Urban cities are usually densely populated and have massive infrastructure. They consume a lot of energy and generate pollution. Urban form and structure interact with the environment in a complex way. There is transfer of energy between buildings and the ground layer. Winds flow through the urban street canyons, affecting evaporation, temperature and pollution dispersion. The effects of such complex interactions are still not widely known or understood. How well an urban space disperses pollution, or requires energy for heating or cooling is potentially impacted by many components, such as where the buildings are located with respect to each other, which materials the buildings are constructed from, or where trees or parks are placed. The aim of the Genusis project is to provide a tool for urban planners that they can utilize to understand such impacts and to assist them in taking design decisions accordingly. Even with just a few choices in building locations or tree types the number of possible configurations is vast. Running the simulations on many thousand of these configurations is a huge problem on its own and truly not feasible for urban planners to use in their daily routines.This thesis strives towards tackling that problem by developing a computational environment in which specifying these configurations is easy and can compute potential solutions to the problems within an acceptable time frame using multiple machines. A simple and yet powerful language is created to let urban planners control the simulations and specify the configurations. In order to reduce the computational time, Berkeley Open Infrastructure for Network Computing (BOINC) is used to harness all available computational resources. Experiments were conducted to analyze the implementation and performance of the system. The results obtained validate the implementation and indicate a significant performance gain.