Sharing GPUs and Programmable Switches in a Federated Testbed with SHARY
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913672744402944 |
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| author | Salsano, Stefano Mayer, Andrea Lungaroni, Paolo Loreti, Pierpaolo Bracciale, Lorenzo Detti, Andrea Orazi, Marco Giaccone, Paolo Risso, Fulvio Cornacchia, Alessandro Chiasserini, Carla Fabiana |
| author_facet | Salsano, Stefano Mayer, Andrea Lungaroni, Paolo Loreti, Pierpaolo Bracciale, Lorenzo Detti, Andrea Orazi, Marco Giaccone, Paolo Risso, Fulvio Cornacchia, Alessandro Chiasserini, Carla Fabiana |
| contents | Federated testbeds enable collaborative research by providing access to diverse resources, including computing power, storage, and specialized hardware like GPUs, programmable switches and smart Network Interface Cards (NICs). Efficiently sharing these resources across federated institutions is challenging, particularly when resources are scarce and costly. GPUs are crucial for AI and machine learning research, but their high demand and expense make efficient management essential. Similarly, advanced experimentation on programmable data plane requires very expensive programmable switches (e.g., based on P4) and smart NICs.
This paper introduces SHARY (SHaring Any Resource made easY), a dynamic reservation system that simplifies resource booking and management in federated environments. We show that SHARY can be adopted for heterogenous resources, thanks to an adaptation layer tailored for the specific resource considered. Indeed, it can be integrated with FIGO (Federated Infrastructure for GPU Orchestration), which enhances GPU availability through a demand-driven sharing model. By enabling real-time resource sharing and a flexible booking system, FIGO improves access to GPUs, reduces costs, and accelerates research progress. SHARY can be also integrated with SUP4RNET platform to reserve the access of P4 switches. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_18840 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sharing GPUs and Programmable Switches in a Federated Testbed with SHARY Salsano, Stefano Mayer, Andrea Lungaroni, Paolo Loreti, Pierpaolo Bracciale, Lorenzo Detti, Andrea Orazi, Marco Giaccone, Paolo Risso, Fulvio Cornacchia, Alessandro Chiasserini, Carla Fabiana Networking and Internet Architecture Federated testbeds enable collaborative research by providing access to diverse resources, including computing power, storage, and specialized hardware like GPUs, programmable switches and smart Network Interface Cards (NICs). Efficiently sharing these resources across federated institutions is challenging, particularly when resources are scarce and costly. GPUs are crucial for AI and machine learning research, but their high demand and expense make efficient management essential. Similarly, advanced experimentation on programmable data plane requires very expensive programmable switches (e.g., based on P4) and smart NICs. This paper introduces SHARY (SHaring Any Resource made easY), a dynamic reservation system that simplifies resource booking and management in federated environments. We show that SHARY can be adopted for heterogenous resources, thanks to an adaptation layer tailored for the specific resource considered. Indeed, it can be integrated with FIGO (Federated Infrastructure for GPU Orchestration), which enhances GPU availability through a demand-driven sharing model. By enabling real-time resource sharing and a flexible booking system, FIGO improves access to GPUs, reduces costs, and accelerates research progress. SHARY can be also integrated with SUP4RNET platform to reserve the access of P4 switches. |
| title | Sharing GPUs and Programmable Switches in a Federated Testbed with SHARY |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2501.18840 |