Related papers: Scalable Superconducting Nanowire Memory Array wit…
Ordered nanoarrays, i.e. regular patterns of quantum structures at the nanometre scale, have recently been synthesized in a wide range of systems. Here I explore a possible route to technological exploitation: assuming a simple form of…
Reducing the memory footprint of neural networks is a crucial prerequisite for deploying them in small and low-cost embedded devices. Network parameters can often be reduced significantly through pruning. We discuss how to best represent…
We have calculated the key characteristics of associative (content-addressable) spatial-temporal memories based on neuromorphic networks with restricted connectivity - "CrossNets". Such networks may be naturally implemented in…
Ternary content addressable memory (TCAM) has been a critical component in caches, routers, etc., in which density, speed, power efficiency, and reliability are the major design targets. There have been the conventional low-write-power but…
Neuromorphic computing aims to reproduce the energy efficiency and adaptability of biological intelligence in hardware. Superconducting devices are an attractive platform due to their ultra-low dissipation and fast switching dynamics. Here…
We present a nanomechanical device design to be used in a non-volatile mechanical memory point. The structure is composed of a suspended slender nanowire (width : 100nm, thickness 430nm length : 8 to 30$\mu$m) clamped at its both ends.…
A new concept for nonvolatile superconducting memories is proposed. The devices combine ferromagnetic dots for the storage of the data and Josephson junctions for their readout. Good scalability is expected for large scale integration.…
Amorphous insulators have localized wave functions that decay with the distance $r$ following exp($-r/\zeta$). Since nanoscale conduction is not excluded at $r<\zeta$, one may use amorphous insulators and take advantage of their size effect…
Reservoir computing is an emerging methodology for neuromorphic computing that is especially well-suited for hardware implementations in size, weight, and power (SWaP) constrained environments. This work proposes a novel hardware…
The growth of connected intelligent devices in the Internet of Things has created a pressing need for real-time processing and understanding of large volumes of analogue data. The difficulty in boosting the computing speed renders digital…
A promising way to store quantum information is by encoding it in the bosonic excitations of microwave resonators. This provides for long coherence times, low dephasing rates, as well as a hardware-efficient approach to quantum error…
A novel high-fan-in differential superconductor neuron structure designed for ultra-high-performance Spiking Neural Network (SNN) accelerators is presented. Utilizing a high-fan-in neuron structure allows us to design SNN accelerators with…
A quantum memory that can store quantum states faithfully and retrieve them on demand has wide applications in quantum information science. An efficient quantum memory in the microwave regime working alongside quantum processors based on…
The first contribution of this paper is the development of extremely dense, energy-efficient mixed-signal vector-by-matrix-multiplication (VMM) circuits based on the existing 3D-NAND flash memory blocks, without any need for their…
The recent development of the superlattice nanowire pattern transfer (SNAP) technique allows for the fabrication of arrays of nanowires at a diameter, pitch, aspect ratio, and regularity beyond competing approaches. Here, we report the…
Much effort has been devoted to device and materials engineering to realize nanoscale resistance random access memory (RRAM) for practical applications, but there still lacks a rational physical basis to be relied on to design scalable…
Analog memory is of great importance in neurocomputing technologies field, but still remains difficult to implement. With emergence of memristors in VLSI technologies the idea of designing scalable analog data storage elements finds its…
Fast cryogenic switches with ultra-low power dissipation are highly sought-after for control electronics of quantum computers, space applications and next generation logic circuits. However, existing high-frequency switches are often bulky,…
Recurrent transducer models have emerged as a promising solution for speech recognition on the current and next generation smart devices. The transducer models provide competitive accuracy within a reasonable memory footprint alleviating…
This letter analyzes the scaling property of nanowire (NW) phase change memory (PCM) using analytic and numerical methods. The scaling scenarios of the three widely-used NW PCM peration schemes (constant electric field, voltage, and…