Ozer, Hayati UnsalTuncel, MehmetDuran, AhmetDuran, Fatih Said2026-01-052026-01-0520250920-85421573-0484https://doi.org/10.1007/s11227-025-08152-3https://hdl.handle.net/20.500.11779/3164Real-time computation of eigenvalues is valuable in science and engineering. This is possible via memory-efficient, scalable, robust, and high-performance algorithms when we take advantage of supercomputing. Baer wave equation arises from applying the separation of variables to the Helmholtz equation. When the Baer wave equation is discretized, a three-parameter eigenvalue problem is obtained. In this study, we consider the computationally challenging problem of finding eigenvalue tuples in a three-parameter eigenvalue problem reduced from the Baer wave equation. We solve this problem using a fused parameter optimization algorithm by implementing a dynamic thread-based computation in C and MATLAB. We achieved scaled speed-up for the dense coefficient matrices of the problem from the Baer wave equation to run up to 64 threads in our C implementation. To the best of our knowledge, this is the first study to solve the three-parameter eigenvalue problem using parallel thread-based computing.eninfo:eu-repo/semantics/closedAccessBaer Wave EquationThree-Parameter Eigenvalue ProblemThread-Based Parallel ComputingArticle10.1007/s11227-025-08152-3