## Abstract

We present the design of stochastic computing systems based on sequential logic to implement arbitrary polynomial functions. Stochastic computing is an emerging alternative computing paradigm that performs arithmetic operations on real-valued data represented as random bitstreams using digital logic gates. Stochastic computing systems are capable of realizing complex mathematical operations using a small number of hardware resources by expressing the computation in terms of probabilities. Moreover, the stochastic representation of data using random bitstreams is extremely robust against bit errors. We present a systematic approach to implement arbitrary polynomial functions in stochastic computing using sequential logic, and compare our approach against prior conventional and stochastic implementations.

Original language | English (US) |
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Title of host publication | GLSVLSI 2016 - Proceedings of the 2016 ACM Great Lakes Symposium on VLSI |

Publisher | Association for Computing Machinery |

Pages | 245-250 |

Number of pages | 6 |

ISBN (Electronic) | 9781450342742 |

DOIs | |

State | Published - May 18 2016 |

Event | 26th ACM Great Lakes Symposium on VLSI, GLSVLSI 2016 - Boston, United States Duration: May 18 2016 → May 20 2016 |

### Publication series

Name | Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI |
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Volume | 18-20-May-2016 |

### Other

Other | 26th ACM Great Lakes Symposium on VLSI, GLSVLSI 2016 |
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Country | United States |

City | Boston |

Period | 5/18/16 → 5/20/16 |

### Bibliographical note

Funding Information:This material is based on work supported by the National Science Foundation under grant CCF-1408123.