The Missing Adapter Layer for Research Computing
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866917371334098944 |
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| author | Li, Bowen Xie, Jiazhu Wang, Chelsea D'Aloia, Alessandro Umberto Xu, Ziqi Han, Fengling |
| author_facet | Li, Bowen Xie, Jiazhu Wang, Chelsea D'Aloia, Alessandro Umberto Xu, Ziqi Han, Fengling |
| contents | Higher Degree by Research (HDR) candidates increasingly depend on cloud-provisioned virtual machines and local GPU hardware for their computational experiments, yet a persistent and under-addressed gap exists between having compute resources and using them productively. Cloud and infrastructure teams can provision virtual machines, but the path from a raw VM to a reproducible, GPU-ready research environment remains a significant barrier for researchers who are domain experts, not systems engineers. We identify this gap as a missing adapter layer between cloud provisioning and interactive research work. We present a lightweight, open-source solution built on k3s and Coder that implements this adapter layer and is already in active use in our research workspace environment. Our CI/CD pipeline connects GitHub directly to the local cluster, deploying research projects in under five minutes. We define a concrete metrics framework for evaluating this layer -- covering deployment latency, environment reproducibility, onboarding friction, and resource utilisation -- and establish baselines against which improvements can be measured. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_23942 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The Missing Adapter Layer for Research Computing Li, Bowen Xie, Jiazhu Wang, Chelsea D'Aloia, Alessandro Umberto Xu, Ziqi Han, Fengling Computational Engineering, Finance, and Science Distributed, Parallel, and Cluster Computing Higher Degree by Research (HDR) candidates increasingly depend on cloud-provisioned virtual machines and local GPU hardware for their computational experiments, yet a persistent and under-addressed gap exists between having compute resources and using them productively. Cloud and infrastructure teams can provision virtual machines, but the path from a raw VM to a reproducible, GPU-ready research environment remains a significant barrier for researchers who are domain experts, not systems engineers. We identify this gap as a missing adapter layer between cloud provisioning and interactive research work. We present a lightweight, open-source solution built on k3s and Coder that implements this adapter layer and is already in active use in our research workspace environment. Our CI/CD pipeline connects GitHub directly to the local cluster, deploying research projects in under five minutes. We define a concrete metrics framework for evaluating this layer -- covering deployment latency, environment reproducibility, onboarding friction, and resource utilisation -- and establish baselines against which improvements can be measured. |
| title | The Missing Adapter Layer for Research Computing |
| topic | Computational Engineering, Finance, and Science Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2603.23942 |