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1

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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9

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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Lange, Christopher, Stephan Tremmel, and Frank Rieg. "Integration von High-Performance- Computing in die simulationsunterstützte Produktentwicklung." Konstruktion 73, no. 06 (2021): 69–74. http://dx.doi.org/10.37544/0720-5953-2021-06-69.

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Inhalt High-Performance-Computing (HPC) ermöglicht Unternehmen simulationsunterstützte Produktentstehungsprozesse durch Bereitstellung von massiv-paralleler Recheninfrastruktur zu beschleunigen. Die Integration von HPC in die Produktentwicklung ist sowohl prozess- als auch systemseitig komplex und aufgrund der finanziellen Aufwendungen risikobehaftet. Daher haben besonders kleine und mittlere Unternehmen (KMU) eine hohe Einstiegshürde. Dieser Beitrag hat das Ziel die HPC-Integration für Unternehmen durch die Entwicklung eines Vorgehensmodells zu vereinfachen. Hierfür wird zunächst eine Klassif
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ALMEIDA, SÉRGIO. "AN INTRODUCTION TO HIGH PERFORMANCE COMPUTING." International Journal of Modern Physics A 28, no. 22n23 (2013): 1340021. http://dx.doi.org/10.1142/s0217751x13400216.

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High Performance Computing (HPC) has become an essential tool in every researcher's arsenal. Most research problems nowadays can be simulated, clarified or experimentally tested by using computational simulations. Researchers struggle with computational problems when they should be focusing on their research problems. Since most researchers have little-to-no knowledge in low-level computer science, they tend to look at computer programs as extensions of their minds and bodies instead of completely autonomous systems. Since computers do not work the same way as humans, the result is usually Low
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Lynn, Theo, Grace Fox, Anna Gourinovitch, and Pierangelo Rosati. "Understanding the Determinants and Future Challenges of Cloud Computing Adoption for High Performance Computing." Future Internet 12, no. 8 (2020): 135. http://dx.doi.org/10.3390/fi12080135.

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High performance computing (HPC) is widely recognized as a key enabling technology for advancing scientific progress, industrial competitiveness, national and regional security, and the quality of human life. Notwithstanding this contribution, the large upfront investment and technical expertise required has limited the adoption of HPC to large organizations, government bodies, and third level institutions. Recent advances in cloud computing and telecommunications have the potential to overcome the historical issues associated with HPC through increased flexibility and efficiency, and reduced
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Cavet, Cécile, Aurélien Bailly-Reyre, David Chamont, et al. "ComputeOps: containers for High Performance Computing." EPJ Web of Conferences 214 (2019): 07004. http://dx.doi.org/10.1051/epjconf/201921407004.

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The High Performance Computing (HPC) domain aims to optimize code to use the latest multicore and parallel technologies including specific processor instructions. In this computing framework, portability and reproducibility are key concepts. A way to handle these requirements is to use Linux containers. These "light virtual machines" allow users to encapsulate applications within its environment in processes. Containers have been recently highlighted because they provide multi-infrastructure environnement for both developers and system administrators. Furthermore, they offer reproducibility du
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Cavet, Cécile, Martin Souchal, Sébastien Gadrat, et al. "ComputeOps: Container for High Performance Computing." EPJ Web of Conferences 245 (2020): 07006. http://dx.doi.org/10.1051/epjconf/202024507006.

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The High Performance Computing (HPC) domain aims to optimize code in order to use the latest multicore and parallel technologies including specific processor instructions. In this computing framework, portability and reproducibility are key concepts. A way to handle these requirements is to use Linux containers. These “light virtual machines” allow to encapsulate applications within its environment in Linux processes. Containers have been recently rediscovered due to their abilities to provide both multi-infrastructure environnement for developers and system administrators and reproducibility
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16

Luo, Li Qun, and Si Jin He. "A Memory Architecture Design for High-Performance Cloud Computing." Advanced Materials Research 532-533 (June 2012): 677–81. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.677.

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The advent of cloud is drastically changing the High Performance Computing (HPC) application scenarios. Current virtual machine-based IaaS architectures are not designed for HPC applications. This paper presents a new cloud oriented storage system by constructing a large scale memory grid in a distributed environment in order to support low latency data access of HPC applications. This Cloud Memory model is built through the implementation of a private virtual file system (PVFS) upon virtual operating system (OS) that allows HPC applications to access data in such a way that Cloud Memory can a
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Cohen, Jeremy, Ioannis Filippis, Mark Woodbridge, et al. "RAPPORT: running scientific high-performance computing applications on the cloud." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1983 (2013): 20120073. http://dx.doi.org/10.1098/rsta.2012.0073.

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Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on
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Uday Shankar Patil. "High Performance Computing for Large Scale Civil Engineering Simulations." Advances in Nonlinear Variational Inequalities 27, no. 4 (2024): 131–48. http://dx.doi.org/10.52783/anvi.v27.1497.

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High performance Computing (HPC) may be a key portion of progressing large-scale models in respectful designing. It makes modeling complicated buildings and frameworks more precise and effective than ever some time recently. This paper looks at how HPC can be utilized in respectful designing models, particularly how it can be utilized to arrange, analyze, and move forward enormous ventures. We see at diverse HPC plans, such as dispersed computing, cloud-based arrangements, and how they can be utilized for fluid-structure intelligent, auxiliary flow, and geotechnical ponders. The think about ap
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Kang, Pilsung. "Programming for High-Performance Computing on Edge Accelerators." Mathematics 11, no. 4 (2023): 1055. http://dx.doi.org/10.3390/math11041055.

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The field of edge computing has grown considerably over the past few years, with applications in artificial intelligence and big data processing, particularly due to its powerful accelerators offering a large amount of hardware parallelism. As the computing power of the latest edge systems increases, applications of edge computing are being expanded to areas that have traditionally required substantially high-performant computing resources such as scientific computing. In this paper, we review the latest literature and present the current status of research for implementing high-performance co
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20

A, Sathesh. "Autotuning with High-Performance Computing in Real Time Applications." June 2024 3, no. 1 (2024): 104–12. http://dx.doi.org/10.36548/rrrj.2024.1.007.

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This study explores the use of high-performance computing (HPC) to address the demanding requirements of real-time applications. Real-time systems, characterized by stringent timing constraints and variable workloads, require computing solutions capable of delivering excellent performance. The study examines the challenges associated with achieving real-time responsiveness and the opportunities presented by leveraging the computational power of HPC architectures. The study provides an overview of the key characteristics of real-time applications and their various computational needs. It then i
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Chevillard, Maxime, Yu Qiu, Kamiya Mika, and Chenghan Li. "Sustainable High-Performance Computing: Assessing Environmental Impacts and Future Strategies." Advances in Engineering Technology Research 13, no. 1 (2025): 1272. https://doi.org/10.56028/aetr.13.1.1272.2025.

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In this study, we developed a multi-layered model analyzing HPC energy use, carbon footprint, and broader environmental consequences. We built a hierarchical model that categorizes energy consumption based on system scale. Our calculations indicated that global HPC energy consumption in 2023 was 82.09 TWh. We used a weighted carbon intensity formula to estimate carbon emissions using forecasted energy consumption and national energy mixes. The model considered both the manufacturing and operational phases of HPC systems. In 2023, the carbon emissions from HPC systems were approximately 35 mill
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Researcher. "PARALLELISM AND MULTITHREADING IN HIGH-PERFORMANCE COMPUTING." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 360–75. https://doi.org/10.5281/zenodo.13987265.

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This comprehensive article explores the critical role of parallelism and multithreading in high-performance computing (HPC), addressing the growing demand for computational power in scientific and technological advancements. It covers key concepts such as multithreading, thread pools, OpenMP, task parallelism, memory consistency models, and task scheduling in multicore processors. The article presents detailed explanations, code examples, and performance metrics from various studies, highlighting the significant efficiency, scalability, and resource utilization improvements achieved through th
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Sasikumar, D., and S. Saravanakumar. "Cozy and Safety Developments Up to Date in High Overall Performance Computing the Use of Cloud Computing." Journal of Computational and Theoretical Nanoscience 16, no. 2 (2019): 709–14. http://dx.doi.org/10.1166/jctn.2019.7795.

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High performance computing (HPC) is a part of period that focuses on joining the power of figuring devices. HPC created because of increment sought after of handling pace. At some phase in pervious innovation HIPC applications have constantly required huge no of PCs interconnected in a network together with group. Groups are hard to set up and keep both in fact and monetarily. It will turn out to be less confounded to introduce hip bundles inside the cloud without stressing over the expenses related with it additionally convey ensures at the phenomenal of contributions (Qos). It enables ordina
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Nakaegawa, Tosiyuki. "High-Performance Computing in Meteorology under a Context of an Era of Graphical Processing Units." Computers 11, no. 7 (2022): 114. http://dx.doi.org/10.3390/computers11070114.

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This short review shows how innovative processing units—including graphical processing units (GPUs)—are used in high-performance computing (HPC) in meteorology, introduces current scientific studies relevant to HPC, and discusses the latest topics in meteorology accelerated by HPC computers. The current status surrounding HPC is distinctly complicated in both hardware and software terms, and flows similar to fast cascades. It is difficult to understand and follow the status for beginners; they need to overcome the obstacle of catching up on the information on HPC and connecting it to their stu
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Niranjana, Gurushankar. "Advanced Verification Techniques for High-Performance Computing Chips." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 7, no. 1 (2021): 1–6. https://doi.org/10.5281/zenodo.14281923.

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High-Performance Computing (HPC) chips demand advanced verification techniques to ensure correctness and performance. This paper explores methodologies addressing the challenges posed by massive parallelism and complex architectures. We investigate formal verification, hardware acceleration for simulation and emulation, and emerging techniques like constrained-random verification and machine learning for test generation. The paper will examine the challenges associated with verifying HPC chips , considering its technical, linguistic. The paper will also present future directions for these chal
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Makweba, Damas A., and Daudi Samson Simbeye. "Improvement of Energy-Efficiency in High Performance Computing (HPC)." International Journal of ICT Research in Africa and the Middle East 10, no. 2 (2021): 1–22. http://dx.doi.org/10.4018/ijictrame.290835.

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Power continues to be a challenging problem facing institutions which are deploying high performance computing (HPC) facility in developing countries including Tanzania. These institutions like Dar es Salaam Institute of Technology (DIT) can face high operational costs due to the high energy consumption caused by computational operations of HPC systems. Because of the exceedingly high energy cost, diminishing energy consumption has become a major concern in deploying HPC systems. This manuscript per the authors used empirical modeling (EM) to predict the trends of power and cost operation for
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Monteiro, André, Cláudio Teixeira, and Joaquim S. Pinto. "HPC in Weather Forecast." International Journal of Cloud Applications and Computing 5, no. 1 (2015): 14–31. http://dx.doi.org/10.4018/ijcac.2015010102.

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Many traditional High-Performance Computing systems rely on hardware performance as well as compiler parallelization. The increased demand on computing resources rapidly escalates costs, which are the bigger limitation nowadays in both public and private sector. Cutting costs stimulates the research for new solutions, which are being opened by Cloud Computing. Virtualization becomes the key to migration and delivering intensive computing applications becomes more proficient than ever, thus providing the motivation for a change to the Cloud. This paper presents a case study of how to migrate an
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Lu, Zhaojie, Rhibull Tang, Zijia Wan, and Zetao Ye. "Mitigating the Environmental Impact of High-Performance Computing Data Centers." International Journal of Energy 6, no. 3 (2025): 9–18. https://doi.org/10.54097/y0yb9r53.

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While High Performance Computing (HPC) is critical for scientific breakthroughs and AI development, its growing energy use (often dependent on fossil fuels) requires a detailed environmental impact analysis. This study addresses the ever-increasing ecological challenges posed by high-performance computing (HPC) data centers by developing a model to quantify and predict their energy consumption and carbon emissions. Our model estimates the annual energy consumption of HPC data centers globally using data on the size and capacity of small and massive data centers. It distinguishes between theore
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Pathak, Purvi, and Kumar R. "THE FEASIBILITY STUDY OF RUNNING HPC WORKLOADS ON COMPUTATIONAL CLOUDS." Asian Journal of Pharmaceutical and Clinical Research 10, no. 13 (2017): 445. http://dx.doi.org/10.22159/ajpcr.2017.v10s1.20507.

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High-performance computing (HPC) applications require high-end computing systems, but not all scientists have access to such powerful systems. Cloud computing provides an opportunity to run these applications on the cloud without the requirement of investing in high-end parallel computing systems. We can analyze the performance of the HPC applications on private as well as public clouds. The performance of the workload on the cloud can be calculated using different benchmarking tools such as NAS parallel benchmarking and Rally. The workloads of HPC applications require use of many parallel com
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Grannan, A., K. Sood, B. Norris, and A. Dubey. "Understanding the landscape of scientific software used on high-performance computing platforms." International Journal of High Performance Computing Applications 34, no. 4 (2020): 465–77. http://dx.doi.org/10.1177/1094342019899451.

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Scientific discovery increasingly relies on computation through simulations, analytics, and machine and deep learning. Of these, simulations on high-performance computing (HPC) platforms have been the cornerstone of scientific computing for more than two decades. However, the development of simulation software has, in general, occurred through accretion, with a few exceptions. With an increase in scientific understanding, models have become more complex, rendering an accretion mode untenable to the point where software productivity and sustainability have become active concerns in scientific c
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Liu, Tingting, Dong Lu, Hao Zhang, et al. "Applying high-performance computing in drug discovery and molecular simulation." National Science Review 3, no. 1 (2016): 49–63. http://dx.doi.org/10.1093/nsr/nww003.

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Abstract In recent decades, high-performance computing (HPC) technologies and supercomputers in China have significantly advanced, resulting in remarkable achievements. Computational drug discovery and design, which is based on HPC and combines pharmaceutical chemistry and computational biology, has become a critical approach in drug research and development and is financially supported by the Chinese government. This approach has yielded a series of new algorithms in drug design, as well as new software and databases. This review mainly focuses on the application of HPC to the fields of drug
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Suresh Dameruppula. "The evolution and impact of high-performance computing systems." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 1983–89. https://doi.org/10.30574/wjarr.2025.26.1.1247.

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High-Performance Computing (HPC) has revolutionized computational capabilities across industries, enabling solutions to previously intractable problems. The evolution from terascale to exascale systems has fundamentally transformed research methodologies and analytical techniques in domains ranging from climate science to healthcare. Modern HPC architectures leverage specialized hardware integration, advanced interconnect technologies, and sophisticated storage infrastructures to achieve unprecedented performance levels. These systems operate through diverse paradigms, including shared memory,
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Chou, Jerry, and Wu-Chun Chung. "Cloud Computing and High Performance Computing (HPC) Advances for Next Generation Internet." Future Internet 16, no. 12 (2024): 465. https://doi.org/10.3390/fi16120465.

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HORI, M., G. SOBHANINEJAD, T. ICHIMURA, and M. LALITH. "ENHANCEMENT OF INTEGRATED EARTHQUAKE SIMULATION WITH HIGH-PERFORMANCE COMPUTING." Journal of Earthquake and Tsunami 05, no. 03 (2011): 271–82. http://dx.doi.org/10.1142/s1793431111000930.

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Integrated earthquake simulation (IES) is a system to estimate possible earthquake hazard and disaster which can take place in an urban area by means of seamless numerical computation. High-performance computing (HPC) is enhanced so that IES is able to simulate a larger area in a shorter time, by improving the system architecture and adding new elements which smoothens the system's efficiency. It is shown in numerical experiments (which are carried out for actual urban areas) that the performance of IES enhanced with HPC is satisfactory. A new system is developed to generate a hazard map which
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Kelechi, Anabi Hilary, Mohammed H. Alsharif, Okpe Jonah Bameyi, et al. "Artificial Intelligence: An Energy Efficiency Tool for Enhanced High performance computing." Symmetry 12, no. 6 (2020): 1029. http://dx.doi.org/10.3390/sym12061029.

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Power-consuming entities such as high performance computing (HPC) sites and large data centers are growing with the advance in information technology. In business, HPC is used to enhance the product delivery time, reduce the production cost, and decrease the time it takes to develop a new product. Today’s high level of computing power from supercomputers comes at the expense of consuming large amounts of electric power. It is necessary to consider reducing the energy required by the computing systems and the resources needed to operate these computing systems to minimize the energy utilized by
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Hussin, Masnida, Mohd Ridhuan Noor Affendi, and Dana Hasan. "A Study of the High-Performance Computing Parallelism in Solving Complexity of Meteorology Data and Calculations." Journal of Advanced Research in Applied Sciences and Engineering Technology 54, no. 1 (2024): 16–26. https://doi.org/10.37934/araset.54.1.1626.

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This paper investigates the high-performance computing (HPC) implementation in the field of meteorology, the challenges, and the future benefits. It is associated with utilizing HPC parallelism to simultaneously execute multiple tasks or operations for meteorological research. Merely a few people are aware of HPC's role in generating weather forecasting, climate modeling, and data assimilation. Our investigation elaborates on, identifies, and analyzes the features and characteristics of parallel computing that are utilized in it. The paper also focuses on examining parallelization modeling, th
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Sun, Jian, and Jin Tong. "Construction of a User-Oriented Usability Metric Model for High-Performance Computer Systems." Journal of Sensors 2022 (August 19, 2022): 1–11. http://dx.doi.org/10.1155/2022/4100639.

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The peak performance of high-performance computers is affected by many factors in practical operation. Scientific programs in different application areas use different algorithms and have different requirements for HPC systems. For example, communication-intensive algorithms require higher network performance of the machine, and computation-intensive algorithms require higher processor performance. In the face of many HPC systems, how to evaluate and select the HPC system with high availability is a problem that must be solved. In this paper, we study how to construct a user-oriented usability
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Abid, Mohamed Riduan. "HPC (High-Performance the Computing) for Big Data on Cloud: Opportunities and Challenges." International Journal of Computer Theory and Engineering 8, no. 5 (2016): 423–28. http://dx.doi.org/10.7763/ijcte.2016.v8.1083.

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Nagaraj, Vikas. "Design-for-Test (DFT) strategies for high-performance computing and graphics chips." International journal of signal processing, embedded systems and VLSI design 05, no. 01 (2025): 10–34. https://doi.org/10.55640/ijvsli-05-01-03.

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With the architecture complexity of silicon in high-performance computing (HPC) and graphics processing units (GPUs) growing, reliability, scalability, and first-time-right silicon cannot be achieved without the introduction of advanced Design for Test (DFT) methodologies. This paper addresses the peculiarities of DFT magnetization to cope with the characteristics of HPC and GPU environment issues: massive parallelism, depth pipelining, multi-clock, power domains, and rising thermal and power density. It covers basic techniques, including scan-based testing, built-in self-test (BIST), logic BI
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Huang, Tammy, Jiachen Li, Zixuan Ren, and ShengJia Xu. "Examining the Environmental Impact of High-Powered Computing." Advances in Engineering Technology Research 13, no. 1 (2025): 1284. https://doi.org/10.56028/aetr.13.1.1284.2025.

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The carbon emissions of High-Powered Computing (HPC) energy consumption impact the environment. This article establishes a series of models to study the impact of HPC energy consumption carbon emissions on the environment. It proposes corresponding suggestions to reduce the effects of HPC carbon emissions on the environment. This paper develops mathematical models and formulas to analyze the global energy consumption and environmental impact of HPC regarding full capacity and average utilization. Based on this dynamic model, energy consumption and carbon emissions were calculated for three sce
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Ma, Weihang, Lanxi Gao, Qinyue Gong, and Zhixing Wang. "Modeling the Environmental Footprint and Sustainability of High-Performance Computing." Theoretical and Natural Science 104, no. 1 (2025): 8–17. https://doi.org/10.54254/2753-8818/2025.ch24595.

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The rapid development and expansion of High-Performance Computing (HPC) systems present signif- icant environmental challenges, primarily due to substantial energy consumption and associated carbon emissions, often from non-renewable sources. This paper provides a comprehensive analysis of the en- vironmental footprint of HPC. It models global energy consumption, considering both full capacity and average utilization rates (estimated at 12-18%). A model is developed to quantify total carbon emis- sions, accounting for diverse energy sources, regional energy mixes, and conversion efficiencies.
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Lim, Sang Boem, Joon Woo, and Guohua Li. "Performance analysis of container-based networking solutions for high-performance computing cloud." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1507. http://dx.doi.org/10.11591/ijece.v10i2.pp1507-1514.

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Recently, cloud service providers have been gradually changing from virtual machine-based cloud infrastructures to container-based cloud-native infrastructures that consider performance and workload-management issues. Several data network performance issues for virtual instances have arisen, and various networking solutions have been newly developed or utilized. In this paper, we propose a solution suitable for a high-performance computing (HPC) cloud through a performance comparison analysis of container-based networking solutions. We constructed a supercomputer-based test-bed cluster to eval
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Sang, Boem Lim, Woo Joon, and Li Guohua. "Performance analysis of container-based networking Solutions for high-performance computing cloud." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1507–14. https://doi.org/10.11591/ijece.v10i2.pp1507-1514.

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Recently, cloud service providers have been gradually changing from virtual machine-based cloud infrastructures to container-based cloud-native infrastructures that consider performance and workload-management issues. Several data network performance issues for virtual instances have arisen, and various networking solutions have been newly developed or utilized. In this paper, we propose a solution suitable for a high-performance computing (HPC) cloud through a performance comparison analysis of container-based networking solutions. We constructed a supercomputer-based test-bed cluster to eval
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Atanassov, Emanouil, Todor Gurov, and Aneta Karaivanova. "Towards Effective Bulgarian Competence Centre in High Performance Computing – Service Portfolio and Competences." Digital Presentation and Preservation of Cultural and Scientific Heritage 13 (September 1, 2023): 333–40. http://dx.doi.org/10.55630/dipp.2023.13.35.

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Three years ago a new European initiative started: establishing a network of Centres of Competence in HPC in the European countries through the project EuroCC (2020-2022) in its second phase EuroCC2 (2023-2025). The goal is to accelerate the improvement of national and thus European capabilities in the area of HPC+ technologies, where HPC+ means High Performance Computing (HPC) and HPC application in HPDA and AI. In order to form an effective National Competence Centre in HPC+ technologies, we performed extensive competence mapping and now devise an extensive service portfolio, open to users f
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V, Aravinda Rajan, and Marimuthu T. "COMPARATIVE ANALYSIS OF HIGH-PERFORMANCE COMPUTING SOLUTIONS IN BIG DATA ENVIRONMENT." ICTACT Journal on Data Science and Machine Learning 4, no. 3 (2023): 451–56. https://doi.org/10.21917/ijdsml.2023.0105.

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High Performance Computing (HPC) technologies and solutions provide an increasingly important means for organizations and institutions to process larger volumes of data and to generate insights. In particular, big data environments, which are characterized by large and complex datasets, with an unbounded potential for data growth and a need to process both structured and unstructured data quickly, require advanced HPC solutions and technologies. HPC solutions are used to perform complex data transformations, analytics, and simulations, including solving complex numerical problems and modeling
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Hart, David L. "Measuring TeraGrid: workload characterization for a high-performance computing federation." International Journal of High Performance Computing Applications 25, no. 4 (2011): 451–65. http://dx.doi.org/10.1177/1094342010394382.

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TeraGrid has deployed a significant monitoring and accounting infrastructure in order to understand its operational success. In this paper, we present an analysis of the jobs reported by TeraGrid for 2008. We consider the workload from several perspectives: traditional high-performance computing (HPC) workload characteristics; grid-oriented workload characteristics; and finally user- and group-oriented characteristics. We use metrics reported in prior studies of HPC and grid systems in order to understand whether such metrics provide useful information for managing and studying resource federa
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Petrič, Špela, and Miha Turšič. "Becoming.a(Thing): An Artists’ Perspective on High-Performance Computing." Leonardo 52, no. 1 (2019): 73–74. http://dx.doi.org/10.1162/leon_a_01469.

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This article summarizes the process and outcome of the Future Emerging Art and Technology residency during which new media artists Špela Petrič and Miha Turšič undertook the challenge of understanding and manifesting the artistic potential of high-performance computing (HPC). As a result of the collaboration with FET HPC the artists developed a concept liberated from complex computational technicity to underscore the (un)intentional construction of meaning by algorithmic agencies. The performance presents a congress of actors sensing, interrogating and interrupting each other, thereby producin
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Lee, Kiwon, and Suchul Lee. "Knowledge Structure of the Application of High-Performance Computing: A Co-Word Analysis." Sustainability 13, no. 20 (2021): 11249. http://dx.doi.org/10.3390/su132011249.

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As high-performance computing (HPC) plays a key role in the Fourth Industrial Revolution, the application of HPC in various industries is becoming increasingly important. Several studies have reviewed the research trends of HPC but considered only the functional aspects, causing limitations when discussing the application. Thus, this study aims to identify the knowledge structure of the application of HPC, enabling practical and policy support in various industrial fields. Co-word analysis is mainly used to establish the knowledge structure. We first collected 28,941 published papers related t
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Varavithya, Vara, and Supakit Prueksaaroon. "A Survey of High Performance Computing (HPC) Infrastructure in Thailand." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 17, no. 2 (2023): 255–64. http://dx.doi.org/10.37936/ecti-cit.2023172.251440.

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In the last decade, government organizations and private companies in Thailand have invested considerably in computing resources. Research collaborations typically band together based on shared interests and propose projects to compete for funding. Thus, many institutions frequently use similar computing resources. A bird's eye view of high-performance computer infrastructure in Thailand is important in many ways. To the best of our knowledge and ability, we gathered information on government procurements of HPC resources in the past five years, which cover several organizations and ministries
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Okanda, Paul M. "A Sustainability Model for Continental Hybridization of High Performance Computing (HPC) in Africa." International Education Studies and Sustainability 3, no. 1 (2023): p53. http://dx.doi.org/10.22158/iess.v3n1p53.

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The potential for High-performance computing (HPC) opportunities in the areas of health, environment, energy, climate change, business and livelihood are immense in Africa. However, the lack of sufficient HPC facilities and capacity skills deficiencies continue to curtail its growth. This paper maps the status of HPC facilities in Africa. Thereafter based on a review of various business and funding models, it suggests a hybridization model as a way for building sustainable HPC infrastructures across the continent to provide support for teaching and learning, research and education. The main co
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