Abstract

This paper describes the high performance computing (HPC) of document search engines that are vectorizing each classified document. The parallelization is achieved by exploiting the parallel and distributed computing environments of collective multiple processes that are implemented by using Java message passing interface (MPI) bindings of openMPI. A parallelism model of manager/worker is implemented for obtaining the load balancing, as well as the analysis and benchmarking are achieved in our parallelism profiling model that is designed for the implementation. Two output of the experimental results are shown: the parallel processing performance with the efficiency of 80%, and the profiling results that show the utilizations and overheads in our parallelism model.