Summary form only given, as follows. With the increasing use of such methods as dynamic simulations, free energy perturbation and large-molecule ab initio calculations, chemical researchers find increasing frustration in the use of conventional computers to solve their problems. These machines are either too slow or too expensive to be practical for everyday use. However, the advent of parallel computer architectures and parallel algorithms offers a solution to this problem. In addition, the development of tools that detect dependencies and automatically create concurrent code makes the programming of these machines accessible to everyone. The author discusses these tools and their application to widely used chemical codes, such as AMBER and GAUSSIAN. The use of high performance graphics machines in computational chemistry is also discussed. An application, simultaneously running AMBER and GRAMPS, and an analysis program is shown. >