Effects of architecture implementation on DFT algorithm performance

Abstract

Five major DFT algorithms were evaluated on seven different computers. The relative performances of these algorithms were related to the architecture of each computer by finding a relationship between the execution time and the instruction counts. The relative performance of these algorithms on other computers is predicted, based on the knowledge of the computer architecture. On certain implementations, data transfers are more important than floating-point additions and multiplications when comparing DFT algorithms. On the average, data transfers account for a greater percentage of the execution time than floating-point operations,