Abstract
There are many fields of science where the Two- Point Angular Correlation Function (TPACF) is used, such as in statistics, and astronomy. In cosmology, it is used to calculate the distribution of galaxies. The number of galaxies in the Universe is more than 170 billion in a limited region of 13.8 billion light years distance. To compute the distribution of such a large number of galaxies requires huge computational resources. This paper adopts a parallel processing approach to compute angular correlation function. The distribution of galaxies using the TPACF is computed by using a message passing programming model in a cluster based parallel processing environment. To get a better speedup, we adopt a coarse grain approach in which the computation is split among different processes. Each process gets a fixed number of data lines and performs the required computation. The results indicate that the parallel processing of the TPACF provides a significant speedup in terms of execution time.