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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://arxiv.org/abs/2509.22679 |
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| _version_ | 1866909810188877824 |
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| author | Benhari, Abdessalam Denneulin, Yves Desprez, Frédéric Dufossé, Fanny Trystram, Denis |
| author_facet | Benhari, Abdessalam Denneulin, Yves Desprez, Frédéric Dufossé, Fanny Trystram, Denis |
| contents | The demand in computing power has never stopped growing over the years. Today, the performance of the most powerful systems exceeds the exascale. Unfortunately, this growth also comes with ever-increasing energy costs, leading to a high carbon footprint. This paper investigates the evolution of high performance systems in terms of carbon emissions. A lot of studies focus on Top500 (and Green500) as the tip of an iceberg to identify trends in the domain in terms of computing performance. We propose here to go further in considering the whole span life of several large scale systems and to link the evolution with trajectory toward 2030. More precisely, we introduce the energy mix in the analysis of Top500 systems and we derive a predictive model for estimating the weight of HPC for the next 5 years. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_22679 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Analysis of the carbon footprint of HPC Benhari, Abdessalam Denneulin, Yves Desprez, Frédéric Dufossé, Fanny Trystram, Denis Distributed, Parallel, and Cluster Computing The demand in computing power has never stopped growing over the years. Today, the performance of the most powerful systems exceeds the exascale. Unfortunately, this growth also comes with ever-increasing energy costs, leading to a high carbon footprint. This paper investigates the evolution of high performance systems in terms of carbon emissions. A lot of studies focus on Top500 (and Green500) as the tip of an iceberg to identify trends in the domain in terms of computing performance. We propose here to go further in considering the whole span life of several large scale systems and to link the evolution with trajectory toward 2030. More precisely, we introduce the energy mix in the analysis of Top500 systems and we derive a predictive model for estimating the weight of HPC for the next 5 years. |
| title | Analysis of the carbon footprint of HPC |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2509.22679 |