practice DOI:10.1145/1562764.1562780

Article development led by queue.acm.org GPU acceleration and other computer performance increases will offer critical benefits to biomedical science. BY JAMES C. PHILLIPS AND JOHN E. STONE COMPUTER SIMULATION HAS become an integral part of the study of the structure and function of biological molecules. For years, parallel computers have been used to conduct these computationally demanding simulations and to analyze their results. These simulations function as a “computational microscope, ” allowing the scientist to observe details of molecular processes too small, fast, or delicate to capture with traditional instruments. Over time, commodity GPUs (graphics processing units) have evolved into massively parallel computing devices, and more recently it has become possible to program them in dialects of the popular C/C++ pro-gramming languages. This has created a tremendous op-portunity to employ new simulation and analysis techniques that were previ-ously too computationally demanding to use. In other cases, the computation-al power provided by GPUs can bring analysis techniques that previously required computation on high-perfor-mance computing (HPC) clusters down to desktop computers, making them accessible to application scientists lack-ing experience with clustering, queuing systems, and the like. This article is based on our experi-ences developing software for use by and in cooperation with scientists, often graduate students, with backgrounds in physics, chemistry, and biology. Our programs, NAMD18 and VMD10 (Visual Molecular Dynamics), run on computer systems ranging from laptops to super-computers and are used to model pro-teins, nucleic acids, and lipids at the atomic level in order to understand how protein structure enables cellular func-tions such as catalyzing reactions, har-vesting sunlight, generating forces, and sculpting membranes (for additional scientific applications, se