Results 91 to 100 of about 55,999 (288)
Advanced Electronic Materials, EarlyView.A lead‐free perovskite memristive solar cell structure that call emulate both synaptic and neuronal functions controlled by light and electric fields depending on top electrode type. ABSTRACT Memristive devices based on halide perovskites hold strong promise to provide energy‐efficient systems for the Internet of Things (IoT); however, lead (Pb ...
Michalis Loizos +4 more
wiley +1 more source
Implementation of the parallel mean shift-based image segmentation algorithm on a GPU cluster
International Journal of Digital Earth, 2019 The mean shift image segmentation algorithm is very computation-intensive. To address the need to deal with a large number of remote sensing (RS) image segmentations in real-world applications, this study has investigated the parallelization of the mean ...
Fang Huang +6 more
doaj +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
MATria: a unified centrality algorithm
BMC Bioinformatics, 2019 Background Computing centrality is a foundational concept in social networking that involves finding the most “central” or important nodes. In some biological networks defining importance is difficult, which then creates challenges in finding an ...
Trevor Cickovski +2 more
doaj +1 more source
Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines [PDF]
, 2009 Nowadays, several industrial applications are being ported to parallel architectures. In fact, these platforms allow acquire more performance for system modelling and simulation.
Dekeyser, Jean-Luc +3 more
core +2 more sources
, 2013 Recent innovations focused around {\em parallel} processing, either through systems containing multiple processors or processors containing multiple cores, hold great promise for enhancing the performance of the trigger at the LHC and extending its ...
Halyo, V. +4 more
core +1 more source
Advanced Electronic Materials, EarlyView.ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez +10 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
Analysis of Fast Fourier Transformations algorithm for CUDA Architecture
Lietuvos Matematikos Rinkinys, 2012 In this work Fast Fourier transformation algorithm for general purpose graphics processing unit processing (GPGPU) is discussed. Algorithm structure and individual stages performance were analysed.
Beatričė Andziulienė +2 more
doaj +1 more source
Improving GPU-accelerated Adaptive IDW Interpolation Algorithm Using Fast kNN Search
, 2016 This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting ...
Mei, Gang, Xu, Liangliang, Xu, Nengxiong
core +1 more source