Parallelization using task parallel library with task-based programming model

In order to reduce the complexity of traditional multithreaded parallel programming, this paper explores a new task-based parallel programming using the Microsoft .NET Task Parallel Library (TPL). Firstly, this paper proposes a custom data partitioning optimization method to achieve an efficient data parallelism, and applies it to the matrix multiplication. The result of the application supports the custom data partitioning optimization method. Then we develop a task parallel application: Image Blender, and this application explains the efficiency and pitfall aspects associated with task parallelism. Finally, the paper analyzes the performance of our applications. Experiments results show that TPL can dramatically alleviate programmer burden and boost the performance of programs with its task-based parallel programming mechanism.