Developing a high-performance quantum chemistry program with a dynamic scripting language

We discuss the use of dynamic programming languages such as Python to develop first-principles quantum chemistry programs for high-performance computing environments. Dynamic scripting programming languages, in general, have distinct advantages in terms of developer productivity over compiled languages such as C/C++ and Fortran, because of their ease of use and extensive libraries. Such "static" languages have clear performance advantages due to their optimizing compilers. In particular, we report on our experience developing a quantum chemistry program that attempts to combine the best of both worlds by using language binding techniques to bridge different programming languages.