Results 81 to 90 of about 312,991 (292)
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
Positively Charged Polymer‐Brush MOFs for Large‐Area, Pressure‐Resistant Gas Separation Membranes
Advanced Materials, EarlyView.A universal POPA strategy enables positively charged polymer‐brush MOFs with self‐adaptive interfacial interlocking to resist aggregation under fast processing. This design ensures seamless dispersion within large‐area selective layers, achieving 1 m‐wide roll‐to‐roll fabrication of pressure‐resistant MMCMs with tunable CO2 separation performance ...
Yi Yang +11 more
wiley +1 more source
Particle methods parallel implementations by GP-GPU strategies [PDF]
, 2011 This paper outlines the problems found in the parallelization of SPH (Smoothed Particle Hydrodynamics) algorithms using Graphics Processing Units.
Cercós Pita, Jose Luis +3 more
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Fast MPEG-CDVS Encoder with GPU-CPU Hybrid Computing
, 2017 The compact descriptors for visual search (CDVS) standard from ISO/IEC moving pictures experts group (MPEG) has succeeded in enabling the interoperability for efficient and effective image retrieval by standardizing the bitstream syntax of compact ...
Chen, Jie +9 more
core +1 more source
Assembling a True “Olympic Gel” From over 16 000 Combinatorial DNA Rings
Advanced Materials, EarlyView.Olympic gels are an elusive class of soft matter, consisting of molecular networks held together purely by mechanically interlocked rings. Their topological structure promises unique properties and functions, but their synthesis has proven notoriously difficult.
Sarah K. Speed +9 more
wiley +1 more source
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design
, 2016 The most widely used machine learning frameworks require users to carefully tune their memory usage so that the deep neural network (DNN) fits into the DRAM capacity of a GPU. This restriction hampers a researcher's flexibility to study different machine
Clemons, Jason +4 more
core +1 more source
Advanced Materials Technologies, EarlyView.ABSTRACT Quantifying oral polymorphonuclear neutrophils (oPMNs) is a clinically validated approach for assessing periodontal inflammation. However, current methods, such as manual hemocytometry and flow cytometry, are time‐consuming (>3 h), require invasive sampling, and depend on staining and complex instrumentation, making them unsuitable for point ...
Mohsen Hassani +9 more
wiley +1 more source
Advanced Materials Technologies, EarlyView.This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov +3 more
wiley +1 more source
A Bitslice Implementation of Anderson’s Attack on A5/1
Open Engineering, 2018 The A5/1 keystream generator is a part of Global System for Mobile Communications (GSM) protocol, employed in cellular networks all over the world. Its cryptographic resistance was extensively analyzed in dozens of papers.
Bulavintsev Vadim +3 more
doaj +1 more source
Workload-aware Automatic Parallelization for Multi-GPU DNN Training
, 2019 Deep neural networks (DNNs) have emerged as successful solutions for variety of artificial intelligence applications, but their very large and deep models impose high computational requirements during training.
Choi, Jungwook +5 more
core +1 more source