Image processing applications performance study on Cell BE and Blue Gene/L
Two image processing applications, edge detection and image resizing, are studied in this paper on two HPC platforms namely the Cell BE and the Blue Gene/L machines. In this paper we focus on the performance scalability of the studied applications. Our results show that the scale of the problem to be solved highly affects the fitness of the platform. If the data set size is to fit into the Cell core, the fast on-chip inter-core communication of a multi-core system pays back for its high technology design. On the other hand, the overhead of the distant communication in the massively parallel Blue Gene/L machine will only show its benefits for huge data set size that otherwise mandates multiple round-trip data communications between the local memory of a core and main memory. Copyright (C) 2010 John Wiley & Sons, Ltd.
applications computational and programming models performance evaluation