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Статті в журналах з теми "CUDA FRAMEWORK"
Trujillo, Leonardo, Jose Manuel Muñoz Contreras, Daniel E. Hernandez, Mauro Castelli, and Juan J. Tapia. "GSGP-CUDA — A CUDA framework for Geometric Semantic Genetic Programming." SoftwareX 18 (June 2022): 101085. http://dx.doi.org/10.1016/j.softx.2022.101085.
Повний текст джерелаRosenberg, Duane, Pablo D. Mininni, Raghu Reddy, and Annick Pouquet. "GPU Parallelization of a Hybrid Pseudospectral Geophysical Turbulence Framework Using CUDA." Atmosphere 11, no. 2 (February 8, 2020): 178. http://dx.doi.org/10.3390/atmos11020178.
Повний текст джерелаWang, Fan, Xiao Jiang, and 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.
Повний текст джерелаBi, Yujiang, Yi Xiao, WeiYi Guo, Ming Gong, Peng Sun, Shun Xu, and 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.
Повний текст джерелаPeng, Bo, Junliang Lai, Yang Wang, Ling Wang, and Dong C. Liu. "CUDA-Based Parallel Computation Framework for Phase Root Seeking Algorithm." Journal of Medical Imaging and Health Informatics 4, no. 6 (December 1, 2014): 922–31. http://dx.doi.org/10.1166/jmihi.2014.1343.
Повний текст джерелаAhmed, Rafid, Md Sazzadul Islam, and Jia Uddin. "Optimizing Apple Lossless Audio Codec Algorithm using NVIDIA CUDA Architecture." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 1 (February 1, 2018): 70. http://dx.doi.org/10.11591/ijece.v8i1.pp70-75.
Повний текст джерелаMichailidis, P. D., and 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.
Повний текст джерелаBruel, Pedro, Marcos Amarís, and Alfredo Goldman. "Autotuning CUDA compiler parameters for heterogeneous applications using the OpenTuner framework." Concurrency and Computation: Practice and Experience 29, no. 22 (March 6, 2017): e3973. http://dx.doi.org/10.1002/cpe.3973.
Повний текст джерелаHadji-Kyriacou, Avelina, and Ognjen Arandjelović. "Raymarching Distance Fields with CUDA." Electronics 10, no. 22 (November 9, 2021): 2730. http://dx.doi.org/10.3390/electronics10222730.
Повний текст джерелаLee, Seongjae, and Taehyoun Kim. "Parallel Dislocation Model Implementation for Earthquake Source Parameter Estimation on Multi-Threaded GPU." Applied Sciences 11, no. 20 (October 11, 2021): 9434. http://dx.doi.org/10.3390/app11209434.
Повний текст джерелаДисертації з теми "CUDA FRAMEWORK"
Dworaczyk, Wiltshire Austin Aaron. "CUDA ENHANCED FILTERING IN A PIPELINED VIDEO PROCESSING FRAMEWORK." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1072.
Повний текст джерелаKarlsson, Per. "A GPU-based framework for efficient image processing." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-112093.
Повний текст джерелаGiordano, Andrea. "Sviluppo di una simulazione ad agenti di un modello di infezione virale tramite il framework FLAME GPU." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15755/.
Повний текст джерелаFabian, Xavier. "Precision measurements in the weak interaction framework: development of realistic simulations for the LPCTrap device installed at GANIL." Caen, 2015. http://hal.in2p3.fr/tel-01288412.
Повний текст джерелаThis work belongs to the effort presently deployed to measure the angular correlation parameter aβν in three nuclear beta decays (6He+, 35Ar+ and 19Ne+). The V-A structure of the weak interaction implies that aβν = +1 for a pure Fermi transition and aβν = -1/3 for a pure Gamow-Teller transition. A thorough measurement of this parameter to check any deviation from these values may lead to the discovery of possible exotic currents. Furthermore, the measurement of aβν in mirror transitions allows the extraction of Vud, the first element of the Cabibbo-Kobayashi-Maskawa (CKM) matrix. The LPCTrap apparatus, installed at GANIL, is designed to ready a continuous ion beam for injection in a dedicated Paul trap. This latter device allows to have a quasi-ponctual source from which the decay products are detected in coincidence. It is from the study of the recoil ion time-of-flight (TOF) distribution that aβν is withdrawn and, since 2010, the associated Shake-Off (SO) probabilities. This study requires the complete simulation of the LPCTrap experiments. The major part of this work is dedicated to such simulations, especially to the modeling of the trapped ion cloud dynamic. The CLOUDA program, which takes advantage of graphics processing unit (GPU), was developed in this context and its full characterization is presented here. Three important aspects are addressed: the electromagnetic trapping field, the realistic collisions between the ions and the buffer gas atoms and the space charge effect. The present work shows the importance of these simulations to increase the control of the systematic errors on aβν
Badalov, Alexey Pavlovich. "Coprocessor integration for real-time event processing in particle physics detectors." Doctoral thesis, Universitat Ramon Llull, 2016. http://hdl.handle.net/10803/396128.
Повний текст джерелаLa física de altas energías dispone actualmente de aceleradores con energías mayores, sensores más precisos y métodos de recopilación de datos más flexibles que nunca. Su rápido progreso necesita aún más potencia de cálculo; el hardware masivamente paralelo, como las unidades de procesamiento gráfico, nos brinda esta potencia a un coste mucho más bajo que las CPUs tradicionales. Sin embargo, para usar eficientemente este hardware necesitamos algoritmos nuevos y nuevos enfoques de organización de datos difíciles de integrarse con el software existente. En este trabajo, se investiga cómo se pueden usar estos algoritmos paralelos en las infraestructuras de software ya existentes y que están orientadas a CPUs. Se propone una solución en forma de un servicio que comunica con los diversos pipelines que procesan los eventos de las correspondientes colisiones de particulas, reúne los datos en lotes y se los entrega a los algoritmos paralelos acelerados por hardware. Este servicio se integra con Gaudí — la infraestructura del entorno de software que usan dos de los cuatro gran experimentos del Gran Colisionador de Hadrones. Se examinan los costes añadidos por el servicio en los algoritmos paralelos. Se estudia un caso de uso del servicio para ejecutar un algoritmo paralelo para el VELO Pixel (el subdetector encargado de la localización de vértices en el upgrade del experimento LHCb) y se estudian las características de rendimiento de los distintos tamaños de lotes de datos. Finalmente, las conclusiones se contextualizan dentro la perspectiva de los requerimientos para el sistema de trigger de LHCb.
High-energy physics experiments today have higher energies, more accurate sensors, and more flexible means of data collection than ever before. Their rapid progress requires ever more computational power; and massively parallel hardware, such as graphics cards, holds the promise to provide this power at a much lower cost than traditional CPUs. Yet, using this hardware requires new algorithms and new approaches to organizing data that can be difficult to integrate with existing software. In this work, I explore the problem of using parallel algorithms within existing CPU-orientated frameworks and propose a compromise between the different trade-offs. The solution is a service that communicates with multiple event-processing pipelines, gathers data into batches, and submits them to hardware-accelerated parallel algorithms. I integrate this service with Gaudi — a framework underlying the software environments of two of the four major experiments at the Large Hadron Collider. I examine the overhead the service adds to parallel algorithms. I perform a case study of using the service to run a parallel track reconstruction algorithm for the LHCb experiment's prospective VELO Pixel subdetector and look at the performance characteristics of using different data batch sizes. Finally, I put the findings into perspective within the context of the LHCb trigger's requirements.
Varadarajan, Aravind Krishnan. "Improving Bio-Inspired Frameworks." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/97506.
Повний текст джерелаMS
Odeh, Khuloud, Annita Seckinger, and Carina Forsman-Knecht. "Connected Urban Development (CUD) Initiative as an Approach towards Sustainability in Urban Areas." Thesis, Blekinge Tekniska Högskola, Avdelningen för maskinteknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3127.
Повний текст джерелаMed det ökande antalet informations-och kommunikationsteknik (IKT)-baserade initiativ som riktar sig mot hållbarhet i städerna, är det viktigt att undersöka de eventuella bidrag dessa initiativ kan ge när de stödjer samhällens hållbara utveckling. Denna uppsats undersöker Connected urban developments (CUD) potential som initiativ och dess stödjande strategi för städers hållbara utveckling. Förslag till justeringar av CUDs strategi studeras och rekommendationer för bättre anpassning av nuvarande strategier till CUDs nya mål ges. Orginalstrategierna skrevs utifrån orginalmålet, reducering av koldioxidutsläpp och behövde justeras för att bättre inriktas mot det nya målet, global hållbarhet. Detta uppnåddes genom att studera Connected Urban Development som organisation och genom att intervjua representanter från CUDs organisation, representanter för Pilotprojektsstäder, olika experter på stadsplanering, IT och hållbar utveckling (både forskare och praktiker). Ett vetenskapligt förhållningssätt till kunskap om hållbarhetsbegrepp utgör grunden för denna utvärdering av CUD-initiativet, dess fördelar och utmaningar, inklusive rollen för bredbandsuppkoppling och tillämpning av informations-och kommunikationsteknik. I detta sammanhang ges rekommendationer för att ytterligare förbättra CUD-initiativets effektivitet gällande städers hållbara utveckling. Gruppens forskning utgick från ett föreställt idealiskt initiativ i förhållande till systemets gränser och komponenter, strategiska riktlinjer, åtgärder och verktyg - "CUD Gold" och åtgärder föreslås för att göra CUD mer strategiska i sin banbrytande ansträngning för att stödja hållbara städer på global nivå.
Carina Forsman-Knecht S. Bellevuevägen 2 371 61 Lyckeby E-mail: cinaknecht@gmail.com US +1 435 503 8460 Sweden +46 (0)733 629951 Skype: cinaknecht Annita Seckinger 10620 Barnwood Lane Potomac Maryland 20854 email: a2ndger@yahoo.com Khuloud Odeh address: 2501 Calvert St. NW Apt. 401, Washington, DC, 20008, USA phones: home +1-202-332-1103, mobile:+1 301-768-1886 email: khuloud.odeh@gmail.com
Awan, Ammar Ahmad. "Co-designing Communication Middleware and Deep Learning Frameworks for High-Performance DNN Training on HPC Systems." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587433770960088.
Повний текст джерелаOliveira, Danilo Senen Cavallieri de. "Fintechs e inclusão financeira: o caso da implementação de uma plataforma digital de pagamentos em favelas do Rio de Janeiro e São Paulo." reponame:Repositório Institucional do FGV, 2018. http://hdl.handle.net/10438/23940.
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O presente estudo visa responder à pergunta de pesquisa: 'Como ocorre o processo de implantação de uma plataforma digital de pagamentos, desenvolvida por uma fintech, que visa promover a inclusão financeira?'. Para isso, foi analisado o caso do CUFA Card, plataforma digital de pagamentos implantada na favela Parque União, parte do Complexo da Maré no Rio de Janeiro, e na comunidade de Heliópolis, em São Paulo. Compõem o presente trabalho uma revisão de literatura, que nos permite compreender como as fintechs podem ser uma oportunidade para se promover a inclusão financeira; e um estudo de caso, onde foram realizadas entrevistas com os grupos sociais envolvidos na criação ou implantação dessa plataforma, as quais foram transcritas, codificadas e analisadas utilizando o software Atlas TI©. Como principal contribuição, temos a análise de como ocorre a implantação de uma plataforma digital de pagamentos, que visa promover a inclusão financeira a luz da implantação do CUFA Card, bem como com a descrição de como ocorreu a articulação entre diferentes grupos sociais para viabilização do projeto e explicitação do conteúdo resultante da implantação dessa tecnologia, a qual é derivada da parceria entre a fintech Conta Um e a organização FHolding/CUFA. Para isso utilizou-se do multilevel framework de Pozzebon, Diniz e Jayo (2009), uma teoria nativa do campo de sistemas da informação, que possibilitou um melhor entendimento sobre o caso estudado, ao analisar, concomitantemente, aspectos tecnológicos e sociais da implantação dessa da plataforma em um dado contexto onde essa está sendo inserida. O estudo contribui também com a geração de insights para pesquisas futuras e para a prática, ao estudar a relação entre fintechs e inclusão financeira, um tema ainda incipiente na literatura, e ao analisar o processo de implantação da plataforma de pagamento, destacando questões cruciais desse processo.
The present study aims to answer the research question: 'How does the process of implementing a digital payments platform, developed by a fintech, that aims to pro-mote financial inclusion occurs?'. For that, was analyzed the case of CUFA Card, a digital payment platform implemented in the Parque União favela, part of the Com-plexo da Maré in Rio de Janeiro, and in the community of Heliópolis, in São Paulo. The present work compiles a literature review, which allows us to understand how fintechs can be an opportunity to promote financial inclusion; and a case study where interviews were conducted with the social groups involved in the creation or imple-mentation of this platform, that were transcribed, coded and analyzed using Atlas TI © software. As a main contribution, we have the analysis on how this process occurs in the light of the CUFA Card implementation, as well as describing how the articulation between different social groups occurred to project feasibility and explicit content resulting from the implementation of this technology, which is derived from the partnership between the fintech Conta Um and the FHolding /CUFA organization. The work also brings as contributions the articulation of the multilevel framework, by Pozzebon, Diniz and Jayo (2009) and which is native to the information systems field, that made possible a better understanding of the case studied, while simultaneously analyzing technological and social aspects of the implementation of this platform in a given context where it is being inserted. It also contributes to the generation of in-sights for future research and practice, studying the relationship between fintechs and financial inclusion, a still incipient topic in the literature, and analysing the implementation process of a payment platform, highlighting what is the crucial issues in this process.
Chen, Yu-Wen, and 陳郁文. "Online Derivatives Arbitrage Trading Mechanism Based on CUDA Framework." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/35874995565142123742.
Повний текст джерела國立交通大學
資訊科學與工程研究所
104
Parallel Computing denotes a technique to simultaneously process a huge amount of data with low dependency by multiple processing units. In other words, we can divide a complex problem or a huge data set into many small independent problems or small data chunks, and reduce the overall computational time through allocating these problems to different process units in the same time. High frequency trading is becoming important in financial markets and the ability to deal a huge amount of financial trading data in real time is thus critical. This thesis apply parallel computing technique to search for arbitrage opportunities and design trading strategies for TAIEX options and futures. Usually, arbitrage opportunity comes from occasionally irrational price quotes. In highly competitive and mature markets, arbitrage opportunities are not only extremely rare but also fleeting. Therefore, the technique which can process a great number of data rapidly such as Parallel Computing is very suitable for finding arbitrage opportunity. This research revises the framework of [5]. I implement the following arbitrage strategies: convexity strategy and put-call-future parity strategy, and we have introduced spread strategy in my framework to seek arbitrage opportunities in TAIEX Exchange of Futures. Besides, the off-line framework that uses virtual exchange to simulate tradings. I add the online real-time trading mode which can receive price quotes from a remote server and send back the encoded strategies through a TCP channel.
Книги з теми "CUDA FRAMEWORK"
1944-, Kay Cristóbal, Peek Peter 1947-, and International Labour Office, eds. Labour and development in rural Cuba: A study prepared for the International Labour Office within the framework of the World Employment Programme. Basingstoke: Macmillan, 1988.
Знайти повний текст джерелаDiÌaz-Briquets, Sergio. A Transparency/accountability framework for combating corruption in post-Castro Cuba. The Institute, 2002.
Знайти повний текст джерелаBarquin, Nicolas Philip. Real estate opportunities for U.S. investors in post-Castro Cuba: A framework for analysis. 2006.
Знайти повний текст джерелаAlexander, Orakhelashvili. Part 1 The Cold War Era (1945–89), 9 The Cuban Missile Crisis—1962. Oxford University Press, 2018. http://dx.doi.org/10.1093/law/9780198784357.003.0009.
Повний текст джерелаClealand, Danielle Pilar. Conclusion. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190632298.003.0011.
Повний текст джерелаSchmitt, Kenneth E. Cura animarum in the twentieth century and beyond: Toward the development of an ethical framework for the practice of pastoral counseling. 1991.
Знайти повний текст джерелаAhmad, Saiful Yazan, and Norlida Ab. Wahab. Mudahnya Takaful: Soalan lazim bagi rujukan dan kefahaman pantas. UUM Press, 2017. http://dx.doi.org/10.32890/9789672064190.
Повний текст джерелаBaker, Catherine. Making War on Bodies. Edinburgh University Press, 2020. http://dx.doi.org/10.3366/edinburgh/9781474446181.001.0001.
Повний текст джерелаParrott, R. Joseph, and Mark Atwood Lawrence, eds. The Tricontinental Revolution. Cambridge University Press, 2022. http://dx.doi.org/10.1017/9781009004824.
Повний текст джерелаBryant, Sherwin K., Ben Vinson, and Rachel Sarah O’Toole. Introduction. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252036637.003.0010.
Повний текст джерелаЧастини книг з теми "CUDA FRAMEWORK"
Wei, Wei, and Yanqiong Huang. "CUDA Framework for Turbulence Flame Simulation." In Lecture Notes in Electrical Engineering, 791–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21697-8_101.
Повний текст джерелаFatkina, Anna, Maxim Gonchar, Liudmila Kolupaeva, Dmitry Naumov, and Konstantin Treskov. "CUDA Support in GNA Data Analysis Framework." In Computational Science and Its Applications – ICCSA 2018, 12–24. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95171-3_2.
Повний текст джерелаNina Paravecino, Fanny, and David Kaeli. "Accelerated Connected Component Labeling Using CUDA Framework." In Computer Vision and Graphics, 502–9. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11331-9_60.
Повний текст джерелаBaek, Nakhoon. "A Prototype Implementation of NNEF Execution Framework with CUDA Acceleration." In Lecture Notes in Electrical Engineering, 129–32. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6385-4_12.
Повний текст джерелаKosiachenko, Lisa, Nathaniel Hart, and Munehiro Fukuda. "MASS CUDA: A General GPU Parallelization Framework for Agent-Based Models." In Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection, 139–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24209-1_12.
Повний текст джерелаOhshima, Satoshi, Shoichi Hirasawa, and Hiroki Honda. "OMPCUDA : OpenMP Execution Framework for CUDA Based on Omni OpenMP Compiler." In Beyond Loop Level Parallelism in OpenMP: Accelerators, Tasking and More, 161–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13217-9_13.
Повний текст джерелаJung, Hanwoong, Youngmin Yi, and Soonhoi Ha. "Automatic CUDA Code Synthesis Framework for Multicore CPU and GPU Architectures." In Parallel Processing and Applied Mathematics, 579–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31464-3_59.
Повний текст джерелаZhu, Qi, Li Shen, Xinbiao Gan, and Zhiying Wang. "A Compiler Framework for Translating Standard C into Optimized CUDA Code." In Proceedings of the International Conference on Human-centric Computing 2011 and Embedded and Multimedia Computing 2011, 501–14. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2105-0_44.
Повний текст джерелаWang, Zhanghu, Pin Lv, and Changwen Zheng. "CUDA on Hadoop: A Mixed Computing Framework for Massive Data Processing." In Advances in Intelligent Systems and Computing, 253–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37835-5_23.
Повний текст джерелаLuo, Ruiyi, and Qian Yin. "A Novel Parallel Clustering Algorithm Based on Artificial Immune Network Using nVidia CUDA Framework." In Human-Computer Interaction. Design and Development Approaches, 598–607. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21602-2_65.
Повний текст джерелаТези доповідей конференцій з теми "CUDA FRAMEWORK"
Breitbart, Jens. "CuPP - A framework for easy CUDA integration." In Distributed Processing (IPDPS). IEEE, 2009. http://dx.doi.org/10.1109/ipdps.2009.5160937.
Повний текст джерелаShete, Pritam Prakash, P. P. K. Venkat, Dinesh M. Sarode, Mohini Laghate, S. K. Bose, and R. S. Mundada. "Object oriented framework for CUDA based image processing." In 2012 International Conference on Communication, Information & Computing Technology (ICCICT). IEEE, 2012. http://dx.doi.org/10.1109/iccict.2012.6398223.
Повний текст джерелаJain, Akshat, Owais Kazi, Raviraj Joshi, Shraddha Basantwani, Yogita Bang, and Rahul Khengare. "Hyaline: A Transparent Distributed Computing Framework for CUDA." In 2019 IEEE 5th International Conference for Convergence in Technology (I2CT). IEEE, 2019. http://dx.doi.org/10.1109/i2ct45611.2019.9033789.
Повний текст джерелаChoi, Jake, Heon Young Yeom, and Yoonhee Kim. "Implementing CUDA Unified Memory in the PyTorch Framework." In 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C). IEEE, 2021. http://dx.doi.org/10.1109/acsos-c52956.2021.00029.
Повний текст джерелаRamroach, Sterling, Jonathan Herbert, and Ajay Joshi. "CUDA-ACCELERATED FEATURE SELECTION." In International Conference on Emerging Trends in Engineering & Technology (IConETech-2020). Faculty of Engineering, The University of the West Indies, St. Augustine, 2020. http://dx.doi.org/10.47412/juqg5057.
Повний текст джерелаWezowicz, M., and M. Taufer. "On the Cost of a General GPU Framework: The Strange Case of CUDA 4.0 vs. CUDA 5.0." In 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC). IEEE, 2012. http://dx.doi.org/10.1109/sc.companion.2012.310.
Повний текст джерелаHernandez-Gutierrez, Erick, Alonso Ramirez-Manzanares, Jose L. Marroquin, Mario Ocampo-Pineda, and Alessandro Daducci. "Cuda Parallelization of Commit Framework for Efficient Microstructure-Informed Tractography." In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI). IEEE, 2019. http://dx.doi.org/10.1109/isbi.2019.8759098.
Повний текст джерелаWezowicz, Matthew Robert. "Poster: On the Cost of a General GPU Framework: The Strange Case of CUDA 4.0 vs. CUDA 5.0." In 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC). IEEE, 2012. http://dx.doi.org/10.1109/sc.companion.2012.311.
Повний текст джерелаKulkarni, Manjiri K., and J. S. Umale. "Prediction of chemical bond formation using efficient CUDA based HPC framework." In 2016 International Conference on Computing Communication Control and automation (ICCUBEA). IEEE, 2016. http://dx.doi.org/10.1109/iccubea.2016.7859988.
Повний текст джерелаJing Huang, S. P. Ponce, Seung In Park, Yong Cao, and F. Quek. "GPU-accelerated computation for robust motion tracking using the CUDA framework." In 5th International Conference on Visual Information Engineering (VIE 2008). IEE, 2008. http://dx.doi.org/10.1049/cp:20080353.
Повний текст джерелаЗвіти організацій з теми "CUDA FRAMEWORK"
Jamerson, Allen J. United States - Cuba Policy: Strategic Framework for Re-emergent Relations. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada415395.
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