Academic literature on the topic 'GPU Accelerated'
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Journal articles on the topic "GPU Accelerated"
Lu, Q., and J. Amundson. "Synergia CUDA: GPU-accelerated accelerator modeling package." Journal of Physics: Conference Series 513, no. 5 (June 11, 2014): 052021. http://dx.doi.org/10.1088/1742-6596/513/5/052021.
Full textJiang, Hao, Chen-Wei Xu, Zhi-Yong Liu, and Li-Yan Yu. "GPU-Accelerated Apriori Algorithm." ITM Web of Conferences 12 (2017): 03046. http://dx.doi.org/10.1051/itmconf/20171203046.
Full textEndo, Yutaka, Tomoyoshi Shimobaba, Takashi Kakue, and Tomoyoshi Ito. "GPU-accelerated compressive holography." Optics Express 24, no. 8 (April 11, 2016): 8437. http://dx.doi.org/10.1364/oe.24.008437.
Full textFerroni, Francesco, Edmund Tarleton, and Steven Fitzgerald. "GPU accelerated dislocation dynamics." Journal of Computational Physics 272 (September 2014): 619–28. http://dx.doi.org/10.1016/j.jcp.2014.04.052.
Full textKilgard, Mark J., and Jeff Bolz. "GPU-accelerated path rendering." ACM Transactions on Graphics 31, no. 6 (November 2012): 1–10. http://dx.doi.org/10.1145/2366145.2366191.
Full textZhu, Rui, Chang Nian Chen, and Lei Hua Qin. "An Transfer Latency Optimized Solution in GPU-Accelerated De-Duplication." Applied Mechanics and Materials 336-338 (July 2013): 2059–62. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.2059.
Full textWang, Qiao, and Chen Meng. "PhotoNs-GPU: A GPU accelerated cosmological simulation code." Research in Astronomy and Astrophysics 21, no. 11 (December 1, 2021): 281. http://dx.doi.org/10.1088/1674-4527/21/11/281.
Full textFan, Mengran, Jian Wang, Huaipan Jiang, Yilin Feng, Mehrdad Mahdavi, Kamesh Madduri, Mahmut T. Kandemir, and Nikolay V. Dokholyan. "GPU-Accelerated Flexible Molecular Docking." Journal of Physical Chemistry B 125, no. 4 (January 26, 2021): 1049–60. http://dx.doi.org/10.1021/acs.jpcb.0c09051.
Full textWang, Liang, Yi Sheng Zhang, Bin Zhu, Chi Xu, Xiao Wei Tian, Chao Wang, Jian Hua Mo, and Jian Li. "GPU Accelerated Parallel Cholesky Factorization." Applied Mechanics and Materials 148-149 (December 2011): 1370–73. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.1370.
Full textSloup, Petr. "GPU-accelerated raster map reprojection." Geoinformatics FCE CTU 15, no. 1 (July 22, 2016): 61–68. http://dx.doi.org/10.14311/gi.15.1.5.
Full textDissertations / Theses on the topic "GPU Accelerated"
Lionetti, Fred. "GPU accelerated cardiac electrophysiology." Diss., [La Jolla] : University of California, San Diego, 2010. http://wwwlib.umi.com/cr/ucsd/fullcit?p1474756.
Full textTitle from first page of PDF file (viewed April 14, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 85-89).
Mäkelä, J. (Jussi). "GPU accelerated face detection." Master's thesis, University of Oulu, 2013. http://urn.fi/URN:NBN:fi:oulu-201303181103.
Full textGrafiikkaprosessorit kykenevät massiiviseen rinnakkaislaskentaan ja niiden käyttö yleiseen laskentaan on kasvava kiinnostuksen aihe. Eräs alue missä kiihdytyksen käytöstä on kiinnostuttu on laskennallisesti raskaat konenäköalgoritmit kuten kasvojen ilmaisu ja tunnistus. Kasvojen ilmaisua käytetään useissa sovelluksissa, kuten kameroiden automaattitarkennuksessa, kasvojen ja tunteiden tunnistuksessa sekä kulun valvonnassa. Tässä työssä kasvojen ilmaisualgoritmia kiihdytettiin grafiikkasuorittimella käyttäen OpenCL-rajapintaa. Työn tavoite oli parantunut suorituskyky kuitenkin niin että implementaatiot pysyivät toiminnallisesti samanlaisina. OpenCL-versio perustui optimoituun verrokki-implementaatioon. Algoritmin eri vaiheiden kiihdytyksen mahdollisuuksia ja haasteita on tutkittu. Kiihdytetty- ja verrokki-implementaatio kuvaillaan ja niiden välistä suorituskykyeroa vertaillaan. Suorituskykyä arvioitiin ajoaikojen perusteella. Testeissä käytettiin kolmea kuvasarjaa joissa jokaisessa oli neljä eri kokoista kuvaa sekä kolmea lisäkuvaa jotka kuvastivat erikoistapauksia. Testit ajettiin kahdella erilailla varustellulla tietokoneella. Tuloksista voidaan nähdä että kasvojen ilmaisu soveltuu hyvin GPU kiihdytykseen, sillä algoritmin pystyy rinnakkaistamaan ja siinä pystyy käyttämään tehokasta tekstuurinkäsittelylaitteistoa. OpenCL-ympäristön alustaminen aiheuttaa viivettä joka vähentää jonkin verran suorituskykyetua. Testeissä todettiin kiihdytetyn implementaation antavan saman suuruisen tai jopa pienemmän suorituskyvyn kuin verrokki-implementaatio sellaisissa tapauksissa, joissa laskentaa oli vähän johtuen joko pienestä tai helposti käsiteltävästä kuvasta. Toisaalta kiihdytetyn implementaation suorituskyky oli hyvä verrattuna verrokki-implementaatioon kun käytettiin suuria ja monimutkaisia kuvia. Tulevaisuudessa OpenCL-ympäristön alustamisen aiheuttamat viivettä tulisi saada vähennettyä. Tämä työ on kiinnostava myös tulevaisuudessa kun OpenCL-kiihdytys tulee mahdolliseksi matkapuhelimissa
Graves, Alex. "GPU-Accelerated Feature Tracking." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1462372516.
Full textBaravdish, Gabriel. "GPU Accelerated Light Field Compression." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150558.
Full textKottravel, Sathish. "GPU accelerated Nonlinear Soft Tissue Deformation." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-76895.
Full textEdespong, Erik. "GPU Accelerated Surface Reconstruction from Particles." Thesis, Linköpings universitet, Institutionen för teknik och naturvetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93543.
Full textBASTOS, THIAGO DE ALMEIDA. "GPU-ACCELERATED ADAPTIVELY SAMPLED DISTANCE FIELDS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=12160@1.
Full textShape representation is a fundamental problem in Computer Graphics. Among known representations for three-dimensional objects, adaptively sampled distance fields (ADFs) are noted for their versatility. ADFs combine the concepts of geometry with volume data, allow objects to be represented with arbitrary precision, and consolidate several operations - such as visualization, level-of-detail modeling, collision detection, proximity tests, morphing and boolean operations | into a single representation. This work proposes methods to accelerate the reconstruction of static ADFs, to improve the quality of reconstructed fields, and to visualize ADF isosurfaces, making use of the massive computational power found in modern graphics hardware (GPUs). In order to effciently represent ADFs on graphics cards, a hierarchical structure based on perfect spatial hashing is proposed. Rendering of ADFs is done completely on GPUs, using a ray casting technique based on sphere tracing. Means to overcome the C0 and C1 discontinuities inherent to ADFs are suggested in order to attain smoothly shaded iso-surfaces. Finally, a new reconstruction method for ADFs, which can better represent curved surfaces, is proposed. Results are presented through simple interactive visualization applications, with ADFs generated from both triangle meshes and primitive solids.
Zhao, Kaiyong. "GPU accelerated sequence alignment /Zhao Kaiyong." HKBU Institutional Repository, 2016. https://repository.hkbu.edu.hk/etd_oa/378.
Full textSchmitt, Ryan Daniel. "GPU-Accelerated Point-Based Color Bleeding." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/810.
Full textPettersson, Niklas. "GPU-Accelerated Real-Time Surveillance De-Weathering." Thesis, Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97401.
Full textBooks on the topic "GPU Accelerated"
Annick, Le Goyat, ed. Skeleton Key: L'île de tous les dangers. [Paris]: Hachette Jeunesse, 2005.
Find full textSkeleton Key. New York: Philomel Books, 2002.
Find full textSkeleton key: An Alex Rider adventure. United States]: Paw Prints, 2008.
Find full textHorowitz, Anthony. Skeleton Key. London: Walker Books Ltd, 2009.
Find full textSkeleton key. London: Walker Books, 2014.
Find full textSkeleton Key: An Alex Rider adventure. New York: Speak, 2006.
Find full textHorowitz, Anthony. Skeleton Key. Paris: Hachette Jeunesse, 2012.
Find full textAissa, Mohamed Hassanine. GPU-accelerated CFD Simulations for Turbomachinery Design Optimization. von Karman Institute for Fluid Dynamics, 2018. http://dx.doi.org/10.35294/phdt201801.
Full textVaidya, Bhaumik. Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA: Effective techniques for processing complex image data in real time using GPUs. Packt Publishing - ebooks Account, 2018.
Find full textHorowitz, Anthony. Skeleton Key (Alex Rider). Puffin, 2006.
Find full textBook chapters on the topic "GPU Accelerated"
Liu, Yang, Wayne Huang, John Johnson, and Sheila Vaidya. "GPU Accelerated Smith-Waterman." In Computational Science – ICCS 2006, 188–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11758549_29.
Full textKrömer, Pavel, Jan Platoš, and Václav Snášel. "GPU Accelerated Genetic Clustering." In Lecture Notes in Computer Science, 410–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34859-4_41.
Full textFleissner, Sebastian. "GPU-Accelerated Montgomery Exponentiation." In Computational Science – ICCS 2007, 213–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72584-8_28.
Full textBaúto, João, Rui Neves, and Nuno Horta. "GPU-Accelerated SAX/GA." In SpringerBriefs in Applied Sciences and Technology, 45–66. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73329-6_5.
Full textAhmad, Mohamad Rosyidi, Ahmad Fakhri Arif Mat Zaid, Muhamad Husaini Abu Bakar, Mohd Fauzi Alias, and Pranesh Krishnan. "GPU Accelerated Speech Recognition." In Advanced Structured Materials, 59–69. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67750-3_6.
Full textOsama, Muhammad, Anton Wijs, and 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.
Full textRizk, Guillaume, and Dominique Lavenier. "GPU Accelerated RNA Folding Algorithm." In Lecture Notes in Computer Science, 1004–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01970-8_101.
Full textYang, Ying, Yu Gu, Chuanwen Li, Changyi Wan, and Ge Yu. "GPU-Accelerated Dynamic Graph Coloring." In Database Systems for Advanced Applications, 296–99. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18590-9_32.
Full textCao, Jian, Xiao-fang Xie, Jie Liang, and De-dong Li. "GPU Accelerated Target Tracking Method." In Advances in Intelligent and Soft Computing, 251–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25989-0_42.
Full textAndrzejewski, Witold, and Pawel Boinski. "GPU-Accelerated Collocation Pattern Discovery." In Advances in Databases and Information Systems, 302–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40683-6_23.
Full textConference papers on the topic "GPU Accelerated"
Chakroun, Imen, Nick Michiels, and Roel Wuyts. "GPU-accelerated CellProfiler." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621271.
Full textKonobrytskyi, Dmytro, Thomas Kurfess, Joshua Tarbutton, and 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.
Full textMetlicka, Magdalena, Donald Davendra, Frank Hermann, Markus Meier, and Matthias Amann. "GPU accelerated NEH algorithm." In 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS). IEEE, 2014. http://dx.doi.org/10.1109/cipls.2014.7007169.
Full textSanaullah, Ahmed, Saiful A. Mojumder, Kathleen M. Lewis, and Martin C. Herbordt. "GPU-accelerated charge mapping." In 2016 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2016. http://dx.doi.org/10.1109/hpec.2016.7761599.
Full textVan Ranst, Wiebe, Floris De Smedt, and Toon Goedemé. "GPU Accelerated ACF Detector." In International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006585102420248.
Full textDan Liu. "GPU accelerated background subtraction." In 2015 IEEE 16th International Conference on Communication Technology (ICCT). IEEE, 2015. http://dx.doi.org/10.1109/icct.2015.7399860.
Full textGraves, Alexander. "GPU-accelerated feature tracking." In 2016 IEEE National Aerospace and Electronics Conference (NAECON) and Ohio Innovation Summit (OIS). IEEE, 2016. http://dx.doi.org/10.1109/naecon.2016.7856842.
Full textKong, Jiangang, and Yangdong Deng. "GPU accelerated face detection." In 2010 International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2010. http://dx.doi.org/10.1109/icicip.2010.5564978.
Full textSchofield, Ian, and Amirhossein Alimohammad. "Parallel GPU-Accelerated Spike Sorting." In 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE). IEEE, 2019. http://dx.doi.org/10.1109/ccece.2019.8861978.
Full textNeophytou, N., and K. Mueller. "GPU accelerated image aligned splatting." In Volume Graphics 2005. IEEE, 2005. http://dx.doi.org/10.1109/vg.2005.194115.
Full textReports on the topic "GPU Accelerated"
Antz, Hartwig, Piotr Luszczek, Jack Dongarra, and Vinent Heuveline. GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement. Office of Scientific and Technical Information (OSTI), December 2011. http://dx.doi.org/10.2172/1173289.
Full textTognini, S., P. Canal, T. Evans, G. Lima, A. Lund, S. Johnson, S. Jun, V. Pascuzzi, and P. Romano. $Celeritas$: GPU-accelerated particle transport for detector simulation in High Energy Physics experiments. Office of Scientific and Technical Information (OSTI), March 2022. http://dx.doi.org/10.2172/1863002.
Full textKolev, T. CEED-MS36: High-order algorithmic developments and optimizations for large-scale GPU-accelerated simulations. Office of Scientific and Technical Information (OSTI), March 2021. http://dx.doi.org/10.2172/1845639.
Full textRyan, Benjamin, and Manichandra Morampudi. bolt: A GPU-Accelerated Solver for Marginally Collisional Kinetic Physics Using a High- Resolution Constrained Transport Scheme. Office of Scientific and Technical Information (OSTI), June 2022. http://dx.doi.org/10.2172/1873300.
Full textKommera, Pranay, Vinay Ramakrishnaiah, and Christine Sweeney. Accelerate M-TIP on GPUs and deploy to Summit and NERSC-9 (against simulated data) WBS 2.2.4.05 ExaFEL, Milestone ADSE13-199. Office of Scientific and Technical Information (OSTI), November 2021. http://dx.doi.org/10.2172/1830563.
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