Reionization is the process by which the neutral intergallactic medium of the early universe was ionized by the first galaxies, and took place somewhere between roughly redshift 30 and redshift 6, or from 100~Myr into the universe to 1~Gyr. The details of this transition are still not well understood, but observational constraints suggest that reionization happened faster than naive estimates would suggest. In this thesis, we investigate the theory that galaxies which form their stars in short bursts could complete reionization faster than galaxies which emit their photons continuously over their lifespans.

We began investigating this theory with a semi-analytic model of the early universe. We used analytic methods to model the expansion of \HII (ionized hydrogen) regions around isolated galaxies, as well as the behavior of the remnant \HII regions after star formation ceases. We then compiled assortments of galaxies matching dark matter simulation profiles and associated each with an \HII region that could either grow continuously or grow quickly before entering a dormant period of recombination. These tests indicated that the remnants of bursty star formation had lower overall recombination rates than those of continuously expanding \HII regions, and that these remnants could allow for ionizing radiation from more distant sources to influence ionization earlier.

We decided that the next step towards demonstrating the differences between continuous and bursty star formation would require the use of a more accurate model of the early universe. We chose a photon conserving ray tracing algorithm which follows the path of millions of rays from each galaxy and calculates the ionization rate at every point in a uniform 3D grid. The massive amount of computation required for such an algorithm led us to choose MPI as the framework for building our simulation. MPI allowed us to break the grid into 8 sub-volumes, each of which could be assigned to a node on a supercomputer. We then used CUDA to track the millions of rays, with each of the thousands of CUDA cores handling a single ray. Creating my own simulation library would afford us complete control over the distribution and time dependence of ionizing radiation emission, which is critical to isolating the effect of bursty star formation on reionization.

Once we had completed, we conducted a suite of simulations across a selection of model parameters using this library. Every set of model parameters we selected corresponds to two models, one continuous and one bursty. This selection allowed us to isolate the effect of bursty star formation on the results of the simulations. We found that the effects we hoped to see were present in our simulations, and obtained simple estimates of the size of these effects.