Parallel Transition Localization

Microprocessor clock rates-which for three decades doubled about every 18 months-have essentially stopped increasing. Instead the number of processor cores (identical processing units capable of all usual microprocessor functions) in a microprocessor is increasing exponentially with time. In order to increase performance as the number of cores increase, measurement analysis software will have to take advantage of this parallelism. The purpose of this paper is to study one example of a measurement analysis having serial dependencies among the input data and to show that there is a practical parallel algorithm despite the data dependencies within the measured time series. The measurement analysis studied is transition localization in digital signals. A parallel scan-type algorithm is presented. Results of applying the parallel algorithm on both synthetic data and actual measured data are presented, and the speedup obtained on an eight core processor analyzed.