Дисертації з теми "NVIDIA CUDA GPU"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся з топ-30 дисертацій для дослідження на тему "NVIDIA CUDA GPU".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Переглядайте дисертації для різних дисциплін та оформлюйте правильно вашу бібліографію.
Ikeda, Patricia Akemi. "Um estudo do uso eficiente de programas em placas gráficas." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-25042012-212956/.
Повний текст джерелаInitially designed for graphical processing, the graphic cards (GPUs) evolved to a high performance general purpose parallel coprocessor. Due to huge potencial that graphic cards offer to several research and commercial areas, NVIDIA was the pioneer lauching of CUDA architecture (compatible with their several cards), an environment that take advantage of computacional power combined with an easier programming. In an attempt to make use of all capacity of GPU, some practices must be followed. One of them is to maximizes hardware utilization. This work proposes a practical and extensible tool that helps the programmer to choose the best configuration and achieve this goal.
Rivera-Polanco, Diego Alejandro. "COLLECTIVE COMMUNICATION AND BARRIER SYNCHRONIZATION ON NVIDIA CUDA GPU." Lexington, Ky. : [University of Kentucky Libraries], 2009. http://hdl.handle.net/10225/1158.
Повний текст джерелаTitle from document title page (viewed on May 18, 2010). Document formatted into pages; contains: ix, 88 p. : ill. Includes abstract and vita. Includes bibliographical references (p. 86-87).
Harvey, Jesse Patrick. "GPU acceleration of object classification algorithms using NVIDIA CUDA /." Online version of thesis, 2009. http://hdl.handle.net/1850/10894.
Повний текст джерелаLerchundi, Osa Gorka. "Fast Implementation of Two Hash Algorithms on nVidia CUDA GPU." Thesis, Norwegian University of Science and Technology, Department of Telematics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9817.
Повний текст джерелаUser needs increases as time passes. We started with computers like the size of a room where the perforated plaques did the same function as the current machine code object does and at present we are at a point where the number of processors within our graphic device unit its not enough for our requirements. A change in the evolution of computing is looming. We are in a transition where the sequential computation is losing ground on the benefit of the distributed. And not because of the birth of the new GPUs easily accessible this trend is novel but long before it was used for projects like SETI@Home, fightAIDS@Home, ClimatePrediction and there were shouting from the rooftops about what was to come. Grid computing was its formal name. Until now it was linked only to distributed systems over the network, but as this technology evolves it will take different meaning. nVidia with CUDA has been one of the first companies to make this kind of software package noteworthy. Instead of being a proof of concept its a real tool. Where the transition is expressed in greater magnitude in which the true artist is the programmer who uses it and achieves performance increases. As with many innovations, a community distributed worldwide has grown behind this software package and each one doing its bit. It is noteworthy that after CUDA release a lot of software developments grown like the cracking of the hitherto insurmountable WPA. With Sony-Toshiba-IBM (STI) alliance it could be said the same thing, it has a great community and great software (IBM is the company in charge of maintenance). Unlike nVidia is not as accessible as it is but IBM is powerful enough to enter home made supercomputing market. In this case, after IBM released the PS3 SDK, a notorious application was created using the benefits of parallel computing named Folding@Home. Its purpose is to, inter alia, find the cure for cancer. To sum up, this is only the beginning, and in this thesis is sized up the possibility of using this technology for accelerating cryptographic hash algorithms. BLUE MIDNIGHT WISH (The hash algorithm that is applied to the surgery) is undergone to an environment change adapting it to a parallel capable code for creating empirical measures that compare to the current sequential implementations. It will answer questions that nowadays havent been answered yet. BLUE MIDNIGHT WISH is a candidate hash function for the next NIST standard SHA-3, designed by professor Danilo Gligoroski from NTNU and Vlastimil Klima an independent cryptographer from Czech Republic. So far, from speed point of view BLUE MIDNIGHT WISH is on the top of the charts (generally on the second place right behind EDON-R - another hash function from professor Danilo Gligoroski). One part of the work on this thesis was to investigate is it possible to achieve faster speeds in processing of Blue Midnight Wish when the computations are distributed among the cores in a CUDA device card. My numerous experiments give a clear answer: NO. Although the answer is negative, it still has a significant scientific value. The point is that my work acknowledges viewpoints and standings of a part of the cryptographic community that is doubtful that the cryptographic primitives will benefit when executed in parallel in many cores in one CPU. Indeed, my experiments show that the communication costs between cores in CUDA outweigh by big margin the computational costs done inside one core (processor) unit.
Sreenibha, Reddy Byreddy. "Performance Metrics Analysis of GamingAnywhere with GPU accelerated Nvidia CUDA." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16846.
Повний текст джерелаSavioli, Nicolo'. "Parallelization of the algorithm WHAM with NVIDIA CUDA." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/6377/.
Повний текст джерелаZaahid, Mohammed. "Performance Metrics Analysis of GamingAnywhere with GPU acceletayed NVIDIA CUDA using gVirtuS." Thesis, Blekinge Tekniska Högskola, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16852.
Повний текст джерелаVirk, Bikram. "Implementing method of moments on a GPGPU using Nvidia CUDA." Thesis, Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33980.
Повний текст джерелаEkstam, Ljusegren Hannes, and Hannes Jonsson. "Parallelizing Digital Signal Processing for GPU." Thesis, Linköpings universitet, Programvara och system, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167189.
Повний текст джерелаAraújo, João Manuel da Silva. "Paralelização de algoritmos de Filtragem baseados em XPATH/XML com recurso a GPUs." Master's thesis, FCT - UNL, 2009. http://hdl.handle.net/10362/2530.
Повний текст джерелаEsta dissertação envolve o estudo da viabilidade da utilização dos GPUs para o processamento paralelo aplicado aos algoritmos de filtragem de notificações num sistema editor/assinante. Este objectivo passou por realizar uma comparação de resultados experimentais entre a versão sequencial (nos CPUs) e a versão paralela de um algoritmo de filtragem escolhido como referência. Essa análise procurou dar elementos para aferir se eventuais ganhos da exploração dos GPUs serão suficientes para compensar a maior complexidade do processo.
Shi, Bobo. "Implementation and Performance Analysis of Many-body Quantum Chemical Methods on the Intel Xeon Phi Coprocessor and NVIDIA GPU Accelerator." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1462793739.
Повний текст джерелаSenthil, Kumar Nithin. "Designing optimized MPI+NCCL hybrid collective communication routines for dense many-GPU clusters." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1619132252608831.
Повний текст джерелаMacenauer, Pavel. "Detekce objektů na GPU." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234942.
Повний текст джерелаStraňák, Marek. "Raytracing na GPU." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237020.
Повний текст джерелаBartosch, Nadine. "Correspondence-based pairwise depth estimation with parallel acceleration." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34372.
Повний текст джерелаChehaimi, Omar. "Parallelizzazione dell'algoritmo di ricostruzione di Feldkamp-Davis-Kress per architetture Low-Power di tipo System-On-Chip." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13918/.
Повний текст джерелаČermák, Michal. "Detekce pohyblivého objektu ve videu na CUDA." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236992.
Повний текст джерелаPecháček, Václav. "Akcelerace heuristických metod diskrétní optimalizace na GPU." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236550.
Повний текст джерелаPospíchal, Petr. "Akcelerace genetického algoritmu s využitím GPU." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236783.
Повний текст джерелаMintěl, Tomáš. "Interpolace obrazových bodů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236736.
Повний текст джерелаNěmeček, Petr. "Geometrické transformace obrazu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-236764.
Повний текст джерелаHordemann, Glen J. "Exploring High Performance SQL Databases with Graphics Processing Units." Bowling Green State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1380125703.
Повний текст джерелаVenkatasubramanian, Sundaresan. "Tuned and asynchronous stencil kernels for CPU/GPU systems." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29728.
Повний текст джерелаCommittee Chair: Vuduc, Richard; Committee Member: Kim, Hyesoon; Committee Member: Vetter, Jeffrey. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Music, Sani. "Grafikkort till parallella beräkningar." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20150.
Повний текст джерелаThis study describes how we can use graphics cards for general purpose computingwhich differs from the most usual field where graphics cards are used, multimedia.The study describes and discusses present day alternatives for usinggraphic cards for general operations. In this study we use and describe NvidiaCUDA architecture. The study describes how we can use graphic cards for generaloperations from the point of view that we have programming knowledgein some high-level programming language and knowledge of how a computerworks. We use accelerated libraries (THRUST and CUBLAS) to achieve our goalson the graphics card, which are software development and benchmarking. Theresults are programs countering certain problems (matrix multiplication, sorting,binary search, vector inverting) and the execution time and speedup forthese programs. The graphics card is compared to the processor in serial andthe processor in parallel. Results show a speedup of up to approximatly 50 timescompared to serial implementations on the processor.
Adeboye, Taiyelolu. "Robot Goalkeeper : A robotic goalkeeper based on machine vision and motor control." Thesis, Högskolan i Gävle, Avdelningen för elektronik, matematik och naturvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-27561.
Повний текст джерелаSubramoniapillai, Ajeetha Saktheesh. "Architectural Analysis and Performance Characterization of NVIDIA GPUs using Microbenchmarking." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1344623484.
Повний текст джерелаCazalas, Jonathan M. "Efficient and Scalable Evaluation of Continuous, Spatio-temporal Queries in Mobile Computing Environments." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5154.
Повний текст джерелаID: 031001567; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Title from PDF title page (viewed August 26, 2013).; Thesis (Ph.D.)--University of Central Florida, 2012.; Includes bibliographical references (p. 103-112).
Ph.D.
Doctorate
Computer Science
Engineering and Computer Science
Computer Science
Maurer, Andreas. "Methods for Multisensory Detection of Light Phenomena on the Moon as a Payload Concept for a Nanosatellite Mission." Thesis, Luleå tekniska universitet, Rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-80785.
Повний текст джерелаChi, Ping-Lin, and 机炳霖. "Simulation of Optical Properties for Thin Film Using CUDA on NVIDIA GPUs." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/23775928600592540874.
Повний текст джерела國立高雄第一科技大學
光電工程研究所
99
Firstly, the thesis will discuss the difference of parallel computing between the ways of data permutation in multi-threads and single thread, then measure whether the performance of GPU can increase the efficiency and the confidence in the accuracy. Compared with Intel i7 series CPU, the efficiency of NVIDIA G100 series GPU increases more than 40 times, and the effect for relative difference is less than that of 10E-15. That is to say, GPU can be a replacement of CPU to conduct huge calculation. Compared with the simulation programming of development platform with Matlab 2008 , the efficiency increases up to 200 times. In this programming, we have chosen two ways to optimize, including the useful cache memory and PCI-E bandwidth. Besides, it is also be mentioned about the Calculating method for improving the simulation programming and the solution for Many-core processor and multi-GPU. As for the functions, it provides the calculation for the transmittance and reflection of multi-selectivity absorb film, the absorbance of sunlight, the collocation of the best thickness, the supposition of the multi-thickness, and primitive derivation of refractive index and extinction coefficient. The match rate is up to 95% according to comparison of simulation result with experiment date. These are the functions that will be used.
Chen, Wei-Sheng, and 陳威勝. "Hybrid Simulation of Optical Properties for Thin Film Using CUDA on NVIDIA GPUs." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/99410635297475769146.
Повний текст джерела國立高雄第一科技大學
光電工程研究所
101
This study is optical simulation and multifunction program design by CUDA, it contains: 1.Optimization in the thickness of solar selective absorbing film, 2.Reflectivity of optimal thickness fitting, 3.The reflectivity simulation of double-sided coating, 4.The optimal film thickness fitting on superlattice, 5.The reflectivity of multilayer films and the calculation of the absorption rate. Then measure whether the performance of GPU can increase the efficiency and the confidence in the accuracy. Compared with Intel i7 series CPU, the efficiency of NVIDIA G100 series GPU increases more than 40 times, and the effect for relative difference is less than that of 5%. That is to say, GPU can be a replacement of CPU to conduct huge calculation. Compared with the simulation programming of development platform with Matlab 2008 , the efficiency increases up to 200 times.