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| Natura: | Recurso digital |
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Zenodo
2025
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| Accesso online: | https://doi.org/10.5281/zenodo.17971086 |
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| _version_ | 1866901540815503360 |
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| author | Kawauchi, Satoshi |
| author_facet | Kawauchi, Satoshi |
| contents | <p>This paper proposes a next-generation computational resource sharing system that enables a large number of users to simultaneously utilize a small number of high-performance computing devices.</p> <p>Its key feature is the integrated control of second-level dynamic reallocation of computational resources such as CPU, GPU, and memory, combined with AI-based demand prediction, automatic switching of processing models, and live migration.</p> <p>By overcoming the performance degradation and high costs associated with conventional VDI and DaaS, the paper demonstrates the feasibility of a new PC infrastructure in which many users can perform high-load processing on a single machine.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17971086 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Proposal of a Multi-User Concurrent High-Performance Computing System with Dynamic Resource Allocation Kawauchi, Satoshi <p>This paper proposes a next-generation computational resource sharing system that enables a large number of users to simultaneously utilize a small number of high-performance computing devices.</p> <p>Its key feature is the integrated control of second-level dynamic reallocation of computational resources such as CPU, GPU, and memory, combined with AI-based demand prediction, automatic switching of processing models, and live migration.</p> <p>By overcoming the performance degradation and high costs associated with conventional VDI and DaaS, the paper demonstrates the feasibility of a new PC infrastructure in which many users can perform high-load processing on a single machine.</p> |
| title | Proposal of a Multi-User Concurrent High-Performance Computing System with Dynamic Resource Allocation |
| url | https://doi.org/10.5281/zenodo.17971086 |