Relevant bibliographies by topics / High Performance Computing (HPC)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'High Performance Computing (HPC)'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "High Performance Computing (HPC)"

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Blaheta, Radim, Ivan Georgiev, Krassimir Georgiev, et al. "High Performance Computing Applications." Cybernetics and Information Technologies 17, no. 5 (2017): 5–16. http://dx.doi.org/10.1515/cait-2017-0050.

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Abstract High Performance Computing (HPC) is required for many important applications in chemistry, computational fluid dynamics, etc., see, e.g., an overview in [1]. In this paper we shortly describe an application (a multiscale material design problem) that requires HPC for several reasons. The problem of interest is analysis of the fiber-reinforced concrete and we focus on modelling of stiffness through numerical homogenization and computing local material properties by inverse analysis. Both problems require a repeated solution of large-scale finite element problems up to 200 million degre
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Ranjit, Rajak. "A Comparative Study: Taxonomy of High Performance Computing (HPC)." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3386–91. https://doi.org/10.11591/ijece.v8i5.pp3386-3391.

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The computer technologies have rapidly developed in both software and hardware field. The complexity of software is increasing as per the market demand because the manual systems are going to become automation as well as the cost of hardware is decreasing. High Performance Computing (HPC) is very demanding technology and an attractive area of computing due to huge data processing in many applications of computing. The paper focus upon different applications of HPC and the types of HPC such as Cluster Computing, Grid Computing and Cloud Computing. It also studies, different classifications and
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Petrosyan, Davit, and Hrachya Astsatryan. "Serverless High-Performance Computing over Cloud." Cybernetics and Information Technologies 22, no. 3 (2022): 82–92. http://dx.doi.org/10.2478/cait-2022-0029.

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Abstract HPC clouds may provide fast access to fully configurable and dynamically scalable virtualized HPC clusters to address the complex and challenging computation and storage-intensive requirements. The complex environmental, software, and hardware requirements and dependencies on such systems make it challenging to carry out our large-scale simulations, prediction systems, and other data and compute-intensive workloads over the cloud. The article aims to present an architecture that enables HPC workloads to be serverless over the cloud (Shoc), one of the most critical cloud capabilities f
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Pousa, Adrián, Victoria María Sanz, Marcelo Naiouf, and Armando De Giusti. "Trends in High Performance Computing and Quantum Computing." Journal of Computer Science and Technology 24, no. 2 (2024): e11. http://dx.doi.org/10.24215/16666038.24.e11.

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High Performance Computing (HPC) applies different techniques to complex or large-volume applications, relying on both parallel software and hardware, to reduce their execution time compared to running them on a simple computer. On the other hand, Quantum Computing (QC) emerges as a new paradigm that leverages the properties of Quantum Mechanics for computation. QC has an inherently parallel nature and it is expected to solve some problems faster than classical computing. This paper carries out a bibliographic review to examine the point of view of different authors regarding the relationship
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Navaux, Philippe Olivier Alexandre, Arthur Francisco Lorenzon, and Matheus da Silva Serpa. "Challenges in High-Performance Computing." Journal of the Brazilian Computer Society 29, no. 1 (2023): 51–62. http://dx.doi.org/10.5753/jbcs.2023.2219.

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High-Performance Computing, HPC, has become one of the most active computer science fields. Driven mainly by the need for high processing capabilities required by algorithms from many areas, such as Big Data, Artificial Intelligence, Data Science, and subjects related to chemistry, physics, and biology, the state-of-art algorithms from these fields are notoriously demanding computer resources. Therefore, choosing the right computer system to optimize their performance is paramount. This article presents the main challenges of future supercomputer systems, highlighting the areas that demand the
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Rajak, Ranjit. "A Comparative Study: Taxonomy of High Performance Computing (HPC)." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3386. http://dx.doi.org/10.11591/ijece.v8i5.pp3386-3391.

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The computer technologies have rapidly developed in both software and hardware field. The complexity of software is increasing as per the market demand because the manual systems are going to become automation as well as the cost of hardware is decreasing. High Performance Computing (HPC) is very demanding technology and an attractive area of computing due to huge data processing in many applications of computing. The paper focus upon different applications of HPC and the types of HPC such as Cluster Computing, Grid Computing and Cloud Computing. It also studies, different classifications and
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Shajil, Kumar P. A., and Srinivasa Rao Kunte R. "ABCD Analysis of Industries using High-Performance Computing." International Journal of Case Studies in Business, IT, and Education (IJCSBE) 7, no. 2 (2023): 448–65. https://doi.org/10.5281/zenodo.8125105.

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<strong>Purpose:</strong> <em>High-Performance Computing (HPC) is the technique of increasing the overall processing capacity of the system, and </em><em>achieving high performance in solving large problems in science, engineering, or business. This research paper investigated the High-Performance Computing industry using exploratory research methodology and a listing of ABCD analysis is done. Along with this, the identification of various applications and grand challenges in HPC and various Software Tools required for industry-specific application areas of HPC is done.</em> <strong>Design/Met
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Jothikumar, R., Kumar Subramaniam, Siva G. Shanmugam, and S. Susi. "Electronic Voting System with Cloud Based High Performance Computing." Journal of Computational and Theoretical Nanoscience 16, no. 2 (2019): 768–72. http://dx.doi.org/10.1166/jctn.2019.7807.

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Traditional voting system has been replaced by electronic voting systems in most places increasingly. It is efficient, but not efficient enough in terms of cost and capacity. High Performance Computing (HPC) in Cloud computing is a relatively new concept which has been replacing the traditional systems. The HPC has been widely used over the recent years because of its efficiency, reliability, speed and cost. Whereas in the traditional super computing system a lot of cost is involved. The ability of integration of HPC with cloud provided enormous growth in the area of parallel processing and co
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Ayyasamy, S. "Contemporary High-Performance Computing for Big Data Applications." December 2023 5, no. 4 (2023): 375–84. http://dx.doi.org/10.36548/jitdw.2023.4.004.

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High-performance computing (HPC) involves leveraging parallel data processing to enhance computer performance and handle difficult tasks. HPC meets these aims by pooling computing capacity, enabling efficient, reliable, and prompt execution of even complex programs according to user demands and expectations. The rapid growth of HPDA in many sectors has led to the extension of the HPC market into new territory. HPC as well as Big Data systems differ not just in terms of technology but also in ecosystems. Extensive research in this sector has led to the emergence of various Big Data analytics mo
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Kim, Soeun, Sunggon Kim, and Hwajung Kim. "Efficient I/O Performance-Focused Scheduling in High-Performance Computing." Applied Sciences 14, no. 21 (2024): 10043. http://dx.doi.org/10.3390/app142110043.

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High-performance computing (HPC) systems are becoming increasingly important as contemporary exascale applications with demand extensive computational and data processing capability. To optimize these systems, efficient scheduling of HPC applications is important. In particular, because I/O is a shared resource among applications and is becoming more important due to the emergence of big data, it is possible to improve performance by considering the architecture of HPC systems and scheduling jobs based on I/O resource requirements. In this paper, we propose a scheduling scheme that prioritizes
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Dissertations / Theses on the topic "High Performance Computing (HPC)"

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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.

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The HPC+Cloud framework has been built to enable on-premise HPC jobs to use resources from cloud computing nodes. As part of designing the software framework, public cloud providers, namely Amazon AWS, Microsoft Azure and NeCTAR were benchmarked against one another, and Microsoft Azure was determined to be the most suitable cloud component in the proposed HPC+Cloud software framework. Finally, an HPC+Cloud cluster was built using the HPC+Cloud software framework and then was validated by conducting HPC processing benchmarks.
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Daillidis, Christos. "Establishing Linux Clusters for high-performance computing (HPC) at NPS." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Sept%5FDaillidis.pdf.

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Lanore, Vincent. "On Scalable Reconfigurable Component Models for High-Performance Computing." Thesis, Lyon, École normale supérieure, 2015. http://www.theses.fr/2015ENSL1051/document.

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La programmation à base de composants est un paradigme de programmation qui facilite la réutilisation de code et la séparation des préoccupations. Les modèles à composants dits « reconfigurables » permettent de modifier en cours d'exécution la structure d'une application. Toutefois, ces modèles ne sont pas adaptés au calcul haute performance (HPC) car ils reposent sur des mécanismes ne passant pas à l'échelle.L'objectif de cette thèse est de fournir des modèles, des algorithmes et des outils pour faciliter le développement d'applications HPC reconfigurables à base de composants. La principale
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Melas, Panagiotis. "The performance evaluation of workstation clusters." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326395.

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Agarwal, Dinesh. "Scientific High Performance Computing (HPC) Applications On The Azure Cloud Platform." Digital Archive @ GSU, 2013. http://digitalarchive.gsu.edu/cs_diss/75.

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Cloud computing is emerging as a promising platform for compute and data intensive scientific applications. Thanks to the on-demand elastic provisioning capabilities, cloud computing has instigated curiosity among researchers from a wide range of disciplines. However, even though many vendors have rolled out their commercial cloud infrastructures, the service offerings are usually only best-effort based without any performance guarantees. Utilization of these resources will be questionable if it can not meet the performance expectations of deployed applications. Additionally, the lack of the f
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KhoshgoftarMonfared, Alireza. "Tactical HPC: Scheduling high performance computers in a geographical region." Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/54934.

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Mobile devices are often expected to perform computational tasks that may be beyond their processing or battery capability. Cloud computing techniques have been proposed as a means to offload a mobile device's computation to more powerful resources. In this thesis, we consider the case where powerful computing resources are made available by utilizing vehicles. These vehicles can be repositioned in real time to receive computational tasks from user-carried devices. They can be either equipped with rugged high-performance computers to provide both computation and communication service, or they
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Berg, Gustaf, and Magnus Brattlöf. "Distributed Checkpointing with Docker Containers in High Performance Computing." Thesis, Högskolan Väst, Avdelningen för data-, elektro- och lantmäteriteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-11645.

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Container-virtualisering har blivit mer och mer använt efter att uppdateringar till cgroups och namespace-funktionerna släpptes i Linuxkärnan. Samtidigt så lider industrins högpresterande beräkningskluster av dyra licenskostnader som skulle kunna hanteras av virtualisering. I den här uppsatsen utformades experiment för att ta reda på om Dockers funktion checkpoint, som fortfarande är under utveckling, skulle kunna utnyttjas i industrins beräkningskluster. Genom att demonstrera detta koncept och dess möjligheter att pausa distribuerade containrar, som kör parallella processer inuti, användes de
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Mani, Sindhu. "Empirical Performance Analysis of High Performance Computing Benchmarks Across Variations in Cloud Computing." UNF Digital Commons, 2012. http://digitalcommons.unf.edu/etd/418.

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High Performance Computing (HPC) applications are data-intensive scientific software requiring significant CPU and data storage capabilities. Researchers have examined the performance of Amazon Elastic Compute Cloud (EC2) environment across several HPC benchmarks; however, an extensive HPC benchmark study and a comparison between Amazon EC2 and Windows Azure (Microsoft’s cloud computing platform), with metrics such as memory bandwidth, Input/Output (I/O) performance, and communication computational performance, are largely absent. The purpose of this study is to perform an exhaustive HPC bench
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Zhang, Jie Zhang. "Designing and Building Efficient HPC Cloud with Modern Networking Technologies on Heterogeneous HPC Clusters." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1532737201524604.

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Abraham, Subil. "On the Use of Containers in High Performance Computing." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99319.

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The lightweight, portable, and flexible nature of containers is driving their widespread adoption in cloud solutions. Data analysis and deep learning applications have especially benefited from containerized solutions. As such data analysis is also being utilized in the high performance computing (HPC) domain, the need for container support in HPC has become paramount. However, container adoption in HPC face crucial performance and I/O challenges. One obstacle is that while there have been container solutions for HPC, such solutions have not been thoroughly investigated, especially from the as
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Books on the topic "High Performance Computing (HPC)"

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Pancake, Cherri M. Task force on requirements for HPC software and tools: Guidelines for specifying HPC software. Oregon State University, Dept. of Computer Science, 1999.

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Gruber, Ralf. HPC@green IT: Green high performance computing methods. Springer, 2010.

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Pancake, Cherri M. Establishing standards for HPC system software and tools. Oregon State University, Dept. of Computer Science, 1997.

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Corporation, International Business Machines, ed. HPC clusters using Infiniband on IBM Power systems servers. Vervante, 2009.

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Sahni, Sartaj, Viktor K. Prasanna, and Uday Shukla, eds. High Performance Computing — HiPC 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36265-7.

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Monien, Burkhard, Viktor K. Prasanna, and Sriram Vajapeyam, eds. High Performance Computing — HiPC 2001. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45307-5.

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Robert, Yves, Manish Parashar, Ramamurthy Badrinath, and Viktor K. Prasanna, eds. High Performance Computing - HiPC 2006. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11945918.

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Aluru, Srinivas, Manish Parashar, Ramamurthy Badrinath, and Viktor K. Prasanna, eds. High Performance Computing – HiPC 2007. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-77220-0.

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Bougé, Luc, and Viktor K. Prasanna, eds. High Performance Computing - HiPC 2004. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b104576.

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Banerjee, Prith, Viktor K. Prasanna, and Bhabani P. Sinha, eds. High Performance Computing – HiPC’99. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/b86069.

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Book chapters on the topic "High Performance Computing (HPC)"

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Steenman-Clark, Lois, and Alan O’Neill. "Modelling Climate Variability on HPC Platforms." In High-Performance Computing. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4873-7_34.

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Keane, J. A., M. F. P. O’Boyle, and R. Sakellariou. "Legacy Systems - The Future of HPC." In High-Performance Computing. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4873-7_52.

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Openshaw, Stan. "HPC and Human Geographic Social Science Research." In High-Performance Computing. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4873-7_49.

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Nicole, Denis, Kenji Takeda, and Ivan Wolton. "HPC On Dec Alphas And Windows NT." In High-Performance Computing. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4873-7_59.

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Raj, Pethuru, Anupama Raman, Dhivya Nagaraj, and Siddhartha Duggirala. "High-Performance Computing (HPC) Paradigms." In Computer Communications and Networks. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20744-5_7.

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Kerbyson, Darren J., Efstathios Papaefstathiou, John S. Harper, Stewart C. Perry, and Graham R. Nudd. "Is Predictive Tracing Too Late for HPC Users?" In High-Performance Computing. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4873-7_7.

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Elliott, John A., Stephen H. Brindle, Adrian Colbrook, Daron G. Green, and Francis Wray. "Real industrial HPC applications." In High-Performance Computing and Networking. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61142-8_526.

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Dongarra, Jack J., Hans W. Meuer, Horst D. Simon, and Erich Strohmaier. "Changing technologies of HPC." In High-Performance Computing and Networking. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61142-8_639.

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da Rosa Righi, Rodrigo, Guilherme Galante, Vinicius Facco Rodrigues, et al. "Designing Cloud-Friendly HPC Applications." In High Performance Computing in Clouds. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-29769-4_6.

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Strohmaier, Erich, Jack J. Dongarra, Hans W. Meuer, and Horst D. Simon. "Evolution of the HPC Market." In Advances in High Performance Computing. Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5514-4_2.

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Conference papers on the topic "High Performance Computing (HPC)"

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Patil, Abhishek, Shamjith K. V, Senthil Kumar R. K, and S. D. Sudarsan. "Augmenting HPC Profilers with Analysis Capabilities." In 2024 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2024. https://doi.org/10.1109/hpec62836.2024.10938486.

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Chen, Po Hao, Akshaya Bali, Shining Yang, et al. "Cycle-Stealing in Load-Imbalanced HPC Applications." In 2024 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2024. https://doi.org/10.1109/hpec62836.2024.10938500.

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Thurimella, Vijay, Philipp Raith, Rolando P. Hong Enriquez, et al. "Serverless Computing for Dynamic HPC Workflows." In SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 2024. https://doi.org/10.1109/scw63240.2024.00262.

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Byun, Chansup, Albert Reuther, Julie Mullen, et al. "LLload: An Easy-to-Use HPC Utilization Tool." In 2024 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2024. https://doi.org/10.1109/hpec62836.2024.10938510.

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Suetterlein, Joshua, Stephen J. Young, Jesun Firoz, et al. "HPC Network Simulation Tuning via Automatic Extraction of Hardware Parameters." In 2024 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2024. https://doi.org/10.1109/hpec62836.2024.10938439.

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Al-Shaikh, R., O. Saadoon, E. Haydar, and M. Baddourah. "Green HPC for Reservoir Simulation Computing." In EAGE Workshop on High Performance Computing for Upstream. EAGE Publications BV, 2014. http://dx.doi.org/10.3997/2214-4609.20141931.

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Oberlin, S. "Peak HPC": The Moore’s Law Crisis and the Future of HPC." In EAGE Workshop on High Performance Computing for Upstream. EAGE Publications BV, 2014. http://dx.doi.org/10.3997/2214-4609.20141934.

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"HPC 2012: Sustainable HPC Cloud Workshop." In 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC). IEEE, 2012. http://dx.doi.org/10.1109/sc.companion.2012.369.

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Hincelin, A., and P. Demichel. "HPC Expertise for Extreme Generative AI Tuning." In Eighth EAGE High Performance Computing Workshop. European Association of Geoscientists & Engineers, 2024. https://doi.org/10.3997/2214-4609.2024636021.

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Petersen, Torben Kling, and John Fragalla. "Enterprise HPC storage systems." In 2014 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2014. http://dx.doi.org/10.1109/hpec.2014.7040948.

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Reports on the topic "High Performance Computing (HPC)"

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Guo, Yang. High Performance Computing (HPC) Security:. National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.sp.800-223.ipd.

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Dongarra, Jack. High Performance Computing (HPC) Challenge (HPCC) Benchmark Suite Development. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada436281.

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Ross, Virginia W., and Scott E. Spetka. Grid Computing for High Performance Computing (HPC) Data Centers. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada466685.

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Hochstein, Lorin. High Performance Computing (HPC) Innovation Service Portal Pilots Cloud Computing (HPC-ISP Pilot Cloud Computing). Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada549202.

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Kendall, Nicholas, Ethan Eldridge, David Kleponis, and Stephen Schraml. 3D Printing High Performance Computing (HPC) Simulation Results. DEVCOM Army Research Laboratory, 2022. http://dx.doi.org/10.21236/ad1158683.

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Klitsner, Tom. Intro - High Performance Computing for 2015 HPC Annual Report. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1226517.

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Panneton, Brian, and James Adametz. High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: HPC Data Reduction Framework. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada626053.

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McIntyre, Cynthia, Suzy Tichenor, and Brian Schott. High Performance Computing for National Security and Competitive Strength (HPC-NSCS). Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada499551.

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Infantolino, Jamie, Song Park, and Dale Shires. Selecting a Benchmark Suite to Profile High-Performance Computing (HPC) Machines. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada612837.

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Abu-Ghazaleh, Nael. Optimized Parallel Discrete Event Simulation (PDES) for High Performance Computing (HPC) Clusters. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada438052.

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