Results 71 to 80 of about 25,587 (261)
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
Hardware Acceleration for Deep Learning
Deep learning neural models require hardware acceleration. The current thirst for this acceleration is exceeding current capabilities and reality. At current trends, by 2045, one half of the world’s electricity will be consumed by training deep learning
David Bisant
doaj
Drawing inspiration from the layered hard‐soft architecture found in sea sponges, this work establishes a new framework for architected cementitious composites (ACC) through multi‐material additive manufacturing (MMAM) process. The integration of mortar and elastomer phases into layered architectures enables synergistic toughening mechanisms, including
Aimane Najmeddine +5 more
wiley +1 more source
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Code Detection for Hardware Acceleration Using Large Language Models
Large language models (LLMs) have been massively applied to many tasks, often surpassing state-of-the-art approaches. While their effectiveness in code generation has been extensively studied (e.g., AlphaCode), their potential for code detection remains ...
Pablo Antonio Martinez +2 more
doaj +1 more source
We demonstrate a neuromorphic synapse in 2D Fe3GaTe2 flakes. The device operates via a current‐driven transformation from a skyrmion‐lattice to a stripe‐domain state, yielding a linear anomalous Hall resistance response with a tunable slope to enable multiply‐accumulate operations. Simulations confirm its viability in artificial neural networks.
Jixiang Huang +20 more
wiley +1 more source
ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh +2 more
wiley +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Hardware acceleration of genomics data analysis: challenges and opportunities. [PDF]
Robinson T, Harkin J, Shukla P.
europepmc +1 more source
The Hardware Accelerator SFDL/SCL.
This paper presents a new multiprocessor architecture for modelling and simulation of digital circuits. To speed up the simulation process a special static algorithm for dividing modelled circuit components into equivalent classes (before the simulation starts) has been designed. In components of one class events will never appear at the same time. The
Blatný, J., Bartoněk, D.
openaire +1 more source

