Proposed and led development of an AI-driven tool to assist AMDGPU kernel developers in triaging errors from Linux kernel logs — reducing manual effort and improving issue resolution speed across IQE, CVS, and KMD teams.
Proposed the AI log analysis concept and secured leadership approval for cross-team integration with IQE, CVS, and Linux kernel development teams.
Designed and implemented a Go-based framework to parse and categorize AMDGPU kernel logs before passing structured data to an LLM for actionable insights.
Built end-to-end workflow: kernel log capture → structured parsing → LLM analysis → developer-facing triage recommendations.
Reduced manual log triage effort for kernel developers during system bring-up and post-silicon validation of MI-Series GPUs.