Distributed quantum computing integrated into high-performance computing environments
High-Performance Computing (HPC) has historically served as the primary engine for scientific advancement, enabling complex simulations ranging from meteorological prediction to protein folding or drug discovery. For decades, the exponential growth in computational power was sustained by the empiric...
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| Formato: | tesis doctoral |
| Fecha de publicación: | 2026 |
| País: | España |
| Recursos: | Universidad de Santiago de Compostela (USC) |
| Repositorio: | Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:minerva_____::1fdd068bd86860daa51aafd7e697977d |
| Acesso em linha: | https://hdl.handle.net/10347/46765 |
| Access Level: | acceso abierto |
| Palavra-chave: | quantum computing high-performance computing distributed quantum computing quantum network quantum software 330406 Arquitectura de ordenadores 120311 Logicales de ordenadores |
| Resumo: | High-Performance Computing (HPC) has historically served as the primary engine for scientific advancement, enabling complex simulations ranging from meteorological prediction to protein folding or drug discovery. For decades, the exponential growth in computational power was sustained by the empirical axioms of Moore’s Law and Dennard scaling. However, in the last decade, these principles have begun to exhibit unambiguous signs of saturation. The fundamental physical, thermodynamic, and quantum limitations of silicon transistors have compelled the industry to abandon frequency scaling in favor of massive parallelism and architectural heterogeneity. Consequently, contemporary top-tier supercomputers are no longer homogeneous machines, but complex clusters that integrate multicore Central Processing Units (CPU) with specialized accelerators such as Graphics Processing Units (GPU) or FPGAs. |
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