High-Performance Computing: Evaluating Computing Paradigms, Scalability, and Real-World Applications Article Swipe
M. Bhattacharjee
,
Mohamed Muzni Mohamed Ziham
,
Rashid Khan
,
S. A. Usman
,
Mohamed Zeedhan
,
Ahmed M. Mohamed
,
Muhammad Noor‐ul‐Amin
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202504.0723.v1
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202504.0723.v1
High-Performance Computing (HPC) revolutionized the field of computational science by enabling it to process vast amounts of data and execute complex simulations at remarkable speed and efficiency. This paper describes various paradigms of computing, namely, client-server computing, distributed computing, cloud computing, and edge computing, and elaborates on their technology drivers. Particular focus is given to HPC, its architecture, programming models, performance metrics, scalability, and applications. The article highlights the significant impact of HPC to science in fields of medicine, biophysics, business, and engineering by facilitating paradigm-altering scientific discoveries, economic forecasting, and simulations of complex engineering. In addition, the article mentions challenges to deploying HPC, such as scalability, handling resources, and integration of multi-core processors. Through comparative analysis and benchmarking techniques, the research points to the necessity of continuous hardware and software innovations to make HPC systems efficient and sustainable. The study brings out the revolutionary potential of HPC in modern computing and its central role in solving the most complex computational problems in the modern age.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.20944/preprints202504.0723.v1
- https://www.preprints.org/frontend/manuscript/dc60983d638a21ebed178ea52ee68978/download_pub
- OA Status
- green
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409287628
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4409287628Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.20944/preprints202504.0723.v1Digital Object Identifier
- Title
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High-Performance Computing: Evaluating Computing Paradigms, Scalability, and Real-World ApplicationsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
-
2025-04-09Full publication date if available
- Authors
-
M. Bhattacharjee, Mohamed Muzni Mohamed Ziham, Rashid Khan, S. A. Usman, Mohamed Zeedhan, Ahmed M. Mohamed, Muhammad Noor‐ul‐AminList of authors in order
- Landing page
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https://doi.org/10.20944/preprints202504.0723.v1Publisher landing page
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https://www.preprints.org/frontend/manuscript/dc60983d638a21ebed178ea52ee68978/download_pubDirect link to full text PDF
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YesWhether a free full text is available
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-
greenOpen access status per OpenAlex
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https://www.preprints.org/frontend/manuscript/dc60983d638a21ebed178ea52ee68978/download_pubDirect OA link when available
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Scalability, Computer science, Distributed computing, Supercomputer, End-user computing, Unconventional computing, Computational science, Computer architecture, Parallel computing, Utility computing, Cloud computing, Operating system, Cloud computing securityTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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30Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.benchmarking | 118 |
| abstract_inverted_index.discoveries, | 87 |
| abstract_inverted_index.engineering. | 94 |
| abstract_inverted_index.facilitating | 84 |
| abstract_inverted_index.forecasting, | 89 |
| abstract_inverted_index.scalability, | 62, 106 |
| abstract_inverted_index.sustainable. | 138 |
| abstract_inverted_index.applications. | 64 |
| abstract_inverted_index.architecture, | 57 |
| abstract_inverted_index.client-server | 35 |
| abstract_inverted_index.computational | 7, 160 |
| abstract_inverted_index.revolutionary | 144 |
| abstract_inverted_index.revolutionized | 3 |
| abstract_inverted_index.High-Performance | 0 |
| abstract_inverted_index.paradigm-altering | 85 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.13155942 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |