Thesis (Ph.D.)--University of Kansas, Electrical Engineering & Computer Science, 2007.Reconfigurable computing is often lauded as having the potential to bridge the performance gap between computational needs and computational resources. Although numerous successes exist, difficulties persist bridging the CPU/FPGA boundary due to relegating hardware and software systems as separate and inconsistent computational models. Alternatively, the work presented in this thesis proposes using parallel programming models to abstract the CPU/FPGA boundary. Computational tasks would exist either as traditional CPU bound threads or as custom hardware threads running within the FPGA. Achieving an abstract parallel programming model that spans the hardw...