The need for parallel software for scientific computing is ever increasing. Supercomputers are not only being built with more processors, but parallel computers are also no longer limited to large machines owned and managed by high-performance computing centers; parallel desktop computers are increasingly widespread, and even laptop computers have multiple processors. Development of scientific computing software must adapt to these conditions as parallel computation becomes the norm rather than the exception. In the field of quantum chemistry, additional factors contribute to the need for parallelism. Quantum chemistry has become an indispensable tool for investigating chemical phenomena, and quantum chemical methods are employed widely in research across many chemical disciplines; this widespread use of quantum chemistry reinforces the importance of rapid turnaround computations, which can be addressed by parallel computing. Additionally, for quantum chemistry to continue to be an integral part of chemical research, quantum chemical methods must be applicable to the chemical systems of interest, including larger molecules, and parallelism can play an important role in extending the range of these methods. Parallel implementations can broaden the scope of conventional quantum chemical methods, whose computational cost scales as a high-degree polynomial in the molecular size, and enable the treatment of very large molecular systems with linear-scaling or reduced-scaling methods.