국내 NPU 환경에서는 PyTorch, vLLM 등 인공지능 연산 프레임워크를 지원하기 위하여 펌웨어, 컴파일러를 포함한 관련 소프트웨어 스택의 업데이트가 지속적으로 수행되고 있다. 이에 따라 NPU를 활용하는 개발자 및 연구자는 업데이트가 반영된 때마다 새롭게 추가된 기능이 기존 시스템에서 안정적으로 동작하는지, 기 사용 중인 코드가 정상적으로 수행되는지를 검증해야 하는 부담을 수반한다. 본 논문에서는 이러한 문제를 완화하기 위하여 소프트웨어 버전에 따른 시스템의 동작 여부 및 정상 운용 수준을 체계적으로 관리 및 분석할 수 있는 프레임워크를 제안한다. 제안하는 프레임워크는 시스템의 버전 관리와 소스 코드의 형상 관리를 통합적으로 수행하는 동시에, 오류 발생 시 로그 원인을 추적할 수 있도록 설계하였다. 아울러 제안 프레임워크의 실효성을 검증하기 위한 선행 연구로서, 해당 시스템의 구축 과정을 상세히 기술한다.
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