A data and task parallel image processing environment

Abstract

The paper presents a data and task parallel environment for parallelizing low-level image processing applications on distributed memory systems. Image processing operators are parallelized by data decomposition using algorithmic skeletons. At the application level we use task decomposition, based on the Image Application Task Graph. In this way, an image processing application can be parallelized both by data and task decomposition, and thus beter speed-ups can be obtained. The framework is implemented using C and MPI-Panda library and it can be easily ported to other distributed memory systems.