Suchergebnisse - parallel computing (progress OR process)

A Hierarchical Task Graph Parallel Computing Framework for Chemical Process Simulation

Autoren: Shifeng Qu Shaoyi Yang Wenli Du et al.

Quelle: Engineering. 51:229-239

Prospects for Improving the Performance of Parallel Computing Using Python Subinterpreter Technology.

Autoren: Sinitsyn, R. D.

Quelle: Automatic Documentation & Mathematical Linguistics; 2025 Suppl 2, Vol. 59, pS167-S176, 10p

Introduction of dynamic constitutive model into parallel computing system of strata motion and modeling of impact fracture process of roadway

Autoren: Xuebin WANG Qinjie ZHANG Yishan PAN et al.

Quelle: Meitan xuebao, Vol 50, Iss 3, Pp 1473-1483 (2025)

Schlagwörter: roadway rockburst, dynamic constitutive model, viscous damping, parallel computing, continuum-discontinuum method, Geology, QE1-996.5, Mining engineering. Metallurgy, TN1-997

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/0253-9993

Zugangs-URL: https://doaj.org/article/ec99ec5193294d8fb447dfd2be6448ce

Application of Image Search System Based on CPU Parallel Computing in Smart Home Design.

Autoren: Senyang Lu Ziyan Yue

Quelle: Automatic Control & Computer Sciences; Aug2025, Vol. 59 Issue 4, p481-491, 11p

Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing.

Autoren: Schlund, Manuel Andela, Bouwe Benke, Jörg et al.

Quelle: Geoscientific Model Development; 2025, Vol. 18 Issue 13, p4009-4021, 13p

Schlagwörter: DISTRIBUTED computing, HIGH performance computing, COMPUTER systems, PARALLEL programming, SOFTWARE development tools, MATHEMATICAL optimization, ECOLOGICAL impact, ATMOSPHERIC models

Optimization of Parallel Information Processing in a Fault-tolerant Computing System of a Mobile Object with Temporal Redundancy of the Computing Process

Autoren: Ivan Zaharov Ali Musallam

Quelle: Intellectual Technologies on Transport. 0:30-36

Distributed Storage and Parallel Processing Technology of Financial Big Data under Cloud Computing Platform.

Autoren: Zhang, Xin¹ (AUTHOR) 18241683444@163.com

Quelle: Procedia Computer Science. 2025, Vol. 262, p714-721. 8p.

Schlagwörter: Databases, Process capability, Electronic data processing, Parallel processing, Computing platforms

Parallel Computing of Thermo-Fluid Modeling Related to the FSW Process

Autoren: Aoufi, Asdin Montheillet, Frank Desrayaud, Christophe et al.

Weitere Verfasser: Aoufi, Asdin Montheillet, Frank Desrayaud, Christophe et al.

Quelle: Key Engineering Materials. 966:109-114

Schlagwörter: Non-Linear Advection-Reaction-Diffusion, 0209 industrial biotechnology, Parallel Computing, 0203 mechanical engineering, Friction Stir Welding (FSW), Gpu Programming, Many-Core, OpenMP, 02 engineering and technology, Multi-Core, [SPI.MAT]Engineering Sciences [physics]/Materials

Theoretical and practical bases of application of parallel computing when solving problems of the numerical method in the educational process

Autoren: Perizat Gapbarova

Quelle: Scientific Herald of Uzhhorod University Series Physics. :1396-1404

Schlagwörter: 9. Industry and infrastructure, 4. Education

Distributed data processing and task scheduling based on GPU parallel computing.

Autoren: Li, Jun

Quelle: Neural Computing & Applications; Feb2025, Vol. 37 Issue 4, p1757-1769, 13p

Schlagwörter: DISTRIBUTED computing, GRAPHICS processing units, COMPUTER software, COMPUTER graphics, MATHEMATICS software

Analysis of High-Performance Parallel Computing using TOPSIS Method

Quelle: Computer Science, Engineering and Technology. 2:21-32

Schlagwörter: 9. Industry and infrastructure

Optimization of Sales Data Forecasting Computation Process Using Parallel Computing in Cloud Environment

Autoren: I Kadek Susila Satwika I Putu Susila Handika

Quelle: Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI), Vol 13, Iss 3 (2024)

Schlagwörter: Holt-Winters Exponential Smoothing, Modified Improved Particle Swarm Optimization, Parallel Computing, Cloud, Server, Information technology, T58.5-58.64

Dateibeschreibung: electronic resource

Relation: https://ejournal.undiksha.ac.id/index.php/janapati/article/view/85278; https://doaj.org/toc/2089-8673; https://doaj.org/toc/2548-4265

Zugangs-URL: https://doaj.org/article/6eec68328ffc4b939ce19d8e7482fb77

Dynamic Load Balancing Based on Hypergraph Partitioning for Parallel Geospatial Cellular Automata Models.

Autoren: Xia, Wei Guan, Qingfeng Li, Yuanyuan et al.

Quelle: ISPRS International Journal of Geo-Information; Mar2025, Vol. 14 Issue 3, p109, 25p

Schlagwörter: DYNAMIC loads, DYNAMIC balance (Mechanics), CELLULAR automata, DEAD loads (Mechanics), LAND cover

Three-dimensional capacitated route planning optimization using parallel computing for agricultural field involving obstacle.

Autoren: Khosravani Moghadam, Erfan Nørremark, Michael Zhou, Kun et al.

Quelle: Precision Agriculture; Dec2025, Vol. 26 Issue 6, p1-27, 27p

Parallel Computing Using CUDA and MultiThreading in Background Removal Process

Autoren: Yiqi Tew Wee Yan Lee Ga Men Tam

Quelle: 2024 3rd International Conference on Digital Transformation and Applications (ICDXA). :237-242

Computer Simulations of the Heat Transfer Process in Heterogeneous Media Using Parallel Computing Technologies

Autoren: Stanislav Prokhorov Anastasiya Ten

Quelle: Mathematical Physics and Computer Simulation. :26-36

Schlagwörter: 7. Clean energy

Exploring genomic datasets through machine learning methods leveraging high-performance computing

Autoren: Gómez Sánchez, Gonzalo

Weitere Verfasser: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: Berral García, Josep Lluís, Carrera Pérez, David

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Àrees temàtiques de la UPC::Informàtica

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/693566
https://dx.doi.org/10.5821/dissertation-2117-424249

TOUGH3-FLAC3D: a modeling approach for parallel computing of fluid flow and geomechanics

Autoren: Rinaldi, Antonio P Rutqvist, Jonny Luu, Keurfon et al.

Quelle: Computational Geosciences. 26(6)

Schlagwörter: Earth Sciences, Geoinformatics, Life on Land, THM processes, Coupled simulator, Parallel computing, TOUGH3, FLAC3D, Other Earth Sciences, Numerical & Computational Mathematics

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/2n14b29k
https://escholarship.org/content/qt2n14b29k/qt2n14b29k.pdf

Energy‐Efficient Online Training with In Situ Parallel Computing on Electrochemical Memory Arrays.

Autoren: Lu, Yingming Yang, Zhen Tao, Yaoyu et al.

Quelle: Advanced Intelligent Systems (2640-4567); Oct2025, Vol. 7 Issue 10, p1-16, 16p

Schlagwörter: ENERGY consumption, EDGE computing, SCIENTIFIC computing, REAL-time computing, PARALLEL processing, ARTIFICIAL neural networks

Parallel Gaussian Process Surrogate Bayesian Inference with Noisy Likelihood Evaluations

Autoren: Vehtari Aki Marttinen Pekka Järvenpää Marko et al.

Weitere Verfasser: Vehtari Aki Marttinen Pekka Järvenpää Marko et al.

Quelle: Järvenpää, M, Gutmann, M U, Vehtari, A & Marttinen, P 2021, ' Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations ', Bayesian analysis, vol. 16, no. 1, pp. 147-178 . https://doi.org/10.1214/20-BA1200
Bayesian Anal. 16, no. 1 (2021), 147-178

Schlagwörter: Parallel computing, FOS: Computer and information sciences, 0301 basic medicine, Computer Science - Machine Learning, Gaussian processes, Machine Learning (stat.ML), Surrogate modelling, Statistics - Computation, 01 natural sciences, Machine Learning (cs.LG), Methodology (stat.ME), 03 medical and health sciences, Statistics - Machine Learning, likelihood-free inference, expensive likelihoods, 0101 mathematics, Statistics - Methodology, Computation (stat.CO), surrogate modelling, Computer and information sciences, parallel computing, Expensive likelihoods, Likelihood-free inference, sequential experiment design, Sequential experiment design

Dateibeschreibung: application/pdf

Zugangs-URL: https://projecteuclid.org/journals/bayesian-analysis/volume-16/issue-1/Parallel-Gaussian-Process-Surrogate-Bayesian-Inference-with-Noisy-Likelihood-Evaluations/10.1214/20-BA1200.pdf
http://arxiv.org/abs/1905.01252
https://aaltodoc.aalto.fi:443/handle/123456789/102328
https://projecteuclid.org/journals/bayesian-analysis/volume-16/issue-1/Parallel-Gaussian-Process-Surrogate-Bayesian-Inference-with-Noisy-Likelihood-Evaluations/10.1214/20-BA1200.full
https://projecteuclid.org/journals/bayesian-analysis/volume-16/issue-1/Parallel-Gaussian-Process-Surrogate-Bayesian-Inference-with-Noisy-Likelihood-Evaluations/10.1214/20-BA1200.pdf
https://www.research.ed.ac.uk/en/publications/parallel-gaussian-process-surrogate-bayesian-inference-with-noisy
https://www.research.ed.ac.uk/portal/en/publications/parallel-gaussian-process-surrogate-bayesian-inference-with-noisy-likelihood-evaluations(3025e024-c2e0-41f4-b1ce-11e6382c5c97).html
https://research.aalto.fi/en/publications/parallel-gaussian-process-surrogate-bayesian-inference-with-noisy-likelihood-evaluations(25f21ffb-d92b-4fe6-973f-3c0719a30e98).html
http://hdl.handle.net/10138/354711
https://hdl.handle.net/20.500.11820/3025e024-c2e0-41f4-b1ce-11e6382c5c97
https://www.pure.ed.ac.uk/ws/files/189042522/Parallel_Gaussian_JARVENPAA_DAO19022020_VOR_CC_BY.pdf
https://aaltodoc.aalto.fi/handle/123456789/102328
https://projecteuclid.org/euclid.ba/1584583229