomplete) answers as to why Amazon and iRobot want to team up—and whether the merger seems like a good idea.

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How New Storage Technologies Enhance HPC Systems

Different storage technologies can maximize the efficiency and effectiveness of HPC systems while providing high capacity and low latency storage, and minimizing network bandwidth and power consumption

1 min read
How New Storage Technologies Enhance HPC Systems

High-performance computing (HPC) has historically been available primarily to governments, research institutions, and a few very large corporations for modeling, simulation, and forecasting applications. As HPC platforms are being deployed in the cloud for shared services, high-performance computing is becoming much more accessible, and its use is benefiting organizations of all sizes. Increasing investment in the industrial internet of things (IIoT), artificial intelligence (AI), and electronic design automation (EDA) and silicon IP for engineering development are a few factors that are driving increased use of high-performance computing systems. In general, increasingly complex models for big data processing, simulation, and forecasting are driving a need for more compute power and greater storage capacity & performance.

This white paper highlights how different storage technologies can maximize the efficiency and effectiveness of HPC systems while providing high capacity and low latency storage, and minimizing network bandwidth and power consumption.