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LLM assistant improves HPC user support by querying documentation and tickets

Researchers have developed an agentic LLM assistant designed to improve user support for high-performance computing (HPC) environments. This assistant leverages retrieval-augmented generation (RAG) on live documentation and a Llama 3-8B model fine-tuned with QLoRA on historical support tickets. The system aims to answer user queries by drawing from existing documentation and resolved tickets, addressing the difficulty users face in navigating these resources. Evaluations on held-out tickets from Purdue University's Rosen Center for Advanced Computing showed that fine-tuning on rewritten ticket resolutions significantly improved agreement with the center's resolutions, outperforming the base model. AI

IMPACT This research demonstrates a practical application of LLMs in specialized technical support, potentially improving efficiency and user experience in HPC environments.

RANK_REASON The cluster contains an academic paper detailing a novel LLM application for a specific domain. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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LLM assistant improves HPC user support by querying documentation and tickets

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The cluster contains an academic paper detailing a novel LLM application for a specific domain. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Elham J. Barezi, Primus C Kabuo, Niveditha Nerella ·

    Before the Ticket: Grounding HPC User Support in Documentation and Resolved Tickets with an Agentic LLM Assistant

    arXiv:2610.31703v1 Announce Type: cross Abstract: Most questions that reach an HPC help desk have already been answered in the center's user guides or in a ticket someone else filed last semester; users still file new tickets because the guides are hard to navigate and the ticket…