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Design space exploration of reconfigurable systems for calculating flying object's optimal noise reduction paths

Despite improved aerodynamic designs that decrease sound emission, the noise produced by flying objects is a problem because it propagates in large distances in the atmosphere. However, it is possible to describe sound propagation effectively with a parabolic differential equation and determine a path that minimizes noise emissions taking into consideration atmospheric and geographic data. This approach calculates noise propagation progressively in the propagation direction and gives accurate results even for large distances. This paper presents a reconfigurable system that solves the tridiagonal problem that results from the Crank-Nicolson function of the 2nd order parabolic equation. Generally tridiagonal algorithms do not allow parallelism in every level, and complicate parallel and/or reconfigurable hardware implementations. We show that reconfigurable hardware technology allows the fast and accurate implementation of such systems. We explore and present several architecture alternatives that pose different tradeoffs. We consider and evaluate different implementations in order to achieve the best possible parallelism and speed with reasonable cost. We find that a large Virtex-5 device is between 9 and 76 times faster than a current desktop PC, depending on the architecture used.