Tcl is the original embeddable dynamic language. Intro-duced in 1990, Tcl has been the foundation of the script-ing interface of the popular biomolecular visualization and analysis program VMD since 1995 and was extended to the parallel molecular dynamics program NAMD in 1999. The two programs together have over 200,000 users who have enjoyed for nearly two decades the stability and flexibility provided by Tcl. VMD users can implement or extend par-allel trajectory analysis and movie rendering on thousands of nodes of Blue Waters. NAMD users can implement or ex-tend simulation protocols and multiple-copy algorithms that execute unmodified on any supercomputer without the need to recompile NAMD. We now demonstrate the integration of the Swift/T high-performance parallel scripting language to enable high-level data flow programming in NAMD and VMD. This integration is achieved without modifying or re-compiling either program since the Turbine execution engine is itself based on Tcl and is dynamically loaded by the in-terpreter, as is the platform-specific MPI library on which it depends.

Abstract—The cellular process responsible for providing en-ergy for most life on Earth, namely, photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales span-ning several orders of magnitude over quantum and classi-cal regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. We present, in an accompanying movie, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movie is the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. We describe the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movie, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers. I.