Literatura científica selecionada sobre o tema "Algorithmes GPU"
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Artigos de revistas sobre o assunto "Algorithmes GPU"
Boulay, Thomas, Nicolas Gac, Ali Mohammad-Djafari e Julien Lagoutte. "Algorithmes de reconnaissance NCTR et parallélisation sur GPU". Traitement du signal 30, n.º 6 (28 de abril de 2013): 309–42. http://dx.doi.org/10.3166/ts.30.309-342.
Texto completo da fonteRios-Willars, Ernesto, Jennifer Velez-Segura e María Magdalena Delabra-Salinas. "Enhancing Multiple Sequence Alignment with Genetic Algorithms: A Bioinformatics Approach in Biomedical Engineering". Revista Mexicana de Ingeniería Biomédica 45, n.º 2 (1 de maio de 2024): 62–77. http://dx.doi.org/10.17488/rmib.45.2.4.
Texto completo da fonteSOMAN, JYOTHISH, KISHORE KOTHAPALLI e P. J. NARAYANAN. "SOME GPU ALGORITHMS FOR GRAPH CONNECTED COMPONENTS AND SPANNING TREE". Parallel Processing Letters 20, n.º 04 (dezembro de 2010): 325–39. http://dx.doi.org/10.1142/s0129626410000272.
Texto completo da fonteSchnös, Florian, Dirk Hartmann, Birgit Obst e Glenn Glashagen. "GPU accelerated voxel-based machining simulation". International Journal of Advanced Manufacturing Technology 115, n.º 1-2 (8 de maio de 2021): 275–89. http://dx.doi.org/10.1007/s00170-021-07001-w.
Texto completo da fonteZatolokin, Y. A., E. I. Vatutin e V. S. Titov. "ALGORITHMIC OPTIMIZATION OF SOFTWARE IMPLEMENTATION OF ALGORITHMS FOR MULTIPLYING DENSE REAL MATRICES ON GRAPHICS PROCESSORS WITH OPENGL TECHNOLOGY SUPPORT". Proceedings of the Southwest State University 21, n.º 5 (28 de outubro de 2017): 6–15. http://dx.doi.org/10.21869/2223-1560-2017-21-5-06-15.
Texto completo da fonteMERRILL, DUANE, e ANDREW GRIMSHAW. "HIGH PERFORMANCE AND SCALABLE RADIX SORTING: A CASE STUDY OF IMPLEMENTING DYNAMIC PARALLELISM FOR GPU COMPUTING". Parallel Processing Letters 21, n.º 02 (junho de 2011): 245–72. http://dx.doi.org/10.1142/s0129626411000187.
Texto completo da fonteGremse, Felix, Andreas Höfter, Lukas Razik, Fabian Kiessling e Uwe Naumann. "GPU-accelerated adjoint algorithmic differentiation". Computer Physics Communications 200 (março de 2016): 300–311. http://dx.doi.org/10.1016/j.cpc.2015.10.027.
Texto completo da fonteRapaport, D. C. "GPU molecular dynamics: Algorithms and performance". Journal of Physics: Conference Series 2241, n.º 1 (1 de março de 2022): 012007. http://dx.doi.org/10.1088/1742-6596/2241/1/012007.
Texto completo da fonteMikhayluk, M. V., e A. M. Trushin. "Spheres Collision Detection Algorithms on GPU". PROGRAMMNAYA INGENERIA 8, n.º 8 (15 de agosto de 2017): 354–58. http://dx.doi.org/10.17587/prin.8.354-358.
Texto completo da fonteMatei, Adrian, Cristian Lupașcu e Ion Bica. "On GPU Implementations of Encryption Algorithms". Journal of Military Technology 2, n.º 2 (18 de dezembro de 2019): 29–34. http://dx.doi.org/10.32754/jmt.2019.2.04.
Texto completo da fonteTeses / dissertações sobre o assunto "Algorithmes GPU"
Ballage, Marion. "Algorithmes de résolution rapide de problèmes mécaniques sur GPU". Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30122/document.
Texto completo da fonteGenerating a conformal mesh on complex geometries leads to important model size of structural finite element simulations. The meshing time is directly linked to the geometry complexity and can contribute significantly to the total turnaround time. Graphics processing units (GPUs) are highly parallel programmable processors, delivering real performance gains on computationally complex, large problems. GPUs are used to implement a new finite element method on a Cartesian mesh. A Cartesian mesh is well adapted to the parallelism needed by GPUs and reduces the meshing time to almost zero. The novel method relies on the finite element method and the extended finite element formulation. The extended finite element method was introduced in the field of fracture mechanics. It consists in enriching the basis functions to take care of the geometry and the interface. This method doesn't need a conformal mesh to represent cracks and avoids refining during their propagation. Our method is based on the extended finite element method, with a geometry implicitly defined, wich allows for a good approximation of the geometry and boundary conditions without a conformal mesh.To represent the model on a Cartesian grid, we use a level set representing a density. This density is greater than 0.5 inside the domain and less than 0.5 outside. It takes 0.5 on the boundary. A new integration technique is proposed, adapted to the geometrical representation. For the element cut by the levet set, only the part full of material has to be integrated. The Gauss quadrature is no longer adapted. We introduce a quadrature method with integration points on a cartesian dense grid.In order to reduce the computational effort, a learning approach is then considered to form the elementary stiffness matrices as function of density values on the vertices of the elements. This learning method reduces the stiffness matrices time computation. Results obtained after analysis by finite element method or the novel finite element method can have important storage size, dependant of the model complexity and the resolution scheme exactitude. Due to the limited direct memory of graphics processing units, the data results are compressed. We compress the model and the element finite results with a wavelet transform. The compression will help for storage issue and also for data visualization
Luong, Thé Van. "Métaheuristiques parallèles sur GPU". Thesis, Lille 1, 2011. http://www.theses.fr/2011LIL10058/document.
Texto completo da fonteReal-world optimization problems are often complex and NP-hard. Their modeling is continuously evolving in terms of constraints and objectives, and their resolution is CPU time-consuming. Although near-optimal algorithms such as metaheuristics (generic heuristics) make it possible to reduce the temporal complexity of their resolution, they fail to tackle large problems satisfactorily. Over the last decades, parallel computing has been revealed as an unavoidable way to deal with large problem instances of difficult optimization problems. The design and implementation of parallel metaheuristics are strongly influenced by the computing platform. Nowadays, GPU computing has recently been revealed effective to deal with time-intensive problems. This new emerging technology is believed to be extremely useful to speed up many complex algorithms. One of the major issues for metaheuristics is to rethink existing parallel models and programming paradigms to allow their deployment on GPU accelerators. Generally speaking, the major issues we have to deal with are: the distribution of data processing between CPU and GPU, the thread synchronization, the optimization of data transfer between the different memories, the memory capacity constraints, etc. The contribution of this thesis is to deal with such issues for the redesign of parallel models of metaheuristics to allow solving of large scale optimization problems on GPU architectures. Our objective is to rethink the existing parallel models and to enable their deployment on GPUs. Thereby, we propose in this document a new generic guideline for building efficient parallel metaheuristics on GPU. Our challenge is to come out with the GPU-based design of the whole hierarchy of parallel models.In this purpose, very efficient approaches are proposed for CPU-GPU data transfer optimization, thread control, mapping of solutions to GPU threadsor memory management. These approaches have been exhaustively experimented using five optimization problems and four GPU configurations. Compared to a CPU-based execution, experiments report up to 80-fold acceleration for large combinatorial problems and up to 2000-fold speed-up for a continuous problem. The different works related to this thesis have been accepted in a dozen of publications, including the IEEE Transactions on Computers journal
Viard, Thomas. "Algorithmes de visualisation des incertitudes en géomodélisation sur GPU". Thesis, Vandoeuvre-les-Nancy, INPL, 2010. http://www.theses.fr/2010INPL042N/document.
Texto completo da fonteMost of the subsurface is inaccessible to direct observation in geosciences. Consequently, only local or imprecise data are available when building or updating a geological model; uncertainties are therefore central to geomodeling. The inverse problem theory and the stochastic simulation methods provide a framework for the generation of large sets of likely representations of the subsurface, also termed realizations. In practice, however, the size of the set of realizations severely impacts further interpretation or processing of the geological model.This thesis aims at providing visualization algorithms to expert geologists that allow them to explore, analyze and communicate on spatial uncertainties associated to large sets of realizations. Our contributions are: (1) We propose a set of techniques dedicated to petrophysical uncertainty visualization, based on a GPU programming approach that maintains their interoperability; (2) We propose two techniques dedicated to structural uncertainty visualization that can handle both geometrical and topological uncertainties (e.g., the existence of the surface or its relationships with other surfaces); (3) We assess the quality of our uncertainty visualization algorithms through two user studies, which respectively focus on the perception of static and animated methods. These studies bring new elements on how uncertainty should be represented
Lefèbvre, Matthieu. "Algorithmes sur GPU pour la simulation numérique en mécanique des fluides". Paris 13, 2012. http://scbd-sto.univ-paris13.fr/intranet/edgalilee_th_2012_lefebvre.pdf.
Texto completo da fonteNumerical simulations in fluid mechanics require tremendous computational power ; GPU computing is one of the newest approaches to accelerate such simulations. On one hand, this thesis studies the case of fluid mechanics algorithms on structured meshes. The mesh structuration naturally brings well suited memory arrangements and allows to reach guidelines when using GPUs for numerical simulations. On the other hand, we examine the case of fluid mechanics on unstructured meshes with the help of three different algorithmic strategies. The first of these technique is a reorganisation to produce consecutive data accesses, but at the cost of expensive data copies, both in time and in memory. The second technique, a cell partitioning approach, is developed and allows to extensively use modern GPUs’ cache memories. The third technique consists on a generic refinement. The initial mesh is made of coarse elements refined in the exact same way in order to produce consecutive memory accesses. This approach brings significant performance improvements for fluid mechanics simulations on unstructured meshes
Marin, Manuel. "GPU-enhanced power flow analysis". Thesis, Perpignan, 2015. http://www.theses.fr/2015PERP0041.
Texto completo da fonteThis thesis addresses the utilization of Graphics Processing Units (GPUs) for improving the Power Flow (PF) analysis of modern power systems. Currently, GPUs are challenged by applications exhibiting an irregular computational pattern, as is the case of most known methods for PF analysis. At the same time, the PF analysis needs to be improved in order to cope with new requirements of efficiency and accuracy coming from the Smart Grid concept. The relevance of GPU-enhanced PF analysis is twofold. On one hand, it expands the application domain of GPU to a new class of problems. On the other hand, it consistently increases the computational capacity available for power system operation and design. The present work attempts to achieve that in two complementary ways: (i) by developing novel GPU programming strategies for available PF algorithms, and (ii) by proposing novel PF analysis methods that can exploit the numerous features present in GPU architectures. Specific contributions on GPU computing include: (i) a comparison of two programming paradigms, namely regularity and load-balancing, for implementing the so-called treefix operations; (ii) a study of the impact of the representation format over performance and accuracy, for fuzzy interval algebraic operations; and (iii) the utilization of architecture-specific design, as a novel strategy to improve performance scalability of applications. Contributions on PF analysis include: (i) the design and evaluation of a novel method for the uncertainty assessment, based on the fuzzy interval approach; and (ii) the development of an intrinsically parallel method for PF analysis, which is not affected by the Amdahl's law
Van, Luong Thé. "Métaheuristiques parallèles sur GPU". Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2011. http://tel.archives-ouvertes.fr/tel-00638820.
Texto completo da fonteBuatois, Luc. "Algorithmes sur GPU de visualisation et de calcul pour des maillages non-structurés". Phd thesis, Institut National Polytechnique de Lorraine - INPL, 2008. http://tel.archives-ouvertes.fr/tel-00331935.
Texto completo da fonteChakroun, Imen. "Algorithmes Branch and Bound parallèles hétérogènes pour environnements multi-coeurs et multi-GPU". Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2013. http://tel.archives-ouvertes.fr/tel-00841965.
Texto completo da fonteMansouri, Abdelkhalek. "Generic heuristics on GPU to superpixel segmentation and application to optical flow estimation". Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCA012.
Texto completo da fonteFinding clusters in point clouds and matching graphs to graphs are recurrent tasks in computer science domain, data analysis, image processing, that are most often modeled as NP-hard optimization problems. With the development and accessibility of cheap multiprocessors, acceleration of the heuristic procedures for these tasks becomes possible and necessary. We propose parallel implantation on GPU (graphics processing unit) system for some generic algorithms applied here to image superpixel segmentation and image optical flow problem. The aim is to provide generic algorithms based on standard decentralized data structures to be easy to improve and customized on many optimization problems and parallel platforms.The proposed parallel algorithm implementations include classical k-means algorithm and application of minimum spanning forest computation for super-pixel segmentation. They include also a parallel local search procedure, and a population-based memetic algorithm applied to optical flow estimation based on superpixel matching. While data operations fully exploit GPU, the memetic algorithm operates like a coalition of processes executed in parallel on the multi-core CPU and requesting GPU resources. Images are point clouds in 3D Euclidean space (space-gray value domain), and are also graphs to which are assigned processor grids. GPU kernels execute parallel transformations under CPU control whose limited role only consists in stopping criteria evaluation or sequencing transformations.The presented contribution contains two main parts. Firstly, we present tools for superpixel segmentation. A parallel implementation of the k-means algorithm is presented with application to 3D data. It is based on a cellular grid subdivision of 3D space that allows closest point findings in constant optimal time for bounded distributions. We present an application of the parallel Boruvka minimum spanning tree algorithm to compute watershed minimum spanning forest. Secondly, based on the generated superpixels and segmentation, we derive parallel optimization procedures for optical flow estimation with edge aware filtering. The method includes construction and improvement heuristics, as winner-take-all and parallel local search, and their embedding into a population-based metaheuristic framework. The algorithms are presented and evaluated in comparison to state-of-the-art algorithms
Legrand, Hélène. "Algorithmes parallèles pour le traitement rapide de géométries 3D". Electronic Thesis or Diss., Paris, ENST, 2017. http://www.theses.fr/2017ENST0053.
Texto completo da fonteOver the last twenty years, the main signal processing concepts have been adapted for digital geometry, in particular for 3D polygonal meshes. However, the processing time required for large models is significant. This computational load becomes an obstacle in the current context, where the massive amounts of data that are generated every second may need to be processed with several operators. The ability to run geometry processing operators with strong time constraints is a critical challenge in dynamic 3D systems. In this context, we seek to speed up some of the current algorithms by several orders of magnitude, and to reformulate or approximate them in order to reduce their complexity or make them parallel. In this thesis, we are building on a compact and effective object to analyze 3D surfaces at different scales : error quadrics. In particular, we propose new high performance algorithms that maintain error quadrics on the surface to represent the geometry. One of the main challenges lies in the effective generation of the right structures for parallel processing, in order to take advantage of the GPU
Livros sobre o assunto "Algorithmes GPU"
Xu, Guochang. GPS: Theory, algorithms, and applications. Berlin: Springer, 2003.
Encontre o texto completo da fonteShu ju jie gou: Yong mian dui xiang fang fa yu C++ yu yan miao shu. 2a ed. Bei jing: Qing hua da xue chu ban she, 2007.
Encontre o texto completo da fonteBaúto, João, Rui Neves e Nuno Horta. Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73329-6.
Texto completo da fontePilley, H. Robert. GPS-based airport operations: Requirements, analysis & algorithms : engineering source book. Deering, NH: DSDC, 1994.
Encontre o texto completo da fonteGulati, Kanupriya. Hardware acceleration of EDA algorithms: Custom ICs, FPGAs and GPUs. New York: Springer, 2010.
Encontre o texto completo da fonteChen, Dewang, e Ruijun Cheng. Intelligent Processing Algorithms and Applications for GPS Positioning Data of Qinghai-Tibet Railway. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-58970-0.
Texto completo da fonteTu jie zi liao jie gou: Shi yong Python. Xinbei Shi: Bo shuo wen hua gu fen you xian gong si, 2017.
Encontre o texto completo da fonteShu ju jie gou yu suan fa fen xi: C yu yan miao shu. Beijing Shi: Ji xie gong ye chu ban she, 2004.
Encontre o texto completo da fonteJet Propulsion Laboratory (U.S.), ed. A fully redundant double difference algorithm for obtaining minimum variance estimates from GPS observations. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1986.
Encontre o texto completo da fonteMelbourne, William G. A fully redundant double difference algorithm for obtaining minimum variance estimates from GPS observations. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1986.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Algorithmes GPU"
Ou, Zhixin, Juan Chen, Yuyang Sun, Tao Xu, Guodong Jiang, Zhengyuan Tan e Xinxin Qi. "AOA: Adaptive Overclocking Algorithm on CPU-GPU Heterogeneous Platforms". In Algorithms and Architectures for Parallel Processing, 253–72. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-22677-9_14.
Texto completo da fonteWijs, Anton, e Muhammad Osama. "A GPU Tree Database for Many-Core Explicit State Space Exploration". In Tools and Algorithms for the Construction and Analysis of Systems, 684–703. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30823-9_35.
Texto completo da fonteReinders, James, Ben Ashbaugh, James Brodman, Michael Kinsner, John Pennycook e Xinmin Tian. "Programming for GPUs". In Data Parallel C++, 353–85. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5574-2_15.
Texto completo da fonteOsama, Muhammad, Anton Wijs e Armin Biere. "SAT Solving with GPU Accelerated Inprocessing". In Tools and Algorithms for the Construction and Analysis of Systems, 133–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72016-2_8.
Texto completo da fonteOsama, Muhammad, e Anton Wijs. "Hitching a Ride to a Lasso: Massively Parallel On-The-Fly LTL Model Checking". In Tools and Algorithms for the Construction and Analysis of Systems, 23–43. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57249-4_2.
Texto completo da fonteYang, Kaifeng, e Michael Affenzeller. "Surrogate-assisted Multi-objective Optimization via Genetic Programming Based Symbolic Regression". In Lecture Notes in Computer Science, 176–90. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27250-9_13.
Texto completo da fonteVasconcelos, Cristina N., Asla Sá, Paulo Cezar Carvalho e Marcelo Gattass. "Lloyd’s Algorithm on GPU". In Advances in Visual Computing, 953–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89639-5_91.
Texto completo da fonteXu, Guochang, e Yan Xu. "Applications of GPS Theory and Algorithms". In GPS, 313–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-50367-6_10.
Texto completo da fonteMartens, Jan, Jan Friso Groote, Lars van den Haak, Pieter Hijma e Anton Wijs. "A Linear Parallel Algorithm to Compute Bisimulation and Relational Coarsest Partitions". In Formal Aspects of Component Software, 115–33. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-90636-8_7.
Texto completo da fonteŞakar, Ömer, Mohsen Safari, Marieke Huisman e Anton Wijs. "Alpinist: An Annotation-Aware GPU Program Optimizer". In Tools and Algorithms for the Construction and Analysis of Systems, 332–52. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99527-0_18.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Algorithmes GPU"
Konobrytskyi, Dmytro, Thomas Kurfess, Joshua Tarbutton e Tommy Tucker. "GPGPU Accelerated 3-Axis CNC Machining Simulation". In ASME 2013 International Manufacturing Science and Engineering Conference collocated with the 41st North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/msec2013-1096.
Texto completo da fonteTarashima, Shuhei, Satoshi Someya e Koji Okamoto. "Acceleration of Recursive Cross-Correlation PIV Using Multiple GPUs". In ASME/JSME 2011 8th Thermal Engineering Joint Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/ajtec2011-44442.
Texto completo da fonteBergmann, Ryan M., e Jasmina L. Vujić. "Monte Carlo Neutron Transport on GPUs". In 2014 22nd International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/icone22-30148.
Texto completo da fonteBulavintsev, Vadim, e Dmitry Zhdanov. "Method for Adaptation of Algorithms to GPU Architecture". In 31th International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2021. http://dx.doi.org/10.20948/graphicon-2021-3027-930-941.
Texto completo da fonteVulcan, Alexandru mihai, Radu nicolae Pietraru e Maximilian Nicolae. "VISUAL TOOL FOR LEARNING GPU PROGRAMMING". In eLSE 2019. Carol I National Defence University Publishing House, 2019. http://dx.doi.org/10.12753/2066-026x-19-057.
Texto completo da fonteMazhar, Hammad, Andrew Seidl, Rebecca Shotwell, Marco B. Quadrelli, Dan Negrut e Abhinandan Jain. "Granular Dynamics Simulation on Multiple GPUs Using Domain Decomposition". In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71121.
Texto completo da fonteMorris, Christopher, Njiru Mwaura, David Schneider, FNU Tabish, Duncan Carpenter, Nathan Clark e Anjali Sandip. "Graphics Processing Units’ Accelerated Navier-Stokes Solvers for Unstructured Meshes: A Literature Review". In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-112786.
Texto completo da fonteRomanelli, G., L. Mangani, E. Casartelli, A. Gadda e M. Favale. "Implementation of Explicit Density-Based Unstructured CFD Solver for Turbomachinery Applications on Graphical Processing Units". In ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/gt2015-43396.
Texto completo da fonteVanka, S. Pratap, Aaron F. Shinn e Kirti C. Sahu. "Computational Fluid Dynamics Using Graphics Processing Units: Challenges and Opportunities". In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-65260.
Texto completo da fonteBruel, Pedro, Marcos Amarís e Alfredo Goldman. "Autotuning GPU Compiler Parameters Using OpenTuner". In XVI Simpósio em Sistemas Computacionais de Alto Desempenho. Sociedade Brasileira de Computação - SBC, 2015. http://dx.doi.org/10.5753/wscad.2015.14268.
Texto completo da fonteRelatórios de organizações sobre o assunto "Algorithmes GPU"
Mniszewski, Susan, Stan Moore, Sam Reeve, Stuart Slattery, Damien Lebrun-Grandie, Shane Fogerty e Steve Plimpton. Algorithmic and GPU enhancements for molecular dynamics in Cabana and LAMMPS. Office of Scientific and Technical Information (OSTI), março de 2022. http://dx.doi.org/10.2172/1856126.
Texto completo da fonteJimoh, Mujeeb B. Performance Testing of GPU-Based Approximate Matching Algorithm on Network Traffic. Fort Belvoir, VA: Defense Technical Information Center, março de 2015. http://dx.doi.org/10.21236/ada620807.
Texto completo da fonteKolev, T. CEED-MS36: High-order algorithmic developments and optimizations for large-scale GPU-accelerated simulations. Office of Scientific and Technical Information (OSTI), março de 2021. http://dx.doi.org/10.2172/1845639.
Texto completo da fonteLever, James, Allan Delaney, Laura Ray, E. Trautman, Lynette Barna e Amy Burzynski. Autonomous GPR surveys using the polar rover Yeti. Engineer Research and Development Center (U.S.), março de 2022. http://dx.doi.org/10.21079/11681/43600.
Texto completo da fonteSuess, Matthias, Demetrios Matsakis e Charles A. Greeenhall. Simulating Future GPS Clock Scenarios with Two Composite Clock Algorithms. Fort Belvoir, VA: Defense Technical Information Center, novembro de 2010. http://dx.doi.org/10.21236/ada547035.
Texto completo da fonteJade Morton, Yu T. Developing Signal Processing Algorithms for Weak GPS Signal Acquisition in Urban Environment. Fort Belvoir, VA: Defense Technical Information Center, setembro de 2004. http://dx.doi.org/10.21236/ada426847.
Texto completo da fonteMathew, Jijo K., Christopher M. Day, Howell Li e Darcy M. Bullock. Curating Automatic Vehicle Location Data to Compare the Performance of Outlier Filtering Methods. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317435.
Texto completo da fonteCheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li e Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Texto completo da fonteCheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li e Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Texto completo da fonteLee, W. S., Victor Alchanatis e Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, janeiro de 2014. http://dx.doi.org/10.32747/2014.7598158.bard.
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