Academic literature on the topic 'Exascale systems'
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Journal articles on the topic "Exascale systems"
Coteus, P. W., J. U. Knickerbocker, C. H. Lam, and Y. A. Vlasov. "Technologies for exascale systems." IBM Journal of Research and Development 55, no. 5 (September 2011): 14:1–14:12. http://dx.doi.org/10.1147/jrd.2011.2163967.
Full textRumley, Sebastien, Dessislava Nikolova, Robert Hendry, Qi Li, David Calhoun, and Keren Bergman. "Silicon Photonics for Exascale Systems." Journal of Lightwave Technology 33, no. 3 (February 1, 2015): 547–62. http://dx.doi.org/10.1109/jlt.2014.2363947.
Full textJensen, David, and Arun Rodrigues. "Embedded Systems and Exascale Computing." Computing in Science & Engineering 12, no. 6 (November 2010): 20–29. http://dx.doi.org/10.1109/mcse.2010.95.
Full textTahmazli-Khaligova, Firuza. "CHALLENGES OF USING BIG DATA IN DISTRIBUTED EXASCALE SYSTEMS." Azerbaijan Journal of High Performance Computing 3, no. 2 (December 29, 2020): 245–54. http://dx.doi.org/10.32010/26166127.2020.3.2.245.254.
Full textAlexander, Francis J., James Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, et al. "Co-design Center for Exascale Machine Learning Technologies (ExaLearn)." International Journal of High Performance Computing Applications 35, no. 6 (September 27, 2021): 598–616. http://dx.doi.org/10.1177/10943420211029302.
Full textIsmayilova, Nigar. "CHALLENGES OF USING THE FUZZY APPROACH IN EXASCALE COMPUTING SYSTEMS." Azerbaijan Journal of High Performance Computing 4, no. 2 (December 31, 2021): 198–205. http://dx.doi.org/10.32010/26166127.2021.4.2.198.205.
Full textKlasky, S. A., H. Abbasi, M. Ainsworth, J. Choi, M. Curry, T. Kurc, Q. Liu, et al. "Exascale Storage Systems the SIRIUS Way." Journal of Physics: Conference Series 759 (October 2016): 012095. http://dx.doi.org/10.1088/1742-6596/759/1/012095.
Full textСтепаненко, Сергей, Sergey Stepanenko, Василий Южаков, and Vasiliy Yuzhakov. "Exascale supercomputers. Architectural outlines." Program systems: theory and applications 4, no. 4 (November 15, 2013): 61–90. http://dx.doi.org/10.12737/2418.
Full textAbdullayev, Fakhraddin. "RESOURCE DISCOVERY IN DISTRIBUTED EXASCALE SYSTEMS USING A MULTI-AGENT MODEL: CATEGORIZATION OF AGENTS BASED ON THEIR CHARACTERISTICS." Azerbaijan Journal of High Performance Computing 6, no. 1 (June 30, 2023): 113–20. http://dx.doi.org/10.32010/26166127.2023.6.1.113.120.
Full textShalf, John, Dan Quinlan, and Curtis Janssen. "Rethinking Hardware-Software Codesign for Exascale Systems." Computer 44, no. 11 (November 2011): 22–30. http://dx.doi.org/10.1109/mc.2011.300.
Full textDissertations / Theses on the topic "Exascale systems"
Deveci, Mehmet. "Load-Balancing and Task Mapping for Exascale Systems." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1429199721.
Full textBentria, Dounia. "Combining checkpointing and other resilience mechanisms for exascale systems." Thesis, Lyon, École normale supérieure, 2014. http://www.theses.fr/2014ENSL0971/document.
Full textIn this thesis, we are interested in scheduling and optimization problems in probabilistic contexts. The contributions of this thesis come in two parts. The first part is dedicated to the optimization of different fault-Tolerance mechanisms for very large scale machines that are subject to a probability of failure and the second part is devoted to the optimization of the expected sensor data acquisition cost when evaluating a query expressed as a tree of disjunctive Boolean operators applied to Boolean predicates. In the first chapter, we present the related work of the first part and then we introduce some new general results that are useful for resilience on exascale systems.In the second chapter, we study a unified model for several well-Known checkpoint/restart protocols. The proposed model is generic enough to encompass both extremes of the checkpoint/restart space, from coordinated approaches to a variety of uncoordinated checkpoint strategies. We propose a detailed analysis of several scenarios, including some of the most powerful currently available HPC platforms, as well as anticipated exascale designs.In the third, fourth, and fifth chapters, we study the combination of different fault tolerant mechanisms (replication, fault prediction and detection of silent errors) with the traditional checkpoint/restart mechanism. We evaluated several models using simulations. Our results show that these models are useful for a set of models of applications in the context of future exascale systems.In the second part of the thesis, we study the problem of minimizing the expected sensor data acquisition cost when evaluating a query expressed as a tree of disjunctive Boolean operators applied to Boolean predicates. The problem is to determine the order in which predicates should be evaluated so as to shortcut part of the query evaluation and minimize the expected cost.In the sixth chapter, we present the related work of the second part and in the seventh chapter, we study the problem for queries expressed as a disjunctive normal form. We consider the more general case where each data stream can appear in multiple predicates and we consider two models, the model where each predicate can access a single stream and the model where each predicate can access multiple streams
Shalf, John Marshall. "Advanced System-Scale and Chip-Scale Interconnection Networks for Ultrascale Systems." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/36134.
Full textMaster of Science
Maroñas, Marcos. "On the design and development of programming models for exascale systems." Doctoral thesis, Universitat Politècnica de Catalunya, 2021. http://hdl.handle.net/10803/671783.
Full textLos supercomputadores han ido evolucionando a lo largo del tiempo para adaptarse a las necesidades de la comunidad científica. Actualmente, nos acercamos a la era Exascale. Los sistemas Exascale incorporarán un número de nodos enorme. Además, cada uno de esos nodos contendrá una gran cantidad de recursos computacionales. También la jerarquía de memoria se está volviendo más profunda y compleja. En conjunto, los sistemas Exascale plantearán varios desafíos en términos de rendimiento, programabilidad y tolerancia a fallos. Respecto a la programabilidad, cuánto más compleja es la arquitectura de un sistema, más difícil es aprovechar sus recursos de forma adecuada. La programabilidad está íntimamente ligada al rendimiento, ya que por mucho rendimiento que un sistema pueda ofrecer, no sirve de nada si nadie es capaz de conseguir ese rendimiento porque es demasiado difícil de usar. Esto refuerza la importancia de los modelos de programación como herramientas para desarrollar programas que puedan aprovechar al máximo estos sistemas de forma sencilla. Por último, es bien sabido que tener más componentes conlleva más errores. La combinación de ejecuciones muy largas y un tiempo medio hasta el fallo (MTTF) bajo ponen en peligro el progreso de las aplicaciones. Así pues, todos los esfuerzos realizados para mejorar el rendimiento son nulos si las aplicaciones difícilmente terminan. Para evitar esto, debemos desarrollar tolerancia a fallos. El objetivo principal de esta tesis es permitir que usuarios no expertos puedan aprovechar de forma óptima los complejos sistemas Exascale. Para ello, hemos mejorado algunos de los modelos de programación paralela más punteros para que puedan enfrentarse a tres desafíos clave de los sistemas Exascale: programabilidad, rendimiento y tolerancia a fallos. El primer conjunto de contribuciones de esta tesis se centra en la gestión eficiente de procesadores multicore/manycore. Proponemos un nuevo tipo de tarea que combina los puntos clave de las tareas con los de las técnicas de worksharing. Este nuevo tipo de tarea permite aliviar los problemas de granularidad, mejorando el rendimiento en algunos escenarios. También proponemos la introducción de dependencias en la directiva taskloop, de forma que los programadores puedan aplicar blocking de forma sencilla. Finalmente, extendemos la directiva taskloop para que pueda crear nuestro nuevo tipo de tareas, además de las tareas normales. El segundo conjunto de contribuciones está enfocado a la gestión eficiente de jerarquías de memoria modernas, centrado en entornos NUMA. Usando la información de las dependencias que anota el usuario, hemos construido un sistema que guarda la ubicación de los datos. Después, con esa información, decidimos dónde ejecutar el trabajo para maximizar la localidad de datos. El último conjunto de contribuciones se centra en tolerancia a fallos. Proponemos un modelo de programación que ofrece checkpoint/restart a nivel de aplicación, de forma sencilla y portable. Nuestro modelo ofrece una serie de directivas de compilador que permiten al usuario abstraerse de los detalles del sistema. Además, gestionamos librerías punteras en tolerancia a fallos para conseguir un alto rendimiento, incluyendo varios niveles y tipos de redundancia.
Subasi, Omer. "Reliability for exascale computing : system modelling and error mitigation for task-parallel HPC applications." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/397670.
Full textA medida que los Sistemas de Cómputo de Alto rendimiento (HPC por sus siglas en inglés) siguen creciendo, también las tasas de fallos aumentan. Las aplicaciones que se ejecutan en estos sistemas tienen una tasa de fallos que pueden estar en el orden de horas o días. Además, algunos estudios predicen que los fallos estarán en el orden de minutos en los Sistemas Exascale. Por lo tanto, son necesarias soluciones eficientes para la tolerancia a fallos que puedan tolerar fallos frecuentes. Las soluciones para tolerancia a fallos en los Sistemas futuros de HPC y Exascale tienen que ser de bajo costo, eficientes y altamente escalable. El sobrecosto en la ejecución sin fallos debe ser bajo y también se debe proporcionar reinicio rápido, ya que se espera que las aplicaciones de larga duración experimenten muchos fallos durante la ejecución. Por otra parte, los modelos de programación paralelas basados en tareas ordenadas de acuerdo a sus dependencias de datos, se están convirtiendo en un paradigma popular en aplicaciones HPC a gran escala. Por ejemplo, los siguientes modelos de programación paralela incluyen este tipo de modelo de programación OpenMP 4.0, OmpSs, Argobots e Intel Threading Building Blocks. En esta tesis proponemos soluciones de tolerancia a fallos para aplicaciones de HPC programadas en un modelo de programación paralelo basado tareas. Específicamente, en primer lugar, diseñamos e implementamos mecanismos “checkpoint/restart” y “message-logging” para recuperarse de los errores. Para investigar los beneficios de nuestras herramientas a nivel de tarea cuando se integra con los “system-wide checkpointing” se han desarrollado modelos de rendimiento. Por otra parte, diseñamos e implementamos mecanismos de replicación selectiva de tareas que permiten detectar y recuperarse de daños de datos silenciosos en aplicaciones programadas siguiendo el modelo de programación paralela basadas en tareas. Por último, se introduce un esquema de codificación que funciona en tiempo de ejecución para detectar y recuperarse de los errores de la memoria en estas aplicaciones. Todos los esquemas propuestos, en conjunto, proporcionan una cobertura bastante alta a los fallos tanto si estos se producen el cálculo o en la memoria.
Gkikas, Nikolaos. "Data Transfer and Management through the IKAROS framework : Adopting an asynchronous non-blocking event driven approach to implement the Elastic-Transfer's IMAP client-server connection." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166740.
Full textGivet det nuvarande läget för input/output (I/O) och lagringsenheter för system i peta-skala, skulle inkrementella lösningar bli ineffektiva om de implementerades i exa-skalamiljöer. Enligt ”The International Exascale Software Roadmap”, av Dongarra et al., är nuvarande I/O-arkitekturer inte tillräckligt skalbara, särskilt eftersom nuvarande delade filsystem har begränsningar när de används i storskaliga miljöer. Dessa begränsningar är: Bandbredd skalar inte på ett ekonomiskt sätt i storskaliga system, I/O-trafik på höghastighetsnätverk kan ha påverkan på och blir påverkad av andra orelaterade jobb, och I/O-trafik på lagringsservern kan ha påverkan på och bli påverkad av andra orelaterade jobb. Framtida applikationer på exa-skaladatorer kommer kräva I/O-bandbredd proportionellt till deras beräkningskapacitet. För att undvika dessa begränsningar föreslog C. Filippidis, C. Markou och Y. Cotronis ramverket IKAROS. I detta examensarbete utökas funktionaliteten hos den publikt tillgängliga modulen elastic-transfer (eT) som framtagits utifrån IKAROS. Den befintliga versionen av eT-ramverket implementerar Internet Message Access Protocol (IMAP) klient-serverkommunikation genom modulen ”Inbox” från Node Package Manager (NPM) ur Node.js programmeringsspråk. Denna modul användes som ett koncepttest, men i en verklig miljö så underminerar denna implementation systemets skalbarhet när ett stort antal värdar ansluter till systemet. Varje klient begär individuellt information relaterad till systemets metadata från IMAP-servern, vilket leder till en ineffektiv allokering av systemets resurser när ett stort antal värdar är samtidigt anslutna till eT-ramverket. Denna uppsats löser problemet genom att använda ett asynkront, icke-blockerande och händelsedrivet tillvägagångssätt för att implementera en IMAP klient-serveranslutning. Detta görs genom att integrera och modifiera NPM:s ”Imap”-modul, tagen från NPM:s katalog, så att den passar eT-ramverket. Eftersom formatet JavaScript Object Notation (JSON) har blivit ett av de mest spridda formaten för datautbyte så modifieras även eT:s metadata-struktur för att göra systemets metadata enkelt att omvandla till JSON-objekt. Denna funktionalitet ger ett bredare kompatibilitet och interoperabilitet med externa system. Utvärdering och tester av den nya modulens operationella beteende utfördes genom en serie dataöverföringsexperiment i en wide area network-miljö. Dessa experiment genomfördes för att få bekräftat att förändringarna i systemets arkitektur inte påverkade dess prestanda.
Mirtaheri, Seyedeh Leili, and Lucio Grandinetti. "Optimized dynamic load balancing in distributed exascale computing systems." Thesis, 2016. http://hdl.handle.net/10955/1370.
Full textThe dynamic nature of new generation scientific problems needs undergoing review in the traditional and static management of computing resources in Exascale computing systems. Doing so will support dynamic and unpredictable requests of the scientific programs for different type of resources. To achieve this facility, it is necessary to present a dynamic load balancing model to manage the load of the system efficiently based on the requests of the programs. Currently, the distributed Exascale systems with heterogeneous resources are the best branch of distributed computing systems that should be able to support the scientific programs with dynamic and interactive requests to resources. In this thesis, distributed Exascale systems are regarded as the operational and real distributed systems, and the dynamic load balancing model for the distributed controlling of load in the nodes in distributed Exascale computing systems are presented. The dominant paradigm in this model is derived from Operation Research sciences, and the request aware approach is replaced with the command-based approach in managing the load of the system. The results of evaluation show us the significant improvement regarding the performance by using the proposed load balancing mechanism in compare with the common distributed load balancing mechanisms
Università della Calabria
Tiwari, Manasi. "Communication Overlapping Krylov Subspace Methods for Distributed Memory Systems." Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5990.
Full textBooks on the topic "Exascale systems"
Reiz, Severin, Benjamin Uekermann, Philipp Neumann, Hans-Joachim Bungartz, and Wolfgang E. Nagel. Software for Exascale Computing - SPPEXA 2016-2019. Springer International Publishing AG, 2020.
Find full textReiz, Severin, Benjamin Uekermann, Philipp Neumann, Hans-Joachim Bungartz, and Wolfgang E. Nagel. Software for Exascale Computing - SPPEXA 2016-2019. Springer International Publishing AG, 2020.
Find full textBungartz, Hans-Joachim. Software for Exascale Computing - SPPEXA 2016-2019. Springer Nature, 2020.
Find full textVetter, Jeffrey S. Contemporary High Performance Computing: From Petascale Toward Exascale. Taylor & Francis Group, 2017.
Find full textVetter, Jeffrey S. Contemporary High Performance Computing: From Petascale toward Exascale. Chapman and Hall/CRC, 2013.
Find full textVetter, Jeffrey S. Contemporary High Performance Computing: From Petascale Toward Exascale. Taylor & Francis Group, 2017.
Find full textWilliams, Timothy J., Tjerk P. Straatsma, and Katerina B. Antypas. Exascale Scientific Applications: Scalability and Performance Portability. Taylor & Francis Group, 2017.
Find full textWilliams, Timothy J., Tjerk P. Straatsma, and Katerina B. Antypas. Exascale Scientific Applications: Scalability and Performance Portability. Taylor & Francis Group, 2017.
Find full textWilliams, Timothy J., Tjerk P. Straatsma, and Katerina B. Antypas. Exascale Scientific Applications: Scalability and Performance Portability. Taylor & Francis Group, 2017.
Find full textWilliams, Timothy J., Tjerk P. Straatsma, and Katerina B. Antypas. Exascale Scientific Applications: Scalability and Performance Portability. Taylor & Francis Group, 2017.
Find full textBook chapters on the topic "Exascale systems"
Djemame, Karim, and Hamish Carr. "Exascale Computing Deployment Challenges." In Economics of Grids, Clouds, Systems, and Services, 211–16. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63058-4_19.
Full textFlajslik, Mario, Eric Borch, and Mike A. Parker. "Megafly: A Topology for Exascale Systems." In Lecture Notes in Computer Science, 289–310. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92040-5_15.
Full textCasanova, Henri, Frédéric Vivien, and Dounia Zaidouni. "Using Replication for Resilience on Exascale Systems." In Computer Communications and Networks, 229–78. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20943-2_4.
Full textMhedheb, Yousri, and Achim Streit. "Energy Efficient Runtime Framework for Exascale Systems." In Lecture Notes in Computer Science, 32–44. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46079-6_3.
Full textZhao, Jisheng, Colleen Bertoni, Jeffrey Young, Kevin Harms, Vivek Sarkar, and Brice Videau. "HIPLZ: Enabling Performance Portability for Exascale Systems." In Euro-Par 2022: Parallel Processing Workshops, 197–210. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-31209-0_15.
Full textKogge, Peter M. "Updating the Energy Model for Future Exascale Systems." In Lecture Notes in Computer Science, 323–39. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20119-1_24.
Full textRoyuela, Sara, Alejandro Duran, Maria A. Serrano, Eduardo Quiñones, and Xavier Martorell. "A Functional Safety OpenMP $$^{*}$$ for Critical Real-Time Embedded Systems." In Scaling OpenMP for Exascale Performance and Portability, 231–45. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-65578-9_16.
Full textBobák, Martin, Ondrej Habala, and Ladislav Hluchý. "Exascale Flood Modelling in Environment Supporting Urgent Computing." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, 384–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32591-6_41.
Full textAliev, Araz R., and Nigar T. Ismayilova. "Graph-Based Load Balancing Model for Exascale Computing Systems." In 11th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence - ICSCCW-2021, 229–36. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92127-9_33.
Full textOeste, Sebastian, Marc-André Vef, Mehmet Soysal, Wolfgang E. Nagel, André Brinkmann, and Achim Streit. "ADA-FS—Advanced Data Placement via Ad hoc File Systems at Extreme Scales." In Software for Exascale Computing - SPPEXA 2016-2019, 29–59. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47956-5_4.
Full textConference papers on the topic "Exascale systems"
Varela, Maria Ruiz, Kurt B. Ferreira, and Rolf Riesen. "Fault-tolerance for exascale systems." In 2010 IEEE International Conference On Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS). IEEE, 2010. http://dx.doi.org/10.1109/clusterwksp.2010.5613081.
Full textJouppi, Norman Paul. "Resilience Challenges for Exascale Systems." In 2009 24th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems (DFT). IEEE, 2009. http://dx.doi.org/10.1109/dft.2009.52.
Full textKash, J. A., P. Pepeljugoski, F. E. Doany, C. L. Schow, D. M. Kuchta, L. Schares, R. Budd, et al. "Communication technologies for exascale systems." In SPIE OPTO: Integrated Optoelectronic Devices, edited by Alexei L. Glebov and Ray T. Chen. SPIE, 2009. http://dx.doi.org/10.1117/12.815329.
Full textMcLaren, Moray. "CMOS nanophotonics for exascale systems." In 2010 International Conference on Green Computing (Green Comp). IEEE, 2010. http://dx.doi.org/10.1109/greencomp.2010.5598267.
Full textBergman, Keren, Sébastien Rumley, Noam Ophir, Dessislava Nikolova, Robert Hendry, Qi Li, Kishore Padmara, Ke Wen, and Lee Zhu. "Silicon Photonics for Exascale Systems." In Optical Fiber Communication Conference. Washington, D.C.: OSA, 2014. http://dx.doi.org/10.1364/ofc.2014.m3e.1.
Full textCourteille, F., and J. Eaton. "Programming Perspectives for Pre-exascale Systems." In Second EAGE Workshop on High Performance Computing for Upstream. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201414023.
Full textParsons, Mark. "Exascale computing - An impossible challenge?" In 2011 NASA/ESA Conference on Adaptive Hardware and Systems (AHS). IEEE, 2011. http://dx.doi.org/10.1109/ahs.2011.5963975.
Full textFeng, Rui, Peng Zhang, and Yuefan Deng. "Network Design Considerations for Exascale Supercomputers." In Parallel and Distributed Computing and Systems. Calgary,AB,Canada: ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.789-001.
Full textLankes, Stefan. "Revisiting co-scheduling for upcoming ExaScale systems." In 2015 International Conference on High Performance Computing & Simulation (HPCS). IEEE, 2015. http://dx.doi.org/10.1109/hpcsim.2015.7237117.
Full textAgullo, Emmanuel, George Bosilca, Berenger Bramas, Cedric Castagnede, Olivier Coulaud, Eric Darve, Jack Dongarra, et al. "Abstract: Matrices Over Runtime Systems at Exascale." In 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC). IEEE, 2012. http://dx.doi.org/10.1109/sc.companion.2012.167.
Full textReports on the topic "Exascale systems"
Hendrickson, Bruce A. Scientific Discovery on Exascale Systems. Office of Scientific and Technical Information (OSTI), June 2015. http://dx.doi.org/10.2172/1198987.
Full textStearley, Jon R., Rolf E. Riesen, James H. ,. III Laros, Kurt Brian Ferreira, Kevin Thomas Tauke Pedretti, Ron A. Oldfield, and Ronald Brian Brightwell. Redundant computing for exascale systems. Office of Scientific and Technical Information (OSTI), December 2010. http://dx.doi.org/10.2172/1011662.
Full textBeckman, Pete, Ron Brightwell, Maya Gokhale, Bronis R. de Supinski, Steven Hofmeyr, Sriram Krishnamoorthy, Mike Lang, Barney Maccabe, John Shalf, and Marc Snir. Exascale Operating Systems and Runtime Software Report. Office of Scientific and Technical Information (OSTI), December 2012. http://dx.doi.org/10.2172/1471119.
Full textRiesen, Rolf E., Patrick G. Bridges, Jon R. Stearley, James H. ,. III Laros, Ron A. Oldfield, Dorian Arnold, Kevin Thomas Tauke Pedretti, Kurt Brian Ferreira, and Ronald Brian Brightwell. Keeping checkpoint/restart viable for exascale systems. Office of Scientific and Technical Information (OSTI), September 2011. http://dx.doi.org/10.2172/1029780.
Full textLong, Darrell E., and Ethan L. Miller. Dynamic Non-Hierarchical File Systems for Exascale Storage. Office of Scientific and Technical Information (OSTI), February 2015. http://dx.doi.org/10.2172/1170868.
Full textFerreira, Kurt Brian. Fault Survivability of Lightweight Operating Systems for exascale. Office of Scientific and Technical Information (OSTI), September 2014. http://dx.doi.org/10.2172/1459775.
Full textChoudhary, Alok, Nagiza Samatova, Kesheng Wu, and Wei-keng Liao. Scalable and Power Efficient Data Analytics for Hybrid Exascale Systems. Office of Scientific and Technical Information (OSTI), March 2015. http://dx.doi.org/10.2172/1173060.
Full textXie, Yuan. Blackcomb2: Hardware-Software Co-design for Nonvolatile Memory in Exascale Systems. Office of Scientific and Technical Information (OSTI), April 2018. http://dx.doi.org/10.2172/1485357.
Full textBrown, Forrest B., Brian Christopher Kiedrowski, Jeffrey S. Bull, and Lawrence James Cox. MCNP 2020: Preparing LANL Monte Carlo for Exascale Computer Systems (White Paper). Office of Scientific and Technical Information (OSTI), April 2015. http://dx.doi.org/10.2172/1177983.
Full textMudge, Trevor. BLACKCOMB2: Hardware-software co-design for non-volatile memory in exascale systems. Office of Scientific and Technical Information (OSTI), December 2017. http://dx.doi.org/10.2172/1413470.
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