Archive for the ‘Nano News’ Category

A call for papers is now open for the IEEE Journal on Exploratory Solid-State Computational Devices and Circuits (JXCDC) special topic on “Spintronic Devices for Energy Efficient Computing”

Submission Deadline: September 5th, 2022

Aims and Scope

The inherent properties of ferromagnetic materials operating at room temperature and at the nanoscale coupled with various aspects of spin physics offer abundant possibilities and functionalities for developing novel computing and memory devices and their integration. The fundamental advantage of spintronic devices over the semiconductor-based switch is its projected ultra-low operation energy through different switching mechanisms. As an example, the interplay of ferroelectric effect (charge) and ferromagnetic effect (spin) can lead to the energy efficient switching. Meanwhile, the extremely efficient charge-to-spin conversion has become promising through the integration of recently discovered topological effects (topology and chirality) and ferromagnetic effect (spin). One of the key challenges for spintronic devices, the operation speed, has been well addressed recently through the usage of antiferromagnetic materials and the application of spin-orbit-torque switching mechanism and its interplay with other switching mechanisms.

The most apparent features of spintronic devices are their non-volatility and superior endurance behavior, where spin-based devices outperform other nonvolatile devices for designing computing blocks, nonvolatile processors, logic-in-memory arrays, hyper-dimensional computing. This will enable the energy-efficient computing systems of the future.

The intrinsic multi-functionalities of spintronic devices have generated many “unexpected computing devices and architectures” in the past decade. One example is the proposal and demonstration of the usage of magnetic tunnel junctions for computing using memory, stochastic computing and probabilistic computing.

This special topic of the IEEE JXCDC will publish original recent research centered around spintronic logic and memory devices for energy efficient computing, covering the research topics from new spintronic physics, new spintronic materials, to novel spintronic devices, to spintronic circuits and spintronic computing systems.

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IEEE Journal on Exploratory Solid-State Computational Devices and Circuits (JXCDC): Call for Papers on “Emerging Hardware for Cognitive Computing”

A call for papers is now open for the IEEE Journal on Exploratory Solid-State Computational Devices and Circuits special topic on “Emerging Hardware for Cognitive Computing.”

Aims and Scope:

Emerging materials and physics can be leveraged for new device-inherent behavior that can have system-level benefits. Motivation for device, circuit, and system behavior can be drawn from how the human brain processes certain data-intensive tasks adaptively and quickly, such as canonical image recognition. The field of neuromorphic computing has made great strides in implementing multi-weight synaptic behavior, as well as neuronal behavior such as integrate-and-fire and stochastic switching, and implementation of such behaviors in deep neural network (DNN) processing. Using CMOS, emerging resistive memories, and other device types as the basis, neuromorphic computing is innovating vertically from devices, to circuits, to systems to re-define how computation can be done. Looking forward, the realm of “cognitive computing” is inspired by new and continually emerging understanding of advanced brain and neuronal behavior that enables efficient and real-time learning and reaction.

This call for papers is on emerging hardware for cognitive computing. The focus and emphasis of these special topic papers is beyond DNN processing, as well as beyond multi-weight synapses and basic neuron integrating, firing, and stochasticity. Some example topics of interest include coherent reaction to multiple stimuli and input frequencies, hierarchical temporal memories, coupled dynamics between multiple stimuli and between devices or systems, both short-range and long-range connectivity in the devices and circuits, real-time adaptation to the data the computing system is processing, reconfigurability based on inputs, approximate computing that uses sparsity, and many other bio-inspired behaviors. Papers are encouraged that address implementation of advanced cognitive features at all levels (materials, device, circuits, and systems), including showing at a system level how such advanced functions can be useful for computing tasks and understanding the system-level energy efficiency and speed.

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