### Abstract

In the fields of machine learning and image processing, cost-less circuits with low energy are required instead of extreme precision, and stochastic computing (SC), a type of approximate computing, is attracting attention. In SC, stochastic numbers (SNs), bit streams with values of the appearance rates of 1's, are used. SC enables calculations with simple circuits. To make the calculation results correct, duplication of an SN (gener-ating an SN with the same value) is required when using the SN with the same value. The conventional SN duplicator composed of a flip-flop (FF) has a problem that the output SN only depends on the input SN. Therefore, if the FF-based duplicator is used in a circuit with re-convergence paths, the output SN becomes erroneous. This paper proposes an SN duplicator, 2^{n} RRR, that can output more independent output by its improved flexibility of bit re-arrangement. With this duplicator, the errors of the hyperbolic tangent function are reduced by up to 50% compared to the duplicator that we proposed previously. Also, up to more than 99.9% of the circuit area is reduced compared to the implementation of binary computing.

Original language | English |
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Title of host publication | 2018 New Generation of CAS, NGCAS 2018 |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 182-185 |

Number of pages | 4 |

ISBN (Electronic) | 9781538676813 |

DOIs | |

Publication status | Published - 2018 Dec 10 |

Event | 2018 New Generation of CAS, NGCAS 2018 - Valletta, Malta Duration: 2018 Nov 20 → 2018 Nov 23 |

### Other

Other | 2018 New Generation of CAS, NGCAS 2018 |
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Country | Malta |

City | Valletta |

Period | 18/11/20 → 18/11/23 |

### Fingerprint

### Keywords

- Bit re-arrangement
- Re-convergence path
- Stochastic computing
- Stochastic number
- Stochastic number duplicator

### ASJC Scopus subject areas

- Hardware and Architecture
- Electrical and Electronic Engineering
- Energy Engineering and Power Technology
- Instrumentation

### Cite this

*2018 New Generation of CAS, NGCAS 2018*(pp. 182-185). [8572289] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NGCAS.2018.8572289

**2n RRR : Improved stochastic number duplicator based on bit re-arrangement.** / Ishikawa, Ryota; Tawada, Masashi; Yanagisawa, Masao; Togawa, Nozomu.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*2018 New Generation of CAS, NGCAS 2018.*, 8572289, Institute of Electrical and Electronics Engineers Inc., pp. 182-185, 2018 New Generation of CAS, NGCAS 2018, Valletta, Malta, 18/11/20. https://doi.org/10.1109/NGCAS.2018.8572289

}

TY - GEN

T1 - 2n RRR

T2 - Improved stochastic number duplicator based on bit re-arrangement

AU - Ishikawa, Ryota

AU - Tawada, Masashi

AU - Yanagisawa, Masao

AU - Togawa, Nozomu

PY - 2018/12/10

Y1 - 2018/12/10

N2 - In the fields of machine learning and image processing, cost-less circuits with low energy are required instead of extreme precision, and stochastic computing (SC), a type of approximate computing, is attracting attention. In SC, stochastic numbers (SNs), bit streams with values of the appearance rates of 1's, are used. SC enables calculations with simple circuits. To make the calculation results correct, duplication of an SN (gener-ating an SN with the same value) is required when using the SN with the same value. The conventional SN duplicator composed of a flip-flop (FF) has a problem that the output SN only depends on the input SN. Therefore, if the FF-based duplicator is used in a circuit with re-convergence paths, the output SN becomes erroneous. This paper proposes an SN duplicator, 2n RRR, that can output more independent output by its improved flexibility of bit re-arrangement. With this duplicator, the errors of the hyperbolic tangent function are reduced by up to 50% compared to the duplicator that we proposed previously. Also, up to more than 99.9% of the circuit area is reduced compared to the implementation of binary computing.

AB - In the fields of machine learning and image processing, cost-less circuits with low energy are required instead of extreme precision, and stochastic computing (SC), a type of approximate computing, is attracting attention. In SC, stochastic numbers (SNs), bit streams with values of the appearance rates of 1's, are used. SC enables calculations with simple circuits. To make the calculation results correct, duplication of an SN (gener-ating an SN with the same value) is required when using the SN with the same value. The conventional SN duplicator composed of a flip-flop (FF) has a problem that the output SN only depends on the input SN. Therefore, if the FF-based duplicator is used in a circuit with re-convergence paths, the output SN becomes erroneous. This paper proposes an SN duplicator, 2n RRR, that can output more independent output by its improved flexibility of bit re-arrangement. With this duplicator, the errors of the hyperbolic tangent function are reduced by up to 50% compared to the duplicator that we proposed previously. Also, up to more than 99.9% of the circuit area is reduced compared to the implementation of binary computing.

KW - Bit re-arrangement

KW - Re-convergence path

KW - Stochastic computing

KW - Stochastic number

KW - Stochastic number duplicator

UR - http://www.scopus.com/inward/record.url?scp=85060231240&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85060231240&partnerID=8YFLogxK

U2 - 10.1109/NGCAS.2018.8572289

DO - 10.1109/NGCAS.2018.8572289

M3 - Conference contribution

SP - 182

EP - 185

BT - 2018 New Generation of CAS, NGCAS 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -