MPI-based scalable computing platform for parallel numerical application

Abstract

Developing parallel numerical applications, such as simulators and solvers, involves a variety of challenges in dealing with data partitioning, workload balancing, data dependencies, and synchronization. Many numerical applications share the need for an underlying parallel framework for parallelization on multi-core/multi-machine hardware. In this thesis, a computing platform for parallel numerical applications is designed and implemented. The platform performs parallelization by multiprocessing over MPI library, and serves as a layer of abstraction that hides the complexities in dealing with data distribution and inter-process communication. It also provides the essential functions that most numerical application use, such as handling data-dependency, workload-balancing, and overlapping communication and computation. The performance evaluation of the parallel platform shows that it is highly scalable for large problems.