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Статті в журналах з теми "Projection de performance":
Ramanath, Rohan, S. Sathiya Keerthi, Yao Pan, Konstantin Salomatin, and Kinjal Basu. "Efficient Vertex-Oriented Polytopic Projection for Web-Scale Applications." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (June 28, 2022): 3821–29. http://dx.doi.org/10.1609/aaai.v36i4.20297.
Li, Dong, Danli Wang, and Dongdong Weng. "Non-planar projection performance evaluation and projector pose optimization." Journal of the Society for Information Display 26, no. 6 (May 4, 2018): 352–68. http://dx.doi.org/10.1002/jsid.633.
Shi, Xudong, Feiqi Su, Jih-kwon Peir, Ye Xia, and Zhen Yang. "CMP cache performance projection." ACM SIGARCH Computer Architecture News 35, no. 1 (March 2007): 13–20. http://dx.doi.org/10.1145/1241601.1241607.
Bhatnagar, Saakaar. "Investigating the Surrogate Modeling Capabilities of Continuous Time Echo State Networks." Mathematical and Computational Applications 29, no. 1 (January 24, 2024): 9. http://dx.doi.org/10.3390/mca29010009.
Özge Onur, Tuğba. "An application of filtered back projection method for computed tomography images." International Review of Applied Sciences and Engineering 12, no. 2 (May 29, 2021): 194–200. http://dx.doi.org/10.1556/1848.2021.00231.
Zheng, Wei, Bin Li, Shu Bo Ren, Jiang Chen, and Jian Jun Wu. "Interference Modeling and Analysis for Inclined Projective Multiple Beams of GEO Satellite Communication Systems." Advanced Materials Research 756-759 (September 2013): 1204–9. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1204.
Wehner, Michael, David R. Easterling, Jay H. Lawrimore, Richard R. Heim, Russell S. Vose, and Benjamin D. Santer. "Projections of Future Drought in the Continental United States and Mexico." Journal of Hydrometeorology 12, no. 6 (December 1, 2011): 1359–77. http://dx.doi.org/10.1175/2011jhm1351.1.
Wang, Jiangang, Yuning Cui, Yawen Li, Wenqi Ren, and Xiaochun Cao. "Omnidirectional Image Super-resolution via Bi-projection Fusion." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 6 (March 24, 2024): 5454–62. http://dx.doi.org/10.1609/aaai.v38i6.28354.
Gu, Jiaxin, Ce Li, Baochang Zhang, Jungong Han, Xianbin Cao, Jianzhuang Liu, and David Doermann. "Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8344–51. http://dx.doi.org/10.1609/aaai.v33i01.33018344.
Moreira de Sousa, Luís, Laura Poggio, and Bas Kempen. "Comparison of FOSS4G Supported Equal-Area Projections Using Discrete Distortion Indicatrices." ISPRS International Journal of Geo-Information 8, no. 8 (August 9, 2019): 351. http://dx.doi.org/10.3390/ijgi8080351.
Дисертації з теми "Projection de performance":
Hagerman, James B. "Speak the Speech: Lessons in Projection, Clarity and Performance." Otterbein University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=otbn1589913342610542.
Hsu, Shu-Ting. "High performance micro scanners for miniature laser projection displays." Dresden TUDpress, 2009. http://d-nb.info/996064125/04.
Knapton, Benjamin W. "Using digital projection to evoke aesthetic ideas in performance." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/78129/1/Benjamin_Knapton_Thesis.pdf.
Chau-Dang, Tiffanie T. "Using Optical Illusions to Enhance Projection Design for Live Performance." Kent State University Honors College / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ksuhonors1588376296563101.
Gavoille, Clément. "Approche de projection de performance pour l’exploration de paramètres de conception de l’environnement Arm en HPC." Electronic Thesis or Diss., Bordeaux, 2024. http://www.theses.fr/2024BORD0004.
Today’s science increasingly uses simulation to model and understand the world around us. To improve their speed, accuracy, and modeling capabilities, scientists rely on supercomputers, the domain of expertise of High-Performance Computing. As the demand for computing power keeps growing, these machines must become ever more powerful. However, the reduction in transistor size predicted by Moore’s Law is no longer sufficient to drive the evolution of processors, the core of supercomputer power. Hence, these machines are becoming increasingly complex to answer this increasing demand. The performance of HPC applications depends on interactions between varied application behavior, a complex processor architecture, and the choices made by the software stack. As a result, optimizing applications’ performance on these machines is a tedious task. One solution to simplify optimization efforts and improve applications’ performance is to bring together all HPC actors in a codesign environment for designing future machines. In an environment where the interests of applications drive the choices made by constructors, the processors and software stack will be adapted to the needs of future users. It is all the more vital with the recent arrival of the Arm environment in HPC, already representing 10% total computing power of the Top500 with just six machines, because this environment offers manufacturers great freedom in their choice of processor characteristics. However, in such a codesign environment, it is mandatory to use a performance prediction approach that accounts for the impact of the choices made by all players to drive the design-space exploration. In this thesis, we implement a performance projection approach adapted to our definition of a codesign environment that groups the actors and aspects of application performance into three groups: the application, the software stack, and the hardware. This model takes the form of a three-step process for projecting an accessible application/software stack/source hardware triplet onto a future target triplet of interest, which is inaccessible. These steps are performance characterization of our three aspects, followed by performance analysis on the source triplet, which finally leads to a projection of performance towards the target triplet as a function of the differences between its parameters and those of the source triplet. Then, we implement this approach using a Roofline model representation, in which we focus on the maximum performance attainable by the triplets and project performance with an assumption of architectural efficiency conservation. We then use this model to analyze and explore hardware parameters such as hardware vector size and choice of memory type on different Arm core architectures. Finally, we extend this exploration to multi-core architectures by refining the characterization of the bandwidth and the workload of each core. Then, we use this extension for the exploration of application and software stack parameters on a future HPC architecture of interest: the EPI (European Processor Initiative) processor
Choi, Dongsoo. "Susannah." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78004.
Master of Fine Arts
Alwathainani, Abdulaziz. "Do Investors Over-react to Patterns of Past Financial Performance Measures?" VCU Scholars Compass, 2006. http://scholarscompass.vcu.edu/etd/756.
Trimeloni, Thomas. "Accelerating Finite State Projection through General Purpose Graphics Processing." VCU Scholars Compass, 2011. http://scholarscompass.vcu.edu/etd/175.
Saluru, Sarat K. "Projection of TaSiOx/In0.53Ga0.47As Tri-gate transistor performance for future Low-Power Electronic Applications." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78028.
Master of Science
Gasc, Thibault. "Modèles de performance pour l'adaptation des méthodes numériques aux architectures multi-coeurs vectorielles. Application aux schémas Lagrange-Projection en hydrodynamique compressible." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLN063/document.
This works are dedicated to hydrodynamics. For decades, numerous numerical methods has been developed to deal with this type of problems. However, both the evolution and the complexity of computing make us rethink or redesign our numerical solver in order to use efficiently massively parallel computers. Using performance modeling, we perform an analysis of a reference Lagrange-Remap solver in order to deeply understand its behavior on current supercomputer and to optimize its implementation. Thanks to the conclusions of this analysis, we derive a new numerical solver which by design has a better performance. We call it the Lagrange-Flux solver. The accuracy obtained with this solver is similar to the reference one. The derivation of this method also leads to rethink the Remap step
Книги з теми "Projection de performance":
Rees, A. L. Expanded cinema: Art, performance, film. London: Tate Gallery Pub., 2011.
1946-, Steeb Randall, United States Army, United States. Dept. of Defense. Office of the Secretary of Defense., Arroyo Center, National Defense Research Institute (U.S.), and Rand Corporation, eds. Rapid force projection technologies: Assessing the performance of advanced ground sensors. Santa Monica, CA (1700 Main Street, P.O. Box 2138, Santa Monica, 90407-2138): Rand, 2000.
Syngellakis, S. Projectile impact: Modelling techniques and target performance assessment. Southampton, Boston: WIT Press, 2014.
Gaethke-Brandt, Jane E. The effect of auditory subliminal deactivating messages on motor and task performance of hyperkinetic children. 1986.
Dobbins, Alison C. Projection Design for Theatre and Live Performance: Principles of Media Design. Taylor & Francis Group, 2021.
Dobbins, Alison C. Projection Design for Theatre and Live Performance: Principles of Media Design. Routledge, 2021.
Dobbins, Alison C. Projection Design for Theatre and Live Performance: Principles of Media Design. Taylor & Francis Group, 2021.
Dobbins, Alison C. Projection Design for Theatre and Live Performance: Principles of Media Design. Taylor & Francis Group, 2021.
Dobbins, Alison C. Projection Design for Theatre and Live Performance: Principles of Media Design. Routledge, 2021.
Soyres, Constance de, and Henry Mooney. Debt Sustainability Analyses for Low-Income Countries: An Assessment of Projection Performance. International Monetary Fund, 2017.
Частини книг з теми "Projection de performance":
Kononov, Yuri D. "The Effect of the Projection Time Frame on Projection Performance and Projection Performance Requirements." In Long-term Modeled Projections of the Energy Sector, 1–14. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30533-8_1.
Gavoille, Clément, Hugo Taboada, Patrick Carribault, Fabrice Dupros, Brice Goglin, and Emmanuel Jeannot. "Relative Performance Projection on Arm Architectures." In Euro-Par 2022: Parallel Processing, 85–99. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12597-3_6.
Garey, L. E., R. E. Shaw, and J. Zhang. "Parallel Projection Algorithms for Tridiagonal Toeplitz Systems." In High Performance Computing Systems and Applications, 75–86. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0288-3_15.
Lee, Jaewoon, Yeonjin Kim, Myeong-Hyeon Heo, Dongho Kim, and Byeong-Seok Shin. "Real-Time Projection Mapping for Performance Arts." In Computer Science and its Applications, 163–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-45402-2_24.
Fan, Shikun, Muzi Gao, and Yingfan Lu. "Projection of Intel’s Financial Performance in 2022." In Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022), 224–32. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-036-7_33.
Dobbins, Alison C. "Animatic." In Projection Design for Theatre and Live Performance, 72–82. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003137207-8.
Dobbins, Alison C. "Jargon." In Projection Design for Theatre and Live Performance, 105–12. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003137207-11.
Dobbins, Alison C. "Storyboard." In Projection Design for Theatre and Live Performance, 39–49. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003137207-5.
Dobbins, Alison C. "Introduction." In Projection Design for Theatre and Live Performance, 1–2. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003137207-1.
Dobbins, Alison C. "Cueing." In Projection Design for Theatre and Live Performance, 83–87. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003137207-9.
Тези доповідей конференцій з теми "Projection de performance":
Stearns, D. G. "High Performance Multilayer X-Ray Optics." In Soft X-Ray Projection Lithography. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/sxray.1991.wc2.
Gutman, Georgy, Kevin Parker, James L. Wood, and Richard Watts. "Multilayer Performance for Soft X-ray Schwarzchild Optics." In Soft X-Ray Projection Lithography. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/sxray.1992.tub4.
Viswanathan, V. K. "Practical Tolerancing and Performance Implications for XUV Projection Lithography Reduction Systems*." In Soft X-Ray Projection Lithography. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/sxray.1992.tua4.
Kortright, J. B., and R. Watts. "Multilayer Period Uniformity and Performance of Soft X-ray Imaging Systems." In Soft X-Ray Projection Lithography. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/sxray.1991.thb2.
Mansfield, W. M., O. R. Wood, J. E. Bjorkholm, J. Bokor, R. R. Freeman, A. A. MacDowell, L. H. Szeto, et al. "Effects of Absorption on Resist Performance in Soft X-Ray Projection Lithography." In Soft X-Ray Projection Lithography. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/sxray.1991.thd4.
Bijkerk, F., E. Louis, L. Shmaenok, H. J. Voorma, M. J. van der Wiel, R. Schlatmann, J. Verhoeven, et al. "Enhanced performance of KrF laser-induced x-ray sources and multilayer mirrors for soft x-ray projection lithography." In Soft X-Ray Projection Lithography. Washington, D.C.: Optica Publishing Group, 1993. http://dx.doi.org/10.1364/sxray.1993.wa.1.
Lin, Chun C., Tu-Yiin Chang, and Chie-Ching Lin. "Performance measurement of projection display." In Photonics China '96, edited by Eric G. Lean, Zhiren Tian, and Bao Gang Wu. SPIE, 1996. http://dx.doi.org/10.1117/12.253327.
Jones, Philip J., Akira Tomita, and Mark Wartenberg. "Performance of NCAP projection displays." In Medical Imaging '91, San Jose, CA, edited by Harry M. Assenheim, Richard A. Flasck, Thomas M. Lippert, and Jerry Bentz. SPIE, 1991. http://dx.doi.org/10.1117/12.45414.
Tsuji, Miwako, William T. C. Kramer, and Mitsuhisa Sato. "A Performance Projection of Mini-Applications onto Benchmarks Toward the Performance Projection of Real-Applications." In 2017 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2017. http://dx.doi.org/10.1109/cluster.2017.123.
Viswanathan, V. K., and Brian E. Newnam. "Development of Reflective Optical Systems for XUV Projection Lithography*." In Soft X-Ray Projection Lithography. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/sxray.1991.fb2.
Звіти організацій з теми "Projection de performance":
Brailsford, D., M. Brunetti, Saul Alonso Monsalve, A. Blake, Andy Chappell, J. Marshall, L. Whitehead, and E. Worcester. Reconstruction performance studies for liquid argon time projection chambers with two and three readout planes. Office of Scientific and Technical Information (OSTI), January 2021. http://dx.doi.org/10.2172/1826741.
Roberts, Benedict C., Charles Noll, Jeffrey J. Hobbs, Edward Dawson, and Robert Greiner. An Analysis of the Requirements Levels and Performance Projection Modules of the Corporate Information Management Requirements System. Fort Belvoir, VA: Defense Technical Information Center, October 1994. http://dx.doi.org/10.21236/ada285766.
Carrasquilla Barrera, Alberto, Arturo José Galindo Andrade, Gerardo Alfredo Hernández Correa, Ana Fernanda Maiguashca Olano, Carolina Soto Losada, Roberto Steiner Sampedro, and Juan José Echavarría Soto. Report of the Board of Directors to the Congress of Colombia - March 2020. Banco de la República de Colombia, March 2020. http://dx.doi.org/10.32468/inf-jun-dir-con-rep-eng.03-2020.
PF Baldasaro, MW Dashiell, JE Oppenlander, JL Vell, P Fourspring, K Rahner, LR Danielson, S Burger, and E Brown. System Performance Projections for TPV Energy Conversion. Office of Scientific and Technical Information (OSTI), June 2004. http://dx.doi.org/10.2172/837457.
Majeski, R., L. Berzak, T. Gray, R. Kaita, T. Kozub, F. Levinton, D. P. Lundberg, et al. Performance Projections For The Lithium Tokamak Experiment (LTX). Office of Scientific and Technical Information (OSTI), June 2009. http://dx.doi.org/10.2172/958400.
Celina, Mathias C., Nicholas Henry Giron, and Adam Quintana. Aging Behavior and Performance Projections for a Polysulfide Elastomer. Office of Scientific and Technical Information (OSTI), May 2015. http://dx.doi.org/10.2172/1183359.
Bhatele, A., P. Bremer, T. Gamblin, and M. Schulz. Intuitive visualizations through multi-domain projections for performance analysis at scale. Office of Scientific and Technical Information (OSTI), March 2012. http://dx.doi.org/10.2172/1090833.
Leptinsky, Sarah, Tommy Schmitt, Alex Zoelle, Sally Homsy, Mark Woods, Travis Shultz, Jeff Hoffmann, and Gregory Hackett. Cost and Performance Projections for Coal- and Natural Gas-Fired Power Plants. Office of Scientific and Technical Information (OSTI), May 2023. http://dx.doi.org/10.2172/1988750.
Ruosteenoja, Kimmo. Applicability of CMIP6 models for building climate projections for northern Europe. Finnish Meteorological Institute, September 2021. http://dx.doi.org/10.35614/isbn.9789523361416.
Jadun, Paige, Colin McMillan, Daniel Steinberg, Matteo Muratori, Laura Vimmerstedt, and Trieu Mai. Electrification Futures Study: End-Use Electric Technology Cost and Performance Projections through 2050. Office of Scientific and Technical Information (OSTI), December 2017. http://dx.doi.org/10.2172/1416113.