How to Build CI/CD Pipelines Designed Specifically for GPU Validation

GPU validation requires far more than simply attaching a GPU runner to a standard CI/CD pipeline, as failures can depend on specific driver versions, firmware, OS, or workload combinations. A practical framework called TRACE — covering Test planning, Resource matching, Artifact traceability, Classification, and Evidence-based quality gates — offers a structured approach to this challenge. The core principle is that every decision in the pipeline must be traceable from the original code change through the hardware environment, test results, and final quality gate. Because compatible GPU hardware is limited and costly, the goal is not to run every possible test combination but to generate reliable evidence efficiently enough to support engineering decisions. The framework addresses three key questions for each commit: what to test, where to run it, and how much evidence is needed before a change can proceed.