Performance analysis of median filtering on Meiko - a distributed multiprocessor system

Abstract

This paper presents the performance analysis of realizing median filtering on a distributed multiprocessor system. The results of the performance analysis give a good indication of the performance gain in using multi-processor for median filtering over uni-processor. Such performance gain is proportional to the problem size as shown by varying the size of the image. Furthermore, through the analysis, it is clear that the computation time and inter-processor communications scale well with the number of processors in the system. However, the overall system performance does not have such behavior because of the initialization overhead dominating the computation time as the number of processors increases beyond a certain point. It is because of this relationship that an optimal performance is achievable with a certain number of processors. It is also found that this number varies with the problem size. In addition, the subimage model is found to be an acceptable approach for this type of processing as only the necessary parts of the image are sent to the other processors. The master and slave scheme proves to be easy for programming, control and data manipulation. As a whole, this type of non-linear processing seems to fit well into the MIMD architecture.