AI Factories: It's time to rethink the Cloud-HPC divide
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arXiv
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| Autores principales: | , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866914039858200576 |
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| author | Lopez, Pedro Garcia Pons, Daniel Barcelona Copik, Marcin Hoefler, Torsten Quiñones, Eduardo Malawski, Maciej Pietzutch, Peter Marti, Alberto Timoudas, Thomas Ohlson Slominski, Aleksander |
| author_facet | Lopez, Pedro Garcia Pons, Daniel Barcelona Copik, Marcin Hoefler, Torsten Quiñones, Eduardo Malawski, Maciej Pietzutch, Peter Marti, Alberto Timoudas, Thomas Ohlson Slominski, Aleksander |
| contents | The strategic importance of artificial intelligence is driving a global push toward Sovereign AI initiatives. Nationwide governments are increasingly developing dedicated infrastructures, called AI Factories (AIF), to achieve technological autonomy and secure the resources necessary to sustain robust local digital ecosystems.
In Europe, the EuroHPC Joint Undertaking is investing hundreds of millions of euros into several AI Factories, built atop existing high-performance computing (HPC) supercomputers. However, while HPC systems excel in raw performance, they are not inherently designed for usability, accessibility, or serving as public-facing platforms for AI services such as inference or agentic applications. In contrast, AI practitioners are accustomed to cloud-native technologies like Kubernetes and object storage, tools that are often difficult to integrate within traditional HPC environments.
This article advocates for a dual-stack approach within supercomputers: integrating both HPC and cloud-native technologies. Our goal is to bridge the divide between HPC and cloud computing by combining high performance and hardware acceleration with ease of use and service-oriented front-ends. This convergence allows each paradigm to amplify the other. To this end, we will study the cloud challenges of HPC (Serverless HPC) and the HPC challenges of cloud technologies (High-performance Cloud). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_12849 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AI Factories: It's time to rethink the Cloud-HPC divide Lopez, Pedro Garcia Pons, Daniel Barcelona Copik, Marcin Hoefler, Torsten Quiñones, Eduardo Malawski, Maciej Pietzutch, Peter Marti, Alberto Timoudas, Thomas Ohlson Slominski, Aleksander Distributed, Parallel, and Cluster Computing Artificial Intelligence The strategic importance of artificial intelligence is driving a global push toward Sovereign AI initiatives. Nationwide governments are increasingly developing dedicated infrastructures, called AI Factories (AIF), to achieve technological autonomy and secure the resources necessary to sustain robust local digital ecosystems. In Europe, the EuroHPC Joint Undertaking is investing hundreds of millions of euros into several AI Factories, built atop existing high-performance computing (HPC) supercomputers. However, while HPC systems excel in raw performance, they are not inherently designed for usability, accessibility, or serving as public-facing platforms for AI services such as inference or agentic applications. In contrast, AI practitioners are accustomed to cloud-native technologies like Kubernetes and object storage, tools that are often difficult to integrate within traditional HPC environments. This article advocates for a dual-stack approach within supercomputers: integrating both HPC and cloud-native technologies. Our goal is to bridge the divide between HPC and cloud computing by combining high performance and hardware acceleration with ease of use and service-oriented front-ends. This convergence allows each paradigm to amplify the other. To this end, we will study the cloud challenges of HPC (Serverless HPC) and the HPC challenges of cloud technologies (High-performance Cloud). |
| title | AI Factories: It's time to rethink the Cloud-HPC divide |
| topic | Distributed, Parallel, and Cluster Computing Artificial Intelligence |
| url | https://arxiv.org/abs/2509.12849 |