The past few decades have seen the development of numerous aeroacoustic prediction codes. Algorithms based on the Lighthill acoustic analogy, and the Ffowcs Williams-Hawkings (FW-H) equation in particular, are now widely used in industry to predict the aeroacoustic field generated by aerospace vehicles and non-aerospace machinery. In a trend similar to the growth of cluster computing, the size and scale of aeroacoustic problems being computed with these codes has increased dramatically in recent years. A discussion of different algorithms to reduce memory and enable real-time noise prediction is presented. The results of a new data structure and computation algorithm recently implemented in the aeroacoustic prediction code PSU-WOPWOP are shown to significantly decrease the memory requirements - a useful outcome for large permeable surface computations. Only small changes to the algorithm are required to enable the real-time prediction of helicopter rotor noise.