Phase unwrapping is an integral part of multiple algorithms with diverse applications. Detailed phase unwrapping is also necessary for achieving high accuracy metric sensing using laser feedback based self-mixing interferometry (SMI). Among SMI specific phase unwrapping approaches, a technique called Improved Phase Unwrapping Method (IPUM) provides the highest accuracy. However, due to its complex, sequential, and compute-intensive nature, this method requires a high performance computing architecture, capable of scalable parallel processing so that such a high accuracy algorithm can be used for high bandwidth sensing applications. In this work, the existing sequential IPUM C program is parallelized by using hybrid OpenMP/MPI (Open Multi-Processing/Message Passing Interface) parallel programming models and tested on Barcelona Supercomputing Center Nord-III Supercomputer. The computational performance of the proposed parallel-hybrid IPUM algorithm is compared with existing IPUM sequential code by executing multi-core and uni-core processor architecture respectively. While comparing the performance of sequential IPUM with the parallel-hybrid IPUM algorithm on 16 nodes of Nord-III supercomputer, the results show that the parallelhybrid algorithm gets 345.9x times performance improvement as compared to IPUM's standard, sequential implementation on a single node system. The results show that the parallel-hybrid version of IPUM gives a scalable performance for different target velocities and a different number of processing cores.