Generating Architecture-Agnostic Performance Tests from Functional Unit Tests

We present a methodology for automated performance regression testing at the unit level, designed to integrate seamlessly into the development workflow of high-performance computing (HPC) applications. The proposed framework emphasizes the integration of performance tests with existing functional unit tests by leveraging their shared structure, thereby enabling the development of performance test suites with minimal developer effort and supporting the early detection of performance degradations. As a proof of concept, we implement and release the framework as a publicly available Julia package. It generates architecture-agnostic test suites that remain valid across heterogeneous hardware environments. To demonstrate its effectiveness, we apply it to representative HPC use cases, including memory throughput analysis in stencil-based computations and roofline modeling of a sparse linear system solver. Experiments conducted on a diverse set of CPU and GPU architectures confirm the framework’s ability to detect performance regressions consistently, validating its potential for use in continuous performance testing pipelines.