Artículos de revistas sobre el tema "CUDA FRAMEWORK"
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Trujillo, Leonardo, Jose Manuel Muñoz Contreras, Daniel E. Hernandez, Mauro Castelli y Juan J. Tapia. "GSGP-CUDA — A CUDA framework for Geometric Semantic Genetic Programming". SoftwareX 18 (junio de 2022): 101085. http://dx.doi.org/10.1016/j.softx.2022.101085.
Texto completoRosenberg, Duane, Pablo D. Mininni, Raghu Reddy y Annick Pouquet. "GPU Parallelization of a Hybrid Pseudospectral Geophysical Turbulence Framework Using CUDA". Atmosphere 11, n.º 2 (8 de febrero de 2020): 178. http://dx.doi.org/10.3390/atmos11020178.
Texto completoWang, Fan, Xiao Jiang y Xiao Peng Hu. "A TBB-CUDA Implementation for Background Removal in a Video-Based Fire Detection System". Mathematical Problems in Engineering 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/692921.
Texto completoBi, Yujiang, Yi Xiao, WeiYi Guo, Ming Gong, Peng Sun, Shun Xu y Yi-bo Yang. "Lattice QCD GPU Inverters on ROCm Platform". EPJ Web of Conferences 245 (2020): 09008. http://dx.doi.org/10.1051/epjconf/202024509008.
Texto completoPeng, Bo, Junliang Lai, Yang Wang, Ling Wang y Dong C. Liu. "CUDA-Based Parallel Computation Framework for Phase Root Seeking Algorithm". Journal of Medical Imaging and Health Informatics 4, n.º 6 (1 de diciembre de 2014): 922–31. http://dx.doi.org/10.1166/jmihi.2014.1343.
Texto completoAhmed, Rafid, Md Sazzadul Islam y Jia Uddin. "Optimizing Apple Lossless Audio Codec Algorithm using NVIDIA CUDA Architecture". International Journal of Electrical and Computer Engineering (IJECE) 8, n.º 1 (1 de febrero de 2018): 70. http://dx.doi.org/10.11591/ijece.v8i1.pp70-75.
Texto completoMichailidis, P. D. y K. G. Margaritis. "Accelerating kernel density estimation on the GPU using the CUDA framework". Applied Mathematical Sciences 7 (2013): 1447–76. http://dx.doi.org/10.12988/ams.2013.13133.
Texto completoBruel, Pedro, Marcos Amarís y Alfredo Goldman. "Autotuning CUDA compiler parameters for heterogeneous applications using the OpenTuner framework". Concurrency and Computation: Practice and Experience 29, n.º 22 (6 de marzo de 2017): e3973. http://dx.doi.org/10.1002/cpe.3973.
Texto completoHadji-Kyriacou, Avelina y Ognjen Arandjelović. "Raymarching Distance Fields with CUDA". Electronics 10, n.º 22 (9 de noviembre de 2021): 2730. http://dx.doi.org/10.3390/electronics10222730.
Texto completoLee, Seongjae y Taehyoun Kim. "Parallel Dislocation Model Implementation for Earthquake Source Parameter Estimation on Multi-Threaded GPU". Applied Sciences 11, n.º 20 (11 de octubre de 2021): 9434. http://dx.doi.org/10.3390/app11209434.
Texto completoJaveed, Danish, Tianhan Gao, Muhammad Taimoor Khan y Ijaz Ahmad. "A Hybrid Deep Learning-Driven SDN Enabled Mechanism for Secure Communication in Internet of Things (IoT)". Sensors 21, n.º 14 (18 de julio de 2021): 4884. http://dx.doi.org/10.3390/s21144884.
Texto completoCabodi, Gianpiero, Paolo Camurati, Alessandro Garbo, Michele Giorelli, Stefano Quer y Francesco Savarese. "A Smart Many-Core Implementation of a Motion Planning Framework along a Reference Path for Autonomous Cars". Electronics 8, n.º 2 (2 de febrero de 2019): 177. http://dx.doi.org/10.3390/electronics8020177.
Texto completoPeña-Cantillana, Francisco, Daniel Díaz-Pernil, Hepzibah A. Christinal y Miguel A. Gutiérrez-Naranjo. "Implementation on CUDA of the Smoothing Problem with Tissue-Like P Systems". International Journal of Natural Computing Research 2, n.º 3 (julio de 2011): 25–34. http://dx.doi.org/10.4018/jncr.2011070103.
Texto completoKinsner, M., D. Capson y A. Spence. "A modular CUDA-based framework for scale-space feature detection in video streams". Journal of Physics: Conference Series 256 (1 de noviembre de 2010): 012005. http://dx.doi.org/10.1088/1742-6596/256/1/012005.
Texto completoChen, DeHao, WenGuang Chen y WeiMin Zheng. "CUDA-Zero: a framework for porting shared memory GPU applications to multi-GPUs". Science China Information Sciences 55, n.º 3 (25 de febrero de 2012): 663–76. http://dx.doi.org/10.1007/s11432-011-4497-z.
Texto completoTang, Ying, Xiaoying Shi, Tingzhe Xiao y Jing Fan. "An improved image analogy method based on adaptive CUDA-accelerated neighborhood matching framework". Visual Computer 28, n.º 6-8 (19 de abril de 2012): 743–53. http://dx.doi.org/10.1007/s00371-012-0701-4.
Texto completoSokolovskyy, Yaroslav, Denys Manokhin, Yaroslav Kaplunsky y Olha Mokrytska. "Development of software and algorithms of parallel learning of artificial neural networks using CUDA technologies". Technology audit and production reserves 5, n.º 2(61) (23 de septiembre de 2021): 21–25. http://dx.doi.org/10.15587/2706-5448.2021.239784.
Texto completoHwang, Jaemin, Jong-Wook Choi, Seongrim Choi y Byeong-Gyu Nam. "A Simulation Framework for CUDA Computing on Non-x86 Platforms based on QEMU and GPGPU-Sim". Journal of the Korea Industrial Information Systems Research 19, n.º 2 (30 de abril de 2014): 15–22. http://dx.doi.org/10.9723/jksiis.2014.19.2.015.
Texto completoPoli, G., E. Llapa, J. R. Cecatto, J. H. Saito, J. F. Peters, S. Ramanna y M. C. Nicoletti. "Solar flare detection system based on tolerance near sets in a GPU–CUDA framework". Knowledge-Based Systems 70 (noviembre de 2014): 345–60. http://dx.doi.org/10.1016/j.knosys.2014.07.012.
Texto completoTovkach, Serhii. "CUDA-інтеграція контурів керування авіаційного газотурбінного двигуна". Aerospace Technic and Technology, n.º 6 (27 de noviembre de 2023): 31–39. http://dx.doi.org/10.32620/aktt.2022.6.04.
Texto completoZhao, Yuxuan, Qi Sun, Zhuolun He, Yang Bai y Bei Yu. "AutoGraph: Optimizing DNN Computation Graph for Parallel GPU Kernel Execution". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 9 (26 de junio de 2023): 11354–62. http://dx.doi.org/10.1609/aaai.v37i9.26343.
Texto completoShaikh, Alim, Isha Goski, Parth Bhosale, Somesh Bhosale y Prof S. S. Pawar. "HORUS - Heuristic Object Recognition Unified System Using YOLO and CUDA". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de mayo de 2023): 974–76. http://dx.doi.org/10.22214/ijraset.2023.51688.
Texto completoHanousek, Vít y Tomáš Oberhuber. "Efficient Transfer of C++ Objects on Intel Xeon Phi KNC in Offload Mode". Computer Methods in Material Science 17, n.º 2 (2017): 94–100. http://dx.doi.org/10.7494/cmms.2017.2.0594.
Texto completoTorti, Emanuele, Alessandro Fontanella, Antonio Plaza, Javier Plaza y Francesco Leporati. "Hyperspectral Image Classification Using Parallel Autoencoding Diabolo Networks on Multi-Core and Many-Core Architectures". Electronics 7, n.º 12 (8 de diciembre de 2018): 411. http://dx.doi.org/10.3390/electronics7120411.
Texto completoBocci, Andrea, David Dagenhart, Vincenzo Innocente, Christopher Jones, Matti Kortelainen, Felice Pantaleo y Marco Rovere. "Bringing heterogeneity to the CMS software framework". EPJ Web of Conferences 245 (2020): 05009. http://dx.doi.org/10.1051/epjconf/202024505009.
Texto completoKUMAR, PIYUSH y ANUPAM AGRAWAL. "GPU-ACCELERATED INTERACTIVE VISUALIZATION OF 3D VOLUMETRIC DATA USING CUDA". International Journal of Image and Graphics 13, n.º 02 (abril de 2013): 1340003. http://dx.doi.org/10.1142/s0219467813400032.
Texto completoGuzzi, Francesco, George Kourousias, Fulvio Billè, Roberto Pugliese, Alessandra Gianoncelli y Sergio Carrato. "A modular software framework for the design and implementation of ptychography algorithms". PeerJ Computer Science 8 (25 de julio de 2022): e1036. http://dx.doi.org/10.7717/peerj-cs.1036.
Texto completoSheng, Yanyan, William S. Welling y Michelle M. Zhu. "A GPU-Based Gibbs Sampler for a Unidimensional IRT Model". International Scholarly Research Notices 2014 (30 de octubre de 2014): 1–11. http://dx.doi.org/10.1155/2014/368149.
Texto completoMunawar, Asim, Mohamed Wahib, Masaharu Munetomo y Kiyoshi Akama. "Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework". Genetic Programming and Evolvable Machines 10, n.º 4 (20 de octubre de 2009): 391–415. http://dx.doi.org/10.1007/s10710-009-9091-4.
Texto completoBlazewicz, Marek, Ian Hinder, David M. Koppelman, Steven R. Brandt, Milosz Ciznicki, Michal Kierzynka, Frank Löffler, Erik Schnetter y Jian Tao. "From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation". Scientific Programming 21, n.º 1-2 (2013): 1–16. http://dx.doi.org/10.1155/2013/167841.
Texto completoSamaké, A., M. Alassane, A. Mahamane y O. Diallo. "A SCALABLE HYBRID CPU-GPU COMPUTATIONAL FRAMEWORK FOR A FINITE ELEMENT-BASED AIR QUALITY MODEL". Advances in Mathematics: Scientific Journal 12, n.º 1 (2 de enero de 2023): 45–61. http://dx.doi.org/10.37418/amsj.12.1.3.
Texto completoT. A. Valencia-Pérez, J. M. Hernández-López, E. Moreno-Barbosa y B. de Celis-Alonso. "Study of CT Images Processing with the Implementation of MLEM Algorithm using CUDA on NVIDIA’S GPU Framework". Journal of Nuclear Physics, Material Sciences, Radiation and Applications 7, n.º 2 (28 de febrero de 2020): 165–71. http://dx.doi.org/10.15415/jnp.2020.72021.
Texto completoMontella, Raffaele, Giulio Giunta, Giuliano Laccetti, Marco Lapegna, Carlo Palmieri, Carmine Ferraro, Valentina Pelliccia, Cheol-Ho Hong, Ivor Spence y Dimitrios S. Nikolopoulos. "On the Virtualization of CUDA Based GPU Remoting on ARM and X86 Machines in the GVirtuS Framework". International Journal of Parallel Programming 45, n.º 5 (13 de octubre de 2016): 1142–63. http://dx.doi.org/10.1007/s10766-016-0462-1.
Texto completoQiu, Liu Chao. "OpenCL-Based GPU Acceleration of ISPH Simulation for Incompressible Flows". Applied Mechanics and Materials 444-445 (octubre de 2013): 380–84. http://dx.doi.org/10.4028/www.scientific.net/amm.444-445.380.
Texto completoBlazewicz, Marek, Steven R. Brandt, Michal Kierzynka, Krzysztof Kurowski, Bogdan Ludwiczak, Jian Tao y Jan Weglarz. "CaKernel – A Parallel Application Programming Framework for Heterogenous Computing Architectures". Scientific Programming 19, n.º 4 (2011): 185–97. http://dx.doi.org/10.1155/2011/457030.
Texto completoMadrigal Díaz, Jorge Francisco y Jean-Bernard Hayet. "Color and motion-based particle filter target tracking in a network of overlapping cameras with multi-threading and GPGPU". Acta Universitaria 23, n.º 1 (28 de febrero de 2013): 9–16. http://dx.doi.org/10.15174/au.2013.355.
Texto completoSu, Huayou, Mei Wen, Nan Wu, Ju Ren y Chunyuan Zhang. "Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation". Scientific World Journal 2014 (2014): 1–19. http://dx.doi.org/10.1155/2014/716020.
Texto completoBlyth, Simon. "Integration of JUNO simulation framework with Opticks: GPU accelerated optical propagation via NVIDIA® OptiX™". EPJ Web of Conferences 251 (2021): 03009. http://dx.doi.org/10.1051/epjconf/202125103009.
Texto completoGomes, Raphael De Souza Rosa, Victor Hugo De Morais Danelichen, Marcelo Sacardi Biudes, Maisa Caldas Souza Velasque, Josiel Maimome De Figueiredo y José De Souza Nogueira. "The Surface Energy Balance Algorithm for Land (SEBAL) framework in Graphics Processing Units (GPU) using Cuda and OpenCL". Revista Brasileira de Geografia Física 14, n.º 3 (20 de julio de 2021): 1805. http://dx.doi.org/10.26848/rbgf.v14.3.p1805-1814.
Texto completoCuomo, S., A. Galletti, G. Giunta y L. Marcellino. "Toward a Multi-level Parallel Framework on GPU Cluster with PetSC-CUDA for PDE-based Optical Flow Computation". Procedia Computer Science 51 (2015): 170–79. http://dx.doi.org/10.1016/j.procs.2015.05.220.
Texto completoHolmvall, P., N. Wall Wennerdal, M. Håkansson, P. Stadler, O. Shevtsov, T. Löfwander y M. Fogelström. "SuperConga: An open-source framework for mesoscopic superconductivity". Applied Physics Reviews 10, n.º 1 (marzo de 2023): 011317. http://dx.doi.org/10.1063/5.0100324.
Texto completoWang, Zhenwu, Benting Wan y Mengjie Han. "A Three-Dimensional Visualization Framework for Underground Geohazard Recognition on Urban Road-Facing GPR Data". ISPRS International Journal of Geo-Information 9, n.º 11 (11 de noviembre de 2020): 668. http://dx.doi.org/10.3390/ijgi9110668.
Texto completoDressler, Sven y Daniel N. Wilke. "PyBONDEM-GPU: A discrete element bonded particle Python research framework – Development and examples". EPJ Web of Conferences 249 (2021): 14009. http://dx.doi.org/10.1051/epjconf/202124914009.
Texto completoAdeshina, Adekunle. "Automated Medical Visualization Application of Supervised Learning to Clinical Diagnosis, Disease and Therapy Management.docx". SLU Journal of Science and Technology 5, n.º 1&2 (29 de diciembre de 2022): 104–14. http://dx.doi.org/10.56471/slujst.v5i.311.
Texto completoLuo, Xun, Wei Zhao, Bao Shun Liu y Yan Ming Zhang. "A Feasible Parallel Monte Carlo Algorithm to Simulate Templated Grain Growth". Advanced Materials Research 332-334 (septiembre de 2011): 1868–71. http://dx.doi.org/10.4028/www.scientific.net/amr.332-334.1868.
Texto completoFedorov, Eugene, Peter Nikolyuk, Olga Nechporenko y Esta Chioma. "Intellectualization of a method for solving a logistics problem to optimize costs within the framework of Lean Production technology". Electronic Scientific Journal Intellectualization of Logistics and Supply Chain Management #1 2020 1, n.º 3 (2020): 7–17. http://dx.doi.org/10.46783/smart-scm/2020-3-1.
Texto completoYuan, Jianying, Dequan Guo, Gexiang Zhang, Prithwineel Paul, Ming Zhu y Qiang Yang. "A Resolution-Free Parallel Algorithm for Image Edge Detection within the Framework of Enzymatic Numerical P Systems". Molecules 24, n.º 7 (29 de marzo de 2019): 1235. http://dx.doi.org/10.3390/molecules24071235.
Texto completoHo, Nhut-Minh, Himeshi De silva y Weng-Fai Wong. "GRAM". ACM Transactions on Architecture and Code Optimization 18, n.º 2 (marzo de 2021): 1–24. http://dx.doi.org/10.1145/3441830.
Texto completoTang, Chin-I., Xianyue Deng y Yuzuru Takashima. "Real-Time CGH Generation by CUDA-OpenGL Interoperability for Adaptive Beam Steering with a MEMS Phase SLM". Micromachines 13, n.º 9 (15 de septiembre de 2022): 1527. http://dx.doi.org/10.3390/mi13091527.
Texto completoPeng, Feng, Xiaoli Hao y Fuxin Chai. "A GPU-Accelerated Two-Dimensional Hydrodynamic Model for Unstructured Grids". Water 15, n.º 7 (25 de marzo de 2023): 1300. http://dx.doi.org/10.3390/w15071300.
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