Real-Time Scheduling Models in Diverse Multi-core OpenMP Applications

This research presents some of the critical information required to understand the concept of parallel programming and the implementation of OpenMP in parallel programming. Parallelism is the preferred tool for expediting an algorithm, as demonstrated by the evolution of computing architectures (multi-core and many-core) towards a greater number of processing cores. The report will focus on OpenMP parallel programming models and further examine its implementation and features. Parallel programming OpenMP model is increasingly preferred for its ability to deliver real-time processing, thereby, meeting system requirements performance wise. Furthermore, the study of implementing OpenMP in enhancing the efficiency of 3D discontinuous deformation analysis (3D-DDA) for expansive simulation using parallel block Jacobi (BJ) and Pre-conditioned conjugate gradient (PCG) algorithms. The absence of synchronization of data in parallel programming makes the system more prone to errors in programming since the parallel environment is much more complicated than perceived. The studies performed will highlight how synchronization is managed using OpenMP model. In the field of biometrics, the most important issue faced in DNA sequencing and pattern discovery is locating the longest common subsequence (LCS) among sequences. To identify the LCS of DNA sequences, we will look into the solutions achieved using OpenMP tools based on CPU, that extend major improvements in processing speed, capital, and ubiquity, and the results based on the analysis are discussed.