An Efficient Time-based Stochastic Computing Circuitry Employing Neuron-MOS
An Efficient Time-based Stochastic Computing Circuitry Employing Neuron-MOS
复制标题
采用 Neuron-MOS 的高效基于时间的随机计算电路
DOI:
10.1145/3299874.3317985
复制
发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Nakashima Yasuhiko
中科院分区:
文献类型:
--
作者:
Erlina Tati;Chen Yan;Zhang Renyuan;Nakashima Yasuhiko
A compact and low energy circuitry of time-based stochastic computing (TBSC) have been designed. In the TBSC theory, stochastic numbers (SNs) are represented by duty-cycle of periodic signals. Additionally, multiplication and addition operations of the SNs require the signals to be in-harmonic and uncorrelated in frequency. In order to dynamically tune the frequency, a current-starved structure is applied in a three-stage inverter chain type of oscillator with the neuron-MOS mechanism. By feeding the pulses to a neuron-MOS based inverter with adjustable switching threshold, arbitrary duty-cycle for representing any specific SNs can be generated with the accuracy of 96%. In this manner, the implementation cost of the stochastic number generator (SNG) is reduced by avoiding the use of complex frequency-programmable-oscillator and comparator which are exploited in the conventional TBSC circuit. From circuit simulation results, multiplication and addition operations can be retrieved by proposed TBCS circuits with the accuracy of about 97%. The entire circuitry utilizes 210 CMOS transistors, and consumes the energy of 2.5pJ for one computation, which is 14% and 36.7% of conventional TBCS circuit, respectively.
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DOI:
--
发表时间:
2015
期刊:
影响因子:
--
作者:
Renyuan Zhang;and Mineo Kaneko
通讯作者:
and Mineo Kaneko
DOI:
10.1145/2744769.2747932
发表时间:
2015
期刊:
2015 52nd ACM/EDAC/IEEE Design Automation Conference (DAC)
影响因子:
--
作者:
J. Hayes
通讯作者:
J. Hayes
影响因子:
3.6
作者:
M. Najafi;Shiva Jamali;D. Lilja;Marc D. Riedel;K. Bazargan;R. Harjani
通讯作者:
R. Harjani
DOI:
10.1145/3060403.3060453
发表时间:
2017
期刊:
Proceedings of the Great Lakes Symposium on VLSI 2017
影响因子:
--
作者:
Pai;J. Hayes
通讯作者:
J. Hayes
DOI:
--
发表时间:
2014
期刊:
影响因子:
--
作者:
Renyuan Zhang;and Mineo Kaneko
通讯作者:
and Mineo Kaneko