Publication

Abstract : String matching refers to the search of each and every occurrence of a string in another string. Nowadays, this issue presents itself in various segments in a great deal, starting from standard programs for text editing and processing, through databases and all the way to their various applications in other sciences. There are numerous different efficient algorithms to solve this problem. One of the efficient algorithms is Rabin-Karp algorithm which has complexity of O(m(n-m+l)) whereas the complexity of proposed advanced Rabin-Karp algorithm is O(n-m). However, the main focus of this research is to apply the concepts of parallelism to improve the performance of the algorithm. There are lots of parallel processing Application Programming Interfaces (APIs) available, like OpenMP, MPI, CUDA MapReduce, etc. out of these we have chosen OpenMP and CUDA to achieve parallelism. Comparison of the results of both serial and parallel implementations will give us insights into how performance and efficiency is achieved through various techniques of parallelism.