Related papers: Stochastic Computing Implemented by Skyrmionic Log…
In order to address many of the challenges and bottlenecks currently experienced by traditional charge based technologies, various alternatives are being actively explored to provide potential solutions of device miniaturization and scaling…
Magnetic skyrmions are nanoscale topological spin structures offering great promise for next-generation information storage technologies. The recent discovery of sub-100 nm room temperature (RT) skyrmions in several multilayer films has…
Current-driven magnetic skyrmions show promise as carriers of information bits in racetrack magnetic memory applications. Specifically, the utilization of skyrmions in synthetic antiferromagnetic (SAF) systems is highly attractive due to…
SoCs are now designed with their own AI accelerator segment to accommodate the ever-increasing demand of Deep Learning (DL) applications. With powerful MAC engines for matrix multiplications, these accelerators show high computing…
Magnetic skyrmions are quasiparticle configurations in a magnetic film that can act as information carrying bits for ultrasmall, all-electronic nonvolatile memory. The skyrmions can be nucleated and driven by spin-orbit torque from a…
Algorithms and a hardware accelerator for performing stochastic rounding (SR) are presented. The main goal is to augment the ARM M4F based multi-core processor SpiNNaker2 with a more flexible rounding functionality than is available in the…
Skyrmions and antiskyrmions are nanoscale swirling textures of magnetic moments formed by chiral interactions between atomic spins in magnetic non-centrosymmetric materials and multilayer films with broken inversion symmetry. These…
Over the last decade, memristive devices have been widely adopted in computing for various conventional and unconventional applications. While the integration density, memory property, and nonlinear characteristics have many benefits,…
While magnetic solid-state memory has found commercial applications to date, magnetic logic has rather remained on a conceptual level so far. Here, we discuss open challenges of different spintronic logic approaches, which use magnetic…
Skyrmions with topologically stable configurations have shown a promising route toward magnetic and photonic materials for information processing due to their defect-immune and low-driven energy. However, the practical application of…
Spiking Neural Networks (SNNs) have been recently integrated into Transformer architectures due to their potential to reduce computational demands and to improve power efficiency. Yet, the implementation of the attention mechanism using…
Skyrmion bags as spin textures with arbitrary topological charge are expected to be the carriers in racetrack memory. Here, we theoretically and numerically investigated the dynamics of skyrmion bags in an anisotropy gradient. It is found…
The hardware-friendly implementation of transcendental functions remains a longstanding challenge in design automation. These functions, which cannot be expressed as finite combinations of algebraic operations, pose significant complexity…
Magnetic skyrmions and multiferroics are the most interesting objects in nanostructure science that have great potential in future spin-electronic technology. The study of the multiferroic skyrmions has attracted much interest in recent…
Magnetic skyrmions are highly promising candidates for future spintronic applications such as skyrmion racetrack memories and logic devices. They exhibit exotic and complex dynamics governed by topology and are less influenced by defects,…
Magnetic skyrmions, renowned for their fascinating electromagnetic properties, hold potential for next-generation topological spintronic devices. Recent advancements have unveiled a rich tapestry of 3D topological magnetism. Nevertheless,…
Skyrmion is a topologically protected spin texture excited in magnetic thin films. The radii of skyrmions are typically 10-100 nm. Because of the size, the skyrmion is expected to be a candidate for memory and novel-device usages. To…
On metrics of density and power efficiency, neuromorphic technologies have the potential to surpass mainstream computing technologies in tasks where real-time functionality, adaptability, and autonomy are essential. While algorithmic…
Stochastic kinetic models (SKMs) are increasingly used to account for the inherent stochasticity exhibited by interacting populations of species in areas such as epidemiology, population ecology and systems biology. Species numbers are…
Physical reservoir computing (RC) is a beyond von-Neumann computing paradigm that harnesses the dynamical properties of a complex physical system (reservoir) to process information efficiently in tasks such as pattern recognition. This…