Archive for the ‘Nano News’ Category

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits

Special Topic on “Physics-based modeling and simulation of materials, devices and circuits of beyond-CMOS logic and memory technologies for energy efficient computing.”

Guest Editors

• Sumeet K. Gupta, Purdue University, guptask@purdue.edu
• Editor-in-Chief Azad Naeemi, Georgia Institute of Technology, azad@gatech.edu

Aims and Scope
Standard Complementary Metal Oxide Semiconductor (CMOS) technology and its advanced flavors in the form of FinFETs have propelled the electronic industry to its extraordinary success. While the CMOS technology may continue to deliver its remarkably powerful performance to next-generation computing platforms, it is quite clear that in the longer term, it has major challenges in scaling, suffers from power consumption and power density limitations and may not be amenable to the new demands of the emerging applications. This will require beyond-CMOS technologies to step in and augment CMOS. Whether it is the design of energy efficient scalable switches for logic design, or non-volatile memory, or the integration of memory and logic functionalities for general-purpose computers and application-specific accelerators, the need for the application of quantum materials to realize these new microelectronic devices has surged.

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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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