Supercomputing in compression of temporal fringe pattern analysis

Abstract

Temporal fringe pattern analysis is invaluable in transient phenomena studies but necessitates long processing times. Here, we describe a parallel computing strategy based on the single program multiple data (SPMD) model and hyper-threading processor technology to reduce the execution time. In a two-node cluster workstation configuration, we found that execution periods reduced by 1.6 times using four virtual processors. To allow even lower execution times with increasing number of processors, the time allocated for data transfer, data read, and waiting should be minimized. Parallel or super computing is found here to present a feasible approach to reduce execution times in temporal fringe pattern analysis.