AI-Assisted Computational Reproducibility on the FABRIC Testbed
Computational reproducibility remains difficult despite being central to scientific research. In this paper, we show how the international FABRIC testbed, combined with a large language model (LLM) coding agent through LoomAI, can simplify reproducing published experiments across multiple domains. We reproduced three case studies on FABRIC, covering BBR-family congestion-control evaluations, LAMMPS molecular dynamics scaling benchmarks on a CPU-only MPI cluster, and stress protein homeostasis genomics pipelines. Rather than focusing only on matching numerical outputs, we evaluate whether the reproduced experiments support the same scientific conclusions as the original studies. The AI ass...
| Authors | Komal Thareja, Paul Ruth, Berent Aldikacti et al. |
|---|---|
| Primary category | cs.DC |
| Published | 24 June 2026 |
| Last updated at source | 7 October 2026 |
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