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 parallel-hybrid 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.

相位展开是具有多种应用程序的多种算法的组成部分。使用基于激光反馈的自混合干涉仪（SMI）来实现高精度的度量传感，也需要详细的相位展开。在特定于SMI的相位解缠方法中，一种称为改进相位解缠方法（IPUM）的技术可提供最高的精度。但是，由于其复杂，顺序和计算密集的特性，该方法需要一种高性能的计算体系结构，该体系结构能够进行可伸缩的并行处理，因此这种高精度算法可用于高带宽传感应用。在这项工作中 现有的顺序IPUM C程序使用混合的OpenMP / MPI（开放式多处理/消息传递接口）并行编程模型进行并行化，并在Barcelona超级计算中心Nord-III超级计算机上进行了测试。通过分别执行多核和单核处理器体系结构，将所提出的并行混合IPUM算法的计算性能与现有IPUM顺序代码进行比较。在对Nord-III超级计算机的16个节点上的顺序IPUM和并行混合IPUM算法的性能进行比较时，结果表明，与IPUM的标准，在单个节点上顺序执行相比，并行混合算法的性能提高了345.9倍。系统。