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Computational science applications and advanced scientific computing have made tremendous gains in the past decade. Researchers are regularly employing the power of large computing systems and parallel processing to tackle larger and more complex problems in all of the physical sciences. For the past decade or so, most of this growth in computing power has been free with increased efficiency more-or-less governed by Moore's Law. However, increases in performance are becoming harder to achieve due to the complexity of the parallel computing platforms and the software required for these systems. Reconfigurable computing, or heterogeneous computing, is offering some hope to the scientific computing community as a means to continued growth in computing capability. This paper offers a glimpse of the hardware and software associated with this new technology and discusses how the new paradigm functions for computational science.