This research focuses on the integration of performance testing into the unit testing phase for High-Performance Computing (HPC) software, emphasizing its importance in ensuring optimal implementations and diagnosing performance regressions. In traditional unit testing, functional aspects are assessed, but performance testing is often deferred to higher testing levels. The absence of performance testing at the unit level in HPC can lead to significant computational efficiency issues, challenging to diagnose and address. The project aims to develop a Julia package for a Performance Regression Unit Test Framework, seamlessly integrating with Julia's ecosystem and specifically made to be easy to integrate in HPC projects. By employing modern software development practices, the framework seeks to create a user-friendly, interpretable, robust, and efficient performance testing infrastructure. The research's significance lies in enhancing the reliability and performance of critical HPC software, promoting early detection and mitigation of performance issues, and advocating for best practices in software development for sustainability and maintainability in the Julia environment. Ultimately, the framework aims to bridge the gap between unit and performance testing in the HPC domain, contributing to improved software reliability, interpretability, and performance.