CEDCMar 25

The Missing Adapter Layer for Research Computing

arXiv:2603.2394283.6h-index: 2Has Code
AI Analysis

This addresses a domain-specific problem for HDR candidates and researchers by reducing onboarding friction and improving reproducibility in research computing environments.

The paper tackles the gap between cloud-provisioned compute resources and productive use by researchers, presenting a lightweight open-source solution that deploys research projects in under five minutes.

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.

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