In subsequent phases, longitudinal sections of the cube are processed together. In such situations, data remapping aims to rearrange the data layout in between the phases so as to reduce the total execution time. In this paper, we present efficient data remapping algorithms for several frequently occurring data redistribution patterns in embedded signal processing applications. We design efficient communication schedules whose performance scales well with system size. Some of the distribution patterns also arise in other application domains, and are part of the HPF standard.
Examples are the block, cyclic and blockcyclic distributions.
Thus, our algorithms can be used in a wide class of applications. In some scenarios, the overhead incurred in performing the remapping operation might be larger than the performance benefit due to remapping. Our approach to designing efficient communication algorithms consists of using a computational model to evaluate the overhead in data remapping. We assume that Ts is typically much larger than td. Thus, our redistribution algorithms aim to decrease the number of message startups, although at the cost of increased data transmission.