With advances in reconfigurable hardware, especially field-programmable gate arrays (FPGAs), it has become possible to use reconfigurable hardware to accelerate complex applications, such as those in scientific computing. There has been a resulting development of reconfigurable computers--computers which have both general purpose processors and reconfigurable hardware, as well as memory and high-performance interconnection networks. In this paper, we study the acceleration of molecular dynamics simulations using reconfigurable computers. We describe how we partition the application between software and hardware and then model the performance of several alternatives for the task mapped to hardware. We describe an implementation of one of these alternatives on a reconfigurable computer and demonstrate that for two real-world simulations, it achieves a 2