TY - JOUR

T1 - Sparse Random Signals for Fast Convergence on Invertible Logic

AU - Onizawa, Naoya

AU - Kato, Makoto

AU - Yamagata, Hitoshi

AU - Yano, Koji

AU - Shin, Seiichi

AU - Fujita, Hiroyuki

AU - Hanyu, Takahiro

N1 - Funding Information:
This work was supported by the Japan Society Technology agency (JST) Precursory Research for Embryonic Science and Technology (PRESTO), Japan, under Grant JPMJPR18M5, and in part by the Canon Medical Systems Corporation.
Publisher Copyright:
© 2013 IEEE.

PY - 2021

Y1 - 2021

N2 - This paper introduces sparse random signals for fast convergence on invertible logic. Invertible logic based on a network of probabilistic nodes (spins), similar to a Boltzmann machine, can compute functions bidirectionally by reducing the network energy to the global minimum with the addition of random signals. Here, we propose using sparse random signals that are generated by replacing a part of the typical dense random signals with zero values in probability. The sparsity of the random signals can induce a relatively relaxed transition of the spin network, reaching the global minimum energy at high probabilities. As a typical design example of invertible logic, invertible adders and multipliers are designed and evaluated. The simulation results show that the convergence speed with the proposed sparse random signals is roughly an order of magnitude faster than that with the conventional dense random signals. In addition, several key parameters are found and could be a guideline for fast convergence on general invertible logic.

AB - This paper introduces sparse random signals for fast convergence on invertible logic. Invertible logic based on a network of probabilistic nodes (spins), similar to a Boltzmann machine, can compute functions bidirectionally by reducing the network energy to the global minimum with the addition of random signals. Here, we propose using sparse random signals that are generated by replacing a part of the typical dense random signals with zero values in probability. The sparsity of the random signals can induce a relatively relaxed transition of the spin network, reaching the global minimum energy at high probabilities. As a typical design example of invertible logic, invertible adders and multipliers are designed and evaluated. The simulation results show that the convergence speed with the proposed sparse random signals is roughly an order of magnitude faster than that with the conventional dense random signals. In addition, several key parameters are found and could be a guideline for fast convergence on general invertible logic.

KW - Boltzmann machine

KW - Stochastic computing

KW - bidirectional operations

UR - http://www.scopus.com/inward/record.url?scp=85104181721&partnerID=8YFLogxK

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U2 - 10.1109/ACCESS.2021.3072048

DO - 10.1109/ACCESS.2021.3072048

M3 - Article

AN - SCOPUS:85104181721

VL - 9

SP - 62890

EP - 62898

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

M1 - 9399449

ER -