Results 51 to 60 of about 175,847 (284)

A Thermodynamic 3D Model for the Simulation of Diffusion‐Controlled Alloying Processes in Heterogeneous Material Structures

Advanced Engineering Materials, EarlyView.
A numerical model resulting from irreversible thermodynamics for describing transport processes is introduced, focusing on thermodynamic activity gradients as the actual driving force for diffusion. Implemented in CUDA C++ and using CalPhaD methods for determining the necessary activity data, the model accurately simulates interdiffusion in aluminum ...
Ulrich Holländer, Leonhard Holländer, André Langohr, Hans Jürgen Maier   +3 more
wiley   +1 more source

GPU-Assisted Computation of Centroidal Voronoi Tessellation [PDF]

IEEE Transactions on Visualization and Computer Graphics, 2011
Centroidal Voronoi tessellations (CVT) are widely used in computational science and engineering. The most commonly used method is Lloyd's method, and recently the L-BFGS method is shown to be faster than Lloyd's method for computing the CVT. However, these methods run on the CPU and are still too slow for many practical applications.
Wang, W, Rong, G, Yin, X, Gu, D, Guo, X, Liu, Y   +5 more
openaire   +6 more sources

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

High-Performance Homomorphic Matrix Completion on Multiple GPUs

IEEE Access, 2020
In various applications such as trajectory tracking in mobile social networks and online recommendation systems, the massive raw data are often incomplete due to various unpredictable or unavoidable reasons. Matrix completion algorithms are effective for
Tao Zhang, Han Lu, Xiao-Yang Liu
doaj   +1 more source

GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments

Frontiers in Big Data, 2021
Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algorithms can be computationally expensive.
Michael Wang, Tingjun Yang, Maria Acosta Flechas, Philip Harris, Benjamin Hawks, Burt Holzman, Kyle Knoepfel, Jeffrey Krupa, Kevin Pedro, Nhan Tran, Nhan Tran   +10 more
doaj   +1 more source

GAMER: a GPU-Accelerated Adaptive Mesh Refinement Code for Astrophysics

, 2009
We present the newly developed code, GAMER (GPU-accelerated Adaptive MEsh Refinement code), which has adopted a novel approach to improve the performance of adaptive mesh refinement (AMR) astrophysical simulations by a large factor with the use of the ...
Aubert, Bagla, Bryan, Campbell, Collins, Frigo, Fryxell, Gingold, Godunov, Hallman, Hockney, Hsi-Yu Schive, Klypin, Kravtsov, Landau, Martin, NVIDIA, O'Shea, Pen, Press, Ricker, Tzihong Chiueh, Woo, Yu-Chih Tsai   +23 more
core   +2 more sources

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Parallelizing the cryo‐EM structure determination in THUNDER using GPU cluster

Engineering Reports
Electron cryo‐microscopy (cryo‐EM) is a powerful tool utilized by biologists for understanding the mysteries of life. However, obtaining high‐resolution 3D reconstructions from innumerable noisy images of macromolecules is an extremely complicated task ...
Zhao Wang, Huabin Ruan, Guangwen Yang, Xueming Li   +3 more
doaj   +1 more source

TBEM: Testing-Based GPU-Memory Consumption Estimation for Deep Learning

IEEE Access, 2022
Deep Learning (DL) has been successfully implemented and deployed to various software service applications. During the training process of DL, a large amount of GPU computing resources is required, but it is difficult for developers to accurately ...
Haiyi Liu, Shaoying Liu, Chenglong Wen, W. Eric Wong   +3 more
doaj   +1 more source

Bio‐Orthogonally Crosslinked Supramolecular Polymer Bottlebrush Hydrogels for Long‐Term 3D Cell Culture

Advanced Functional Materials, EarlyView.
Fibrous benzenetrispeptide (BTP) hydrogels, fabricated via strain‐promoted azide‐alkyne cycloaddition (SPAAC) crosslinking, form robust, bioinert networks. These hydrogels can support 3D cell culture, where cell viability and colony growth depend on the fiber content.
Ceren C. Pihlamagi, David Pretzel, Peer Nölte, Kourosh Rezaei, Ulrich S. Schubert, Johannes C. Brendel   +5 more
wiley   +1 more source