## Abstract

Sorting is a common task in a wide range of applications from signal and image processing to switching systems. For applications that require high performance, sorting is often performed in hardware with application-specified integrated circuits or field-programmable gate arrays. Hardware cost and power consumption are the dominant concerns. The usual approach is to wire up a network of compare-and-swap units in a configuration called the Batcher (or bitonic) network. Such networks can readily be pipelined. This paper proposes a novel area-efficient and power-efficient approach to sorting networks, based on 'unary processing.' In unary processing, numbers are encoded uniformly by a sequence of one value (say 1) followed by a sequence of the other value (say 0) in a stream of 0's and 1's with the value defined by the fraction of 1's in the stream. Synthesis results of complete sorting networks show up to 92% area and power saving compared to the conventional binary implementations. However, the latency increases. To mitigate the increased latency, this paper uses a novel time-encoding of data. The approach is validated with two implementations of an important application of sorting: median filtering. The result is a low cost, energy-efficient implementation of median filtering with only a slight accuracy loss, compared to conventional implementations.

Original language | English (US) |
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Pages (from-to) | 1471-1480 |

Number of pages | 10 |

Journal | IEEE Transactions on Very Large Scale Integration (VLSI) Systems |

Volume | 26 |

Issue number | 8 |

DOIs | |

State | Published - Aug 2018 |

### Bibliographical note

Publisher Copyright:© 1993-2012 IEEE.

## Keywords

- Low cost design
- median filtering
- sorting networks
- stochastic computing
- time-encoding data
- unary processing