• Title/Summary/Keyword: Liquid State Machine(LSM)

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Low Power Neuromorphic Hardware Design and Implementation Based on Asynchronous Design Methodology (비동기 설계 방식기반의 저전력 뉴로모픽 하드웨어의 설계 및 구현)

  • Lee, Jin Kyung;Kim, Kyung Ki
    • Journal of Sensor Science and Technology
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    • v.29 no.1
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    • pp.68-73
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    • 2020
  • This paper proposes an asynchronous circuit design methodology using a new Single Gate Sleep Convention Logic (SG-SCL) with advantages such as low area overhead, low power consumption compared with the conventional null convention logic (NCL) methodologies. The delay-insensitive NCL asynchronous circuits consist of dual-rail structures using {DATA0, DATA1, NULL} encoding which carry a significant area overhead by comparison with single-rail structures. The area overhead can lead to high power consumption. In this paper, the proposed single gate SCL deploys a power gating structure for a new {DATA, SLEEP} encoding to achieve low area overhead and low power consumption maintaining high performance during DATA cycle. In this paper, the proposed methodology has been evaluated by a liquid state machine (LSM) for pattern and digit recognition using FPGA and a 0.18 ㎛ CMOS technology with a supply voltage of 1.8 V. the LSM is a neural network (NN) algorithm similar to a spiking neural network (SNN). The experimental results show that the proposed SG-SCL LSM reduced power consumption by 10% compared to the conventional LSM.