Sorting is one of the most fundamental topics in computer science. Since partial sorting with lower costs would be much more feasible than the complete sorting method for some applications, this paper focuses on the architecture sorting N values from M inputs. To meet the real-time processing requirement, hardware acceleration is commonly employed to enhance the performance. However, high-speed computation usually raises power consumption drastically.To overcome that problem, a low-power, high-throughput, and modular hardware design of partial sorting network is presented. By applying a pointer-like design, the comparing modules move the indexes of samples instead of moving the input data directly. Power dissipation is reduced by minimizing switching activities and signal transitions. To prevent unnecessary comparing of the large data set, an iterative architecture is proposed which uses both the low-power sorting module and a novel clipping mechanism. The proposed design was simulated with a 90-nm cell library and the results are compared to those of other works on hardware sorting. Experiment results show that power consumption is reduced by 64.9 percent and high-throughput performance can also be achieved.
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