Academic literature on the topic 'High performance scientific computing'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'High performance scientific computing.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "High performance scientific computing"
Camp, William J., and Philippe Thierry. "Trends for high-performance scientific computing." Leading Edge 29, no. 1 (January 2010): 44–47. http://dx.doi.org/10.1190/1.3284052.
Full textKisel, Ivan. "Scientific and high-performance computing at FAIR." EPJ Web of Conferences 95 (2015): 01007. http://dx.doi.org/10.1051/epjconf/20159501007.
Full textFosdick, Lloyd D., Elizabeth R. Jessup, Carolyn J. C. Schauble, Gitta Domik, and Ralph L. Place. "An Introduction to High‐Performance Scientific Computing." Physics Today 49, no. 12 (December 1996): 55–56. http://dx.doi.org/10.1063/1.881590.
Full textBiryaltsev, Eugeniy Vasiljevich, Marat Razifovich Galimov, Denis Evgenievich Demidov, and Aleksandr Mikhailovich Elizarov. "The platform approach to research and development using high-performance computing." Program Systems: Theory and Applications 10, no. 2 (2019): 93–119. http://dx.doi.org/10.25209/2079-3316-2019-10-2-93-119.
Full textBernholdt, David E., Benjamin A. Allan, Robert Armstrong, Felipe Bertrand, Kenneth Chiu, Tamara L. Dahlgren, Kostadin Damevski, et al. "A Component Architecture for High-Performance Scientific Computing." International Journal of High Performance Computing Applications 20, no. 2 (May 2006): 163–202. http://dx.doi.org/10.1177/1094342006064488.
Full textKurzak, Jakub, Alfredo Buttari, Piotr Luszczek, and Jack Dongarra. "The PlayStation 3 for High-Performance Scientific Computing." Computing in Science & Engineering 10, no. 3 (May 2008): 84–87. http://dx.doi.org/10.1109/mcse.2008.85.
Full textAlexeev, Yuri, Benjamin A. Allan, Robert C. Armstrong, David E. Bernholdt, Tamara L. Dahlgren, Dennis Gannon, Curtis L. Janssen, et al. "Component-based software for high-performance scientific computing." Journal of Physics: Conference Series 16 (January 1, 2005): 536–40. http://dx.doi.org/10.1088/1742-6596/16/1/073.
Full textDavis, Kei, and Jöerg Striegnitz. "Parallel/High Performance Object-Oriented Scientific Computing 2008." International Journal of Parallel, Emergent and Distributed Systems 24, no. 6 (December 2009): 463–65. http://dx.doi.org/10.1080/17445760902758529.
Full textPonce, Marcelo, Erik Spence, Ramses van Zon, and Daniel Gruner. "Scientific Computing, High-Performance Computing and Data Science in Higher Education." Journal of Computational Science Education 10, no. 1 (January 2019): 24–31. http://dx.doi.org/10.22369/issn.2153-4136/10/1/5.
Full textBoulle, A., and J. Kieffer. "High-performance Python for crystallographic computing." Journal of Applied Crystallography 52, no. 4 (July 24, 2019): 882–97. http://dx.doi.org/10.1107/s1600576719008471.
Full textDissertations / Theses on the topic "High performance scientific computing"
Balakrishnan, Suresh Reuben A/L. "Hybrid High Performance Computing (HPC) + Cloud for Scientific Computing." Thesis, Curtin University, 2022. http://hdl.handle.net/20.500.11937/89123.
Full textBentz, Jonathan Lee. "Hybrid programming in high performance scientific computing." [Ames, Iowa : Iowa State University], 2006.
Find full textCalatrava, Arroyo Amanda. "High Performance Scientific Computing over Hybrid Cloud Platforms." Doctoral thesis, Universitat Politècnica de València, 2016. http://hdl.handle.net/10251/75265.
Full textLas aplicaciones científicas generalmente precisan grandes requisitos de cómputo, memoria y gestión de datos para su ejecución. Este tipo de aplicaciones tradicionalmente ha empleado recursos de altas prestaciones, como supercomputadores de memoria compartida, clústers de PCs de memoria distribuida, o recursos provenientes de infraestructuras Grid, sobre los que se adaptaba la aplicación para que se ejecutara satisfactoriamente. El auge que han tenido las técnicas de virtualización en los últimos años, propiciando la aparición de la computación en la nube (Cloud Computing), ha provocado un importante cambio en la forma de ejecutar este tipo de aplicaciones. Sin embargo, la gestión de la ejecución de aplicaciones científicas sobre plataformas de computación elásticas de altas prestaciones no es una tarea trivial. En esta tesis doctoral se ha desarrollado Elastic Cloud Computing Cluster (EC3), una herramienta de código abierto capaz de llevar a cabo la ejecución de aplicaciones científicas de altas prestaciones creando para ello clústers virtuales, híbridos y elásticos, autogestionados y eficientes en cuanto a costes, sobre plataformas Cloud de tipo Infraestructura como Servicio (IaaS). Estos clústers autogestionados tienen la capacidad de adaptar su tamaño, es decir, el número de nodos, a la carga de trabajo, creando así la ilusión de un clúster real sin requerir una inversión por encima del uso actual. Además, son completamente configurables y pueden ser migrados de un proveedor a otro de manera automática y transparente a los usuarios y trabajos en ejecución en el cluster. EC3 también permite desplegar clústers híbridos sobre recursos Cloud públicos y privados, donde los recursos privados son complementados con recursos Cloud públicos para acelerar el proceso de ejecución. Otras configuraciones híbridas, como el empleo de diferentes tipos de instancias y el uso de instancias puntuales combinado con instancias bajo demanda son también soportadas por EC3. Además, el uso de instancias puntuales junto con técnicas de checkpointing permite a EC3 reducir significantemente el coste total de las ejecuciones a la vez que proporciona tolerancia a fallos. EC3 está concebido para facilitar el uso de clústers virtuales a los usuarios, que, aunque no tengan un conocimiento extenso sobre este tipo de tecnologías, pueden beneficiarse fácilmente de ellas. Por ello, la herramienta ofrece dos interfaces diferentes a sus usuarios, una interfaz web donde se expone EC3 como servicio para usuarios no experimentados y una potente interfaz de línea de comandos. Además, esta tesis doctoral se adentra en el campo de la virtualización ligera, mediante el uso de contenedores como alternativa a la solución tradicional de virtualización basada en máquinas virtuales. Este estudio analiza el escenario propicio para el uso de contenedores y propone una arquitectura para el despliegue de clusters virtuales elásticos basados en esta tecnología. Finalmente, para demostrar la funcionalidad y ventajas de las herramientas desarrolladas durante esta tesis, esta memoria recoge varios casos de uso que abarcan diferentes escenarios y campos de conocimiento, como estudios estructurales de edificios, astrofísica o biodiversidad.
Les aplicacions científiques generalment precisen grans requisits de còmput, de memòria i de gestió de dades per a la seua execució. Este tipus d'aplicacions tradicionalment hi ha empleat recursos d'altes prestacions, com supercomputadors de memòria compartida, clústers de PCs de memòria distribuïda, o recursos provinents d'infraestructures Grid, sobre els quals s'adaptava l'aplicació perquè s'executara satisfactòriament. L'auge que han tingut les tècniques de virtualitzaciò en els últims anys, propiciant l'aparició de la computació en el núvol (Cloud Computing), ha provocat un important canvi en la forma d'executar este tipus d'aplicacions. No obstant això, la gestió de l'execució d'aplicacions científiques sobre plataformes de computació elàstiques d'altes prestacions no és una tasca trivial. En esta tesi doctoral s'ha desenvolupat Elastic Cloud Computing Cluster (EC3), una ferramenta de codi lliure capaç de dur a terme l'execució d'aplicacions científiques d'altes prestacions creant per a això clústers virtuals, híbrids i elàstics, autogestionats i eficients quant a costos, sobre plataformes Cloud de tipus Infraestructura com a Servici (IaaS). Estos clústers autogestionats tenen la capacitat d'adaptar la seua grandària, es dir, el nombre de nodes, a la càrrega de treball, creant així la il·lusió d'un cluster real sense requerir una inversió per damunt de l'ús actual. A més, són completament configurables i poden ser migrats d'un proveïdor a un altre de forma automàtica i transparent als usuaris i treballs en execució en el cluster. EC3 també permet desplegar clústers híbrids sobre recursos Cloud públics i privats, on els recursos privats són complementats amb recursos Cloud públics per a accelerar el procés d'execució. Altres configuracions híbrides, com l'us de diferents tipus d'instàncies i l'ús d'instàncies puntuals combinat amb instàncies baix demanda són també suportades per EC3. A més, l'ús d'instàncies puntuals junt amb tècniques de checkpointing permet a EC3 reduir significantment el cost total de les execucions al mateix temps que proporciona tolerància a fallades. EC3e stà concebut per a facilitar l'ús de clústers virtuals als usuaris, que, encara que no tinguen un coneixement extensiu sobre este tipus de tecnologies, poden beneficiar-se fàcilment d'elles. Per això, la ferramenta oferix dos interfícies diferents dels seus usuaris, una interfície web on s'exposa EC3 com a servici per a usuaris no experimentats i una potent interfície de línia d'ordres. A més, esta tesi doctoral s'endinsa en el camp de la virtualitzaciò lleugera, per mitjà de l'ús de contenidors com a alternativa a la solució tradicional de virtualitzaciò basada en màquines virtuals. Este estudi analitza l'escenari propici per a l'ús de contenidors i proposa una arquitectura per al desplegament de clusters virtuals elàstics basats en esta tecnologia. Finalment, per a demostrar la funcionalitat i avantatges de les ferramentes desenrotllades durant esta tesi, esta memòria arreplega diversos casos d'ús que comprenen diferents escenaris i camps de coneixement, com a estudis estructurals d'edificis, astrofísica o biodiversitat.
Calatrava Arroyo, A. (2016). High Performance Scientific Computing over Hybrid Cloud Platforms [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/75265
TESIS
Agarwal, Dinesh. "Scientific High Performance Computing (HPC) Applications On The Azure Cloud Platform." Digital Archive @ GSU, 2013. http://digitalarchive.gsu.edu/cs_diss/75.
Full textGulabani, Teena Pratap. "Development of high performance scientific components for interoperability of computing packages." [Ames, Iowa : Iowa State University], 2008.
Find full textKaplan, Ali. "Collaborative framework for high-performance p2p-based data transfer in scientific computing." [Bloomington, Ind.] : Indiana University, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3380091.
Full textTitle from PDF t.p. (viewed on Jul 19, 2010). Source: Dissertation Abstracts International, Volume: 70-12, Section: B, page: 7668. Adviser: Geoffrey C. Fox.
Steven, Monteiro Steena Dominica. "Statistical Techniques to Model and Optimize Performance of Scientific, Numerically Intensive Workloads." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/5228.
Full textLin, Tien-Ju. "Web-based front-end design and scientific computing for material stress simulation software." Thesis, Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53101.
Full textKrishnan, Manoj Kumar. "ProLAS a novel dynamic load balancing library for advanced scientific computing /." Master's thesis, Mississippi State : Mississippi State University, 2003. http://library.msstate.edu/etd/show.asp?etd=etd-11102003-184622.
Full textMalenta, Mateusz. "Exploring the dynamic radio sky with many-core high-performance computing." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/exploring-the-dynamic-radio-sky-with-manycore-highperformance-computing(fe86c963-e253-48c0-a907-f8b59c44cf53).html.
Full textBooks on the topic "High performance scientific computing"
Di Napoli, Edoardo, Marc-André Hermanns, Hristo Iliev, Andreas Lintermann, and Alexander Peyser, eds. High-Performance Scientific Computing. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53862-4.
Full textBerry, Michael W., Kyle A. Gallivan, Efstratios Gallopoulos, Ananth Grama, Bernard Philippe, Yousef Saad, and Faisal Saied, eds. High-Performance Scientific Computing. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5.
Full textBreuer, Michael, Franz Durst, and Christoph Zenger, eds. High Performance Scientific And Engineering Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-55919-8.
Full textBungartz, Hans-Joachim, Franz Durst, and Christoph Zenger, eds. High Performance Scientific and Engineering Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60155-2.
Full textYang, Laurence Tianruo, and Yi Pan, eds. High Performance Scientific and Engineering Computing. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4757-5402-5.
Full textChopp, David L. Introduction to High Performance Scientific Computing. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2019. http://dx.doi.org/10.1137/1.9781611975642.
Full textBerry, Michael W. High-Performance Scientific Computing: Algorithms and Applications. London: Springer London, 2012.
Find full textAn Introduction to high-performance scientific computing. Cambridge, Mass: MIT Press, 1996.
Find full textGentzsch, Wolfgang. High speed and large scale scientific computing. Amsterdam: IOS Press, 2009.
Find full textGentzsch, Wolfgang. High speed and large scale scientific computing. Amsterdam: IOS Press, 2009.
Find full textBook chapters on the topic "High performance scientific computing"
Jalby, William, David C. Wong, David J. Kuck, Jean-Thomas Acquaviva, and Jean-Christophe Beyler. "Measuring Computer Performance." In High-Performance Scientific Computing, 75–95. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5_3.
Full textAmman, H. M. "High Performance Computing in Economics." In Scientific Computing on Supercomputers, 235–41. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0819-5_12.
Full textMcBryan, Oliver A. "Limiting factors in high performance computing." In Parallel Scientific Computing, 362–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/bfb0030165.
Full textGallivan, Kyle A., Efstratios Gallopoulos, Ananth Grama, Bernard Philippe, Eric Polizzi, Yousef Saad, Faisal Saied, and Danny Sorensen. "Parallel Numerical Computing from Illiac IV to Exascale—The Contributions of Ahmed H. Sameh." In High-Performance Scientific Computing, 1–44. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5_1.
Full textXia, Jianlin. "Robust and Efficient Multifrontal Solver for Large Discretized PDEs." In High-Performance Scientific Computing, 199–217. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5_10.
Full textBaggag, Abdelkader. "A Preconditioned Scheme for Nonsymmetric Saddle-Point Problems." In High-Performance Scientific Computing, 219–50. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5_11.
Full textKilic, Sami A. "Effect of Ordering for Iterative Solvers in Structural Mechanics Problems." In High-Performance Scientific Computing, 251–60. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5_12.
Full textBaker, Allison H., Robert D. Falgout, Tzanio V. Kolev, and Ulrike Meier Yang. "Scaling Hypre’s Multigrid Solvers to 100,000 Cores." In High-Performance Scientific Computing, 261–79. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5_13.
Full textGallivan, Kyle A., Chunhong Qi, and P. A. Absil. "A Riemannian Dennis-Moré Condition." In High-Performance Scientific Computing, 281–93. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5_14.
Full textWang, Mu, and Xiaoge Wang. "A Jump-Start of Non-negative Least Squares Solvers." In High-Performance Scientific Computing, 295–310. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2437-5_15.
Full textConference papers on the topic "High performance scientific computing"
Kenyon, Connor, and Collin Capano. "Apple Silicon Performance in Scientific Computing." In 2022 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2022. http://dx.doi.org/10.1109/hpec55821.2022.9926315.
Full textHazelhurst, Scott. "Scientific computing using virtual high-performance computing." In the 2008 annual research conference of the South African Institute of Computer Scientists and Information Technologists. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1456659.1456671.
Full textNoack, Matthias. "OpenCL in Scientific High Performance Computing." In IWOCL 2017: 5th International Workshop on OpenCL. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3078155.3078170.
Full textButler, David M. "Scientific Computing Doesn't Need noSQL." In 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC). IEEE, 2012. http://dx.doi.org/10.1109/sc.companion.2012.158.
Full textHiggins, Joshua, Violeta Holmes, and Colin Venters. "Securing user defined containers for scientific computing." In 2016 International Conference on High Performance Computing & Simulation (HPCS). IEEE, 2016. http://dx.doi.org/10.1109/hpcsim.2016.7568369.
Full textVolkema, Glenn, and Gaurav Khanna. "Scientific computing using consumer video-gaming embedded devices." In 2017 IEEE High-Performance Extreme Computing Conference (HPEC). IEEE, 2017. http://dx.doi.org/10.1109/hpec.2017.8091055.
Full textKenyon, Connor, Glenn Volkema, and Gaurav Khanna. "Overcoming Limitations of GPGPU-Computing in Scientific Applications." In 2019 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2019. http://dx.doi.org/10.1109/hpec.2019.8916330.
Full textColonnelli, I., and M. Aldinucci. "HPC07 - Hybrid Workflows For Large - Scale Scientific Applications." In Sixth EAGE High Performance Computing Workshop. European Association of Geoscientists & Engineers, 2022. http://dx.doi.org/10.3997/2214-4609.2022615029.
Full textShirun Ho, S. Itoh, S. Ihara, and R. D. Schlichting. "Agent Middleware for Heterogeneous Scientific Simulations." In SC98 - High Performance Networking and Computing Conference. IEEE, 1998. http://dx.doi.org/10.1109/sc.1998.10014.
Full textBassetti, F., D. Brown, K. Davis, W. Henshaw, and Dan Quinlan. "OVERTURE: An Object-Oriented Framework for High Performance Scientific Computing." In SC98 - High Performance Networking and Computing Conference. IEEE, 1998. http://dx.doi.org/10.1109/sc.1998.10013.
Full textReports on the topic "High performance scientific computing"
Jin, Yier. Resilient and Robust High Performance Computing Platforms for Scientific Computing Integrity. Office of Scientific and Technical Information (OSTI), July 2017. http://dx.doi.org/10.2172/1393914.
Full textGulabani, Teena Pratap. Development of high performance scientific components for interoperability of computing packages. Office of Scientific and Technical Information (OSTI), January 2008. http://dx.doi.org/10.2172/964389.
Full textAntypas, Katie, Jeffrey Broughton, Shane Canon, Nicholas Cardo, Jim Craw, Brent Draney, William Fortney, et al. NERSC 2011: High Performance Computing Facility Operational Assessment for the National Energy Research Scientific Computing Center. Office of Scientific and Technical Information (OSTI), May 2012. http://dx.doi.org/10.2172/1183198.
Full textBergman, Keren, Tom Conte, Al Gara, Maya Gokhale, Mike Heroux, Peter Kogge, Bob Lucas, Satoshi Matsuoka, Vivek Sarkar, and Olivier Temam. Future High Performance Computing Capabilities: Summary Report of the Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee. Office of Scientific and Technical Information (OSTI), March 2019. http://dx.doi.org/10.2172/1570693.
Full textKhaleel, Mohammad A. Scientific Grand Challenges: Forefront Questions in Nuclear Science and the Role of High Performance Computing. Office of Scientific and Technical Information (OSTI), October 2009. http://dx.doi.org/10.2172/968204.
Full textGerber, Richard, William Allcock, Chris Beggio, Stuart Campbell, Andrew Cherry, Shreyas Cholia, Eli Dart, et al. DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities. Office of Scientific and Technical Information (OSTI), October 2014. http://dx.doi.org/10.2172/1163236.
Full textKendall, Richard P., Douglass E. Post, Jeffrey C. Carver, Dale B. Henderson, and David A. Fisher. A Proposed Taxonomy for Software Development Risks for High-Performance Computing (HPC) Scientific/Engineering Applications. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada468594.
Full textHittinger, J. LLNL Response to the DOE ASCR RFI, "Stewardship of Software for Scientific and High-Performance Computing". Office of Scientific and Technical Information (OSTI), December 2021. http://dx.doi.org/10.2172/1835687.
Full textFinkel, Hal, Ben Brown, Robinson Pino, Saswata Hier-Majumder, and Bill Spotz. Responses to the Request for Information on Stewardship of Software for Scientific and High-Performance Computing. Office of Scientific and Technical Information (OSTI), December 2021. http://dx.doi.org/10.2172/1843576.
Full textRangaswami, Raju. Department of Energy Project ER25739 Final Report QoS-Enabled, High-performance Storage Systems for Data-Intensive Scientific Computing. Office of Scientific and Technical Information (OSTI), May 2009. http://dx.doi.org/10.2172/1046919.
Full text