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As it becomes more difficult to increase single-threaded performance, focus on multi-core processor designs increases. However, individual core performance is still important, especially for long-executing applications such as in scientific computing. Based on scientific application needs as modeled by SPEC-FP and a set of applications from Sandia National Labs, we have created several different reconfigurable functional unit (RFU) designs for superscalar multi-processor supercomputers. This paper discusses the design process and evaluates the RFUs' ability to implement instruction dataflow graphs from scientific workloads. Our best-performing RFU design is able to implement 89% of the dataflow graphs in the benchmarks.