Artigos de revistas sobre o tema "GPU pipeline"
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Magro, A., K. Zarb Adami e J. Hickish. "GPU-Powered Coherent Beamforming". Journal of Astronomical Instrumentation 04, n.º 01n02 (junho de 2015): 1550002. http://dx.doi.org/10.1142/s2251171715500026.
Texto completo da fonteMovania, Muhammad Mobeen, e Lin Feng. "A Novel GPU-Based Deformation Pipeline". ISRN Computer Graphics 2012 (15 de dezembro de 2012): 1–8. http://dx.doi.org/10.5402/2012/936315.
Texto completo da fonteVasyliv, О. B., О. S. Titlov e Т. А. Sagala. "Modeling of the modes of natural gas transportation by main gas pipelines in the conditions of underloading". Oil and Gas Power Engineering, n.º 2(32) (27 de dezembro de 2019): 35–42. http://dx.doi.org/10.31471/1993-9868-2019-2(32)-35-42.
Texto completo da fonteKingyens, Jeffrey, e J. Gregory Steffan. "The Potential for a GPU-Like Overlay Architecture for FPGAs". International Journal of Reconfigurable Computing 2011 (2011): 1–15. http://dx.doi.org/10.1155/2011/514581.
Texto completo da fonteWang, Ke Nian, e Hui Min Du. "The FPGA Design and Implementation of Pipeline Image Processing in the GPU System". Applied Mechanics and Materials 380-384 (agosto de 2013): 3807–10. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3807.
Texto completo da fonteXiang, Yue, Peng Wang, Bo Yu e Dongliang Sun. "GPU-accelerated hydraulic simulations of large-scale natural gas pipeline networks based on a two-level parallel process". Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 75 (2020): 86. http://dx.doi.org/10.2516/ogst/2020076.
Texto completo da fonteAkyüz, Ahmet Oğuz. "High dynamic range imaging pipeline on the GPU". Journal of Real-Time Image Processing 10, n.º 2 (12 de setembro de 2012): 273–87. http://dx.doi.org/10.1007/s11554-012-0270-9.
Texto completo da fonteCao, Wei, Zheng Hua Wang e Chuan Fu Xu. "A Survey of General Purpose Computation of GPU for Computational Fluid Dynamics". Advanced Materials Research 753-755 (agosto de 2013): 2731–35. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.2731.
Texto completo da fonteAbdellah, Marwan, Ayman Eldeib e Amr Sharawi. "High Performance GPU-Based Fourier Volume Rendering". International Journal of Biomedical Imaging 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/590727.
Texto completo da fonteCheng, Sining, Huiyan Qu e Xianjun Chen. "Ray tracing collision detection based on GPU pipeline reorganization". Journal of Physics: Conference Series 1732 (janeiro de 2021): 012057. http://dx.doi.org/10.1088/1742-6596/1732/1/012057.
Texto completo da fonteGong, Qian, Esteban Vera, Dathon R. Golish, Steven D. Feller, David J. Brady e Michael E. Gehm. "Model-Based Multiscale Gigapixel Image Formation Pipeline on GPU". IEEE Transactions on Computational Imaging 3, n.º 3 (setembro de 2017): 493–502. http://dx.doi.org/10.1109/tci.2016.2612942.
Texto completo da fonteFu, Zhisong, T. James Lewis, Robert M. Kirby e Ross T. Whitaker. "Architecting the finite element method pipeline for the GPU". Journal of Computational and Applied Mathematics 257 (fevereiro de 2014): 195–211. http://dx.doi.org/10.1016/j.cam.2013.09.001.
Texto completo da fonteYe, Chang, Yuchen Li, Shixuan Sun e Wentian Guo. "gSWORD: GPU-accelerated Sampling for Subgraph Counting". Proceedings of the ACM on Management of Data 2, n.º 1 (12 de março de 2024): 1–26. http://dx.doi.org/10.1145/3639288.
Texto completo da fonteKim, Do-Hyun, e Chi-Yong Kim. "Design of a SIMT architecture GP-GPU Using Tile based on Graphic Pipeline Structure". Journal of IKEEE 20, n.º 1 (31 de março de 2016): 75–81. http://dx.doi.org/10.7471/ikeee.2016.20.1.075.
Texto completo da fonteGeorgii, Joachim, e Rudiger Westermann. "A Generic and Scalable Pipeline for GPU Tetrahedral Grid Rendering". IEEE Transactions on Visualization and Computer Graphics 12, n.º 5 (setembro de 2006): 1345–52. http://dx.doi.org/10.1109/tvcg.2006.110.
Texto completo da fonteKenzel, Michael, Bernhard Kerbl, Dieter Schmalstieg e Markus Steinberger. "A high-performance software graphics pipeline architecture for the GPU". ACM Transactions on Graphics 37, n.º 4 (10 de agosto de 2018): 1–15. http://dx.doi.org/10.1145/3197517.3201374.
Texto completo da fonteHou, Yi, Rongke Liu, Hao Peng e Ling Zhao. "High Throughput Pipeline Decoder for LDPC Convolutional Codes on GPU". IEEE Communications Letters 19, n.º 12 (dezembro de 2015): 2066–69. http://dx.doi.org/10.1109/lcomm.2015.2486764.
Texto completo da fonteMAGRO, A., J. HICKISH e K. Z. ADAMI. "MULTIBEAM GPU TRANSIENT PIPELINE FOR THE MEDICINA BEST-2 ARRAY". Journal of Astronomical Instrumentation 02, n.º 01 (setembro de 2013): 1350008. http://dx.doi.org/10.1142/s2251171713500086.
Texto completo da fonteBraga, Giani, Marcio M. Gonçalves e José Rodrigo Azambuja. "Software-controlled pipeline parity in GPU architectures for error detection". Microelectronics Reliability 148 (setembro de 2023): 115155. http://dx.doi.org/10.1016/j.microrel.2023.115155.
Texto completo da fonteLI, PING, HANQIU SUN, JIANBING SHEN e CHEN HUANG. "HDR IMAGE RERENDERING USING GPU-BASED PROCESSING". International Journal of Image and Graphics 12, n.º 01 (janeiro de 2012): 1250007. http://dx.doi.org/10.1142/s0219467812500076.
Texto completo da fonteGARBA, MICHAEL T., e HORACIO GONZÁLEZ–VÉLEZ. "ASYMPTOTIC PEAK UTILISATION IN HETEROGENEOUS PARALLEL CPU/GPU PIPELINES: A DECENTRALISED QUEUE MONITORING STRATEGY". Parallel Processing Letters 22, n.º 02 (16 de maio de 2012): 1240008. http://dx.doi.org/10.1142/s0129626412400087.
Texto completo da fonteUm, Taegeon, Byungsoo Oh, Byeongchan Seo, Minhyeok Kweun, Goeun Kim e Woo-Yeon Lee. "FastFlow: Accelerating Deep Learning Model Training with Smart Offloading of Input Data Pipeline". Proceedings of the VLDB Endowment 16, n.º 5 (janeiro de 2023): 1086–99. http://dx.doi.org/10.14778/3579075.3579083.
Texto completo da fonteMileff, Péter, e Judit Dudra. "Effective Pixel Rendering in Practice". Production Systems and Information Engineering 10, n.º 1 (2022): 1–15. http://dx.doi.org/10.32968/psaie.2022.1.1.
Texto completo da fonteCarrazza, Stefano, Juan Cruz-Martinez, Marco Rossi e Marco Zaro. "MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes". EPJ Web of Conferences 251 (2021): 03022. http://dx.doi.org/10.1051/epjconf/202125103022.
Texto completo da fonteLi, Tao, Qiankun Dong, Yifeng Wang, Xiaoli Gong e Yulu Yang. "Dual buffer rotation four-stage pipeline for CPU–GPU cooperative computing". Soft Computing 23, n.º 3 (6 de setembro de 2017): 859–69. http://dx.doi.org/10.1007/s00500-017-2795-0.
Texto completo da fonteGou, Chunyang, e Georgi N. Gaydadjiev. "Addressing GPU On-Chip Shared Memory Bank Conflicts Using Elastic Pipeline". International Journal of Parallel Programming 41, n.º 3 (3 de julho de 2012): 400–429. http://dx.doi.org/10.1007/s10766-012-0201-1.
Texto completo da fonteSánchez-Rojas, José Armando, José Aníbal Arias-Aguilar, Hiroshi Takemura e Alberto Elías Petrilli-Barceló. "Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots". Applied Sciences 11, n.º 22 (14 de novembro de 2021): 10736. http://dx.doi.org/10.3390/app112210736.
Texto completo da fonteZhuo, Jianghao, Ling Wang, Ke Xu e Jianwei Wan. "A Coupling Graphic Pipeline with Normal Mode Model for Rapid Calculation of Underwater Acoustic Field". Shock and Vibration 2021 (29 de janeiro de 2021): 1–7. http://dx.doi.org/10.1155/2021/8847664.
Texto completo da fonteNie, Xiao, Leiting Chen e Tao Xiang. "Real-Time Incompressible Fluid Simulation on the GPU". International Journal of Computer Games Technology 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/417417.
Texto completo da fonteWU, JIAWEN, FENGQUAN ZHANG e XUKUN SHEN. "GPU-BASED FLUID SIMULATION WITH FAST COLLISION DETECTION ON BOUNDARIES". International Journal of Modeling, Simulation, and Scientific Computing 03, n.º 01 (março de 2012): 1240003. http://dx.doi.org/10.1142/s179396231240003x.
Texto completo da fonteZamikhovskyi, L. M., O. L. Zamikhovska e V. V. Pavlyk. "Methodology for monitoring the technical condition of GPU type GTK-25i in the process of operation". Scientific Bulletin of Ivano-Frankivsk National Technical University of Oil and Gas, n.º 2(49) (30 de dezembro de 2020): 106–16. http://dx.doi.org/10.31471/1993-9965-2020-2(49)-106-116.
Texto completo da fontePeng, Bo, Tianqi Wang, Xi Jin e Chuanjun Wang. "An Accelerating Solution forN-Body MOND Simulation with FPGA-SoC". International Journal of Reconfigurable Computing 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/4592780.
Texto completo da fonteVázquez, Sergio, e Margarita Amor. "Texture Mapping on NURBS Surface". Proceedings 2, n.º 18 (17 de setembro de 2018): 1197. http://dx.doi.org/10.3390/proceedings2181197.
Texto completo da fonteKunimoto, Michelle, Evan Tey, Willie Fong, Katharine Hesse, Glen Petitpas e Avi Shporer. "QLP Data Release Notes 003: GPU-based Transit Search". Research Notes of the AAS 7, n.º 2 (16 de fevereiro de 2023): 28. http://dx.doi.org/10.3847/2515-5172/acbc13.
Texto completo da fonteXiong, Ruicheng, Yang Lu, Cong Chen, Jiaming Zhu, Yajun Zeng e Ligang Liu. "ETER: Elastic Tessellation for Real-Time Pixel-Accurate Rendering of Large-Scale NURBS Models". ACM Transactions on Graphics 42, n.º 4 (26 de julho de 2023): 1–13. http://dx.doi.org/10.1145/3592419.
Texto completo da fonteLi, Zhifang, Beicheng Peng e Chuliang Weng. "XeFlow: Streamlining Inter-Processor Pipeline Execution for the Discrete CPU-GPU Platform". IEEE Transactions on Computers 69, n.º 6 (1 de junho de 2020): 819–31. http://dx.doi.org/10.1109/tc.2020.2968302.
Texto completo da fonteBabbitt, Gregory A., Jamie S. Mortensen, Erin E. Coppola, Lily E. Adams e Justin K. Liao. "DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics". Biophysical Journal 114, n.º 5 (março de 2018): 1009–17. http://dx.doi.org/10.1016/j.bpj.2018.01.020.
Texto completo da fonteGuo, Xiangyu, Qi Chu, Shin Kee Chung, Zhihui Du, Linqing Wen e Yanqi Gu. "GPU-acceleration on a low-latency binary-coalescence gravitational wave search pipeline". Computer Physics Communications 231 (outubro de 2018): 62–71. http://dx.doi.org/10.1016/j.cpc.2018.05.002.
Texto completo da fonteNicolas-Barreales, Gonzalo, Aaron Sujar e Alberto Sanchez. "A Web-Based Tool for Simulating Molecular Dynamics in Cloud Environments". Electronics 10, n.º 2 (15 de janeiro de 2021): 185. http://dx.doi.org/10.3390/electronics10020185.
Texto completo da fonteVa, Hongly, Min-Hyung Choi e Min Hong. "Real-Time Cloth Simulation Using Compute Shader in Unity3D for AR/VR Contents". Applied Sciences 11, n.º 17 (6 de setembro de 2021): 8255. http://dx.doi.org/10.3390/app11178255.
Texto completo da fonteFang, Juan, Zelin Wei e Huijing Yang. "Locality-Based Cache Management and Warp Scheduling for Reducing Cache Contention in GPU". Micromachines 12, n.º 10 (17 de outubro de 2021): 1262. http://dx.doi.org/10.3390/mi12101262.
Texto completo da fonteLee, Seokwon, Inmo Ban, Myeongjin Lee, Yunho Jung e Wookyung Lee. "Architecture Exploration of a Backprojection Algorithm for Real-Time Video SAR". Sensors 21, n.º 24 (10 de dezembro de 2021): 8258. http://dx.doi.org/10.3390/s21248258.
Texto completo da fonteMo, Tiexiang, e Guodong Li. "Parallel Accelerated Fifth-Order WENO Scheme-Based Pipeline Transient Flow Solution Model". Applied Sciences 12, n.º 14 (21 de julho de 2022): 7350. http://dx.doi.org/10.3390/app12147350.
Texto completo da fonteKozlenko, Mykola, Olena Zamikhovska e Leonid Zamikhovskyi. "Software implemented fault diagnosis of natural gas pumping unit based on feedforward neural network". Eastern-European Journal of Enterprise Technologies 2, n.º 2 (110) (30 de abril de 2021): 99–109. http://dx.doi.org/10.15587/1729-4061.2021.229859.
Texto completo da fonteStřelák, David, Carlos Óscar S. Sorzano, José María Carazo e Jiří Filipovič. "A GPU acceleration of 3-D Fourier reconstruction in cryo-EM". International Journal of High Performance Computing Applications 33, n.º 5 (11 de março de 2019): 948–59. http://dx.doi.org/10.1177/1094342019832958.
Texto completo da fonteKonnurmath, Guruprasad, e Satyadhyan Chickerur. "GPU Shader Analysis and Power Optimization Model". Engineering, Technology & Applied Science Research 14, n.º 1 (8 de fevereiro de 2024): 12925–30. http://dx.doi.org/10.48084/etasr.6695.
Texto completo da fonteKhalid, Muhammad Farhan, Kanzal Iman, Amna Ghafoor, Mujtaba Saboor, Ahsan Ali, Urwa Muaz, Abdul Rehman Basharat et al. "PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics". Nucleic Acids Research 49, W1 (17 de maio de 2021): W510—W515. http://dx.doi.org/10.1093/nar/gkab368.
Texto completo da fonteCali, Damla Senol, Thomas Anantharaman, Martin Muggli, Samer Al-Saffar, Charles Schoonover e Neil Miller. "Abstract 2337: Accelerated optical genome mapping analysis with Stratys Compute and Guided Assembly". Cancer Research 84, n.º 6_Supplement (22 de março de 2024): 2337. http://dx.doi.org/10.1158/1538-7445.am2024-2337.
Texto completo da fonteLazar, Alina, Xiangyang Ju, Daniel Murnane, Paolo Calafiura, Steven Farrell, Yaoyuan Xu, Maria Spiropulu et al. "Accelerating the Inference of the Exa.TrkX Pipeline". Journal of Physics: Conference Series 2438, n.º 1 (1 de fevereiro de 2023): 012008. http://dx.doi.org/10.1088/1742-6596/2438/1/012008.
Texto completo da fonteZhao, Hanyu, Zhi Yang, Yu Cheng, Chao Tian, Shiru Ren, Wencong Xiao, Man Yuan et al. "GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning". Proceedings of the ACM on Management of Data 1, n.º 2 (13 de junho de 2023): 1–25. http://dx.doi.org/10.1145/3589773.
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