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Reconfigurable hardware has become a well-accepted option for implementing digital signal processing (DSP). Traditional devices such as field-programmable gate arrays offer good fine-grain flexibility. More recent coarse-grain reconfigurable architectures are optimized for word-length computations. We have developed a medium-grain reconfigurable architecture that combines the advantages of both approaches. Modules such as multipliers and adders are mapped onto blocks of 4-bit cells. Each cell contains a matrix of lookup tables that either implement mathematics functions or a random-access memory. A hierarchical interconnection network supports data transfer within and between modules. We have created software tools that allow users to map algorithms onto the reconfigurable platform. This paper analyzes the implementation of several common benchmarks, ranging from floating-point arithmetic to a radix-4 fast Fourier transform. The results are compared to contemporary DSP hardware.