Results 101 to 110 of about 79,263 (305)

1 NVIDIA OpenGL Extension Specifications

, 2007
This document is protected by copyright and contains information proprietary to NVIDIA Corporation. This document is an abridged collection of OpenGL extension specifications limited to those extensions for new OpenGL functionality introduced by the ...
Nvidia Opengl
core  

Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami

Advanced Science, EarlyView.
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning, Lu Lu, Sophie Leanza, Ruike Renee Zhao   +3 more
wiley   +1 more source

NVIDIA Automated Testing

, 2012
This project conducted at NVIDIA is aimed to research open-source testing frameworks, and develop a software adapter that coordinates between NVIDIA’s test infrastructure and a given framework.
Ma, Xiaoli, Fields, Jackson Ganister, Brown, Richard Pearce   +2 more
core   +3 more sources

GPU cluster for acceleration of scientific and engineering applications in the context of higher education [PDF]

Many fields of research now rely on High Performance Computing (HPC) systems which can process ever larger datasets, with increasing accuracy and speed. Many universities now provide a HPC service.
Newall, Matthew
core   +2 more sources

CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search

BMC Bioinformatics
Background The maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive.
Bertil Schmidt, Felix Kallenborn, Alejandro Chacon, Christian Hundt   +3 more
doaj   +1 more source

Multi-process thermodynamic graph learning for 2D fluid simulation

Virtual Reality & Intelligent Hardware
Solving partial differential equations (PDEs) for fluid simulation is computationally expensive, especially when dealing with complex geometries and high-resolution meshes.
Yidi WANG, Aik Beng NG, Simon SEE, Zhengkui WANG, Frank GUAN   +4 more
doaj   +1 more source

Quantum simulation of CO2 chemisorption in an amine-functionalized metal–organic framework [PDF]

AIP Advances
We perform a series of calculations using simulated quantum processing units (QPUs), accelerated by the NVIDIA CUDA-Q platform, focusing on a molecular analog of an amine-functionalized metal–organic framework, a promising class of materials for CO2 ...
Jonathan R. Owens, Marwa H. Farag, Pooja Rao, Annarita Giani   +3 more
doaj   +1 more source

Multiscale Coupling From Mastication to Retronasal Aroma Perception: The PG‐DTCFN Model and Multiphysics Simulation

Advanced Science, EarlyView.
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen, Xiongfeng He, Zihao Li, Zidong Chen, Jiajin Sun, Xinyu Jiang, Yunhui Zhang, Lizhang Wu, Ran Wang, Jingnan Lu, Bo Wang, Kezhou Cai, Baocai Xu   +12 more
wiley   +1 more source

Solar Irradiance Forecasting Using a Hybrid Quantum Neural Network: A Comparison on GPU-Based Workflow Development Platforms

IEEE Access
Modern renewable power operations can be enhanced by integrating deep neural networks, particularly for forecasting solar irradiance. Recent advancements in quantum computing have shown potential improvements in classical deep neural networks.
Ying-Yi Hong, Dylan Josh Domingo Lopez, Yun-Yuan Wang   +2 more
doaj   +1 more source

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

Advanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu, Xiao Xu, Fengming Hu, Yuanzhe Liang, Zidong Yin, Biao Qi, Ruolin Liu, Ziyi Dai, Jianyi Luo, Bingpu Zhou   +9 more
wiley   +1 more source