TY - JOUR
T1 - Area/Energy-Efficient Gammatone Filters Based on Stochastic Computation
AU - Onizawa, Naoya
AU - Koshita, Shunsuke
AU - Sakamoto, Shuichi
AU - Abe, Masahide
AU - Kawamata, Masayuki
AU - Hanyu, Takahiro
N1 - Funding Information:
Manuscript received August 13, 2016; revised December 5, 2016 and February 4, 2017; accepted March 21, 2017. Date of publication April 4, 2017; date of current version September 25, 2017. This work was supported in part by the Brainware LSI Project of MEXT, in part by JSPS KAKENHI under Grant JP26700003 and Grant JP16K12494, and in part by the VLSI Design and Education Center, The University of Tokyo, in collaboration with Synopsys Corporation.
Publisher Copyright:
© 1993-2012 IEEE.
PY - 2017/10
Y1 - 2017/10
N2 - This paper introduces area/energy-efficient gammatone filters based on stochastic computation. The gammatone filter well expresses the performance of human auditory peripheral mechanism and has a potential of improving advanced speech communications systems, especially hearing assisting devices and noise robust speech-recognition systems. Using stochastic computation, a power-and-area hungry multiplier used in a digital filter is replaced by a simple logic gate, leading to area-efficient hardware. However, a straightforward implementation of the stochastic gammatone filter suffers from significantly low accuracy in computation, which results in a low dynamic range (a ratio of the maximum to minimum magnitude) due to a small value of a filter gain. To improve the computation accuracy, gain-balancing techniques are presented that represent the original gain as the product of multiple larger gains introduced at the second-order sections. In addition, dynamic scaling techniques are proposed that scales up small values only on stochastic domain in order to reduce the number of stochastic bits required while maintaining the computation accuracy. For performance comparisons, the proposed stochastic gammatone filters are designed and evaluated on Taiwan semiconductor manufacturing company (TSMC) 65-nm CMOS technology. As a result, the proposed filter achieves an area reduction of 90.7% and an energy reduction of 91.8% in comparison with a fixed-point gammatone filter at the same sampling frequency and a comparable dynamic range.
AB - This paper introduces area/energy-efficient gammatone filters based on stochastic computation. The gammatone filter well expresses the performance of human auditory peripheral mechanism and has a potential of improving advanced speech communications systems, especially hearing assisting devices and noise robust speech-recognition systems. Using stochastic computation, a power-and-area hungry multiplier used in a digital filter is replaced by a simple logic gate, leading to area-efficient hardware. However, a straightforward implementation of the stochastic gammatone filter suffers from significantly low accuracy in computation, which results in a low dynamic range (a ratio of the maximum to minimum magnitude) due to a small value of a filter gain. To improve the computation accuracy, gain-balancing techniques are presented that represent the original gain as the product of multiple larger gains introduced at the second-order sections. In addition, dynamic scaling techniques are proposed that scales up small values only on stochastic domain in order to reduce the number of stochastic bits required while maintaining the computation accuracy. For performance comparisons, the proposed stochastic gammatone filters are designed and evaluated on Taiwan semiconductor manufacturing company (TSMC) 65-nm CMOS technology. As a result, the proposed filter achieves an area reduction of 90.7% and an energy reduction of 91.8% in comparison with a fixed-point gammatone filter at the same sampling frequency and a comparable dynamic range.
KW - Auditory filter
KW - digital circuit implementation
KW - gammatone filter
KW - infinite impulse response (IIR) filter
KW - static power dissipation
KW - stochastic logic
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U2 - 10.1109/TVLSI.2017.2687404
DO - 10.1109/TVLSI.2017.2687404
M3 - Article
AN - SCOPUS:85017100881
VL - 25
SP - 2724
EP - 2735
JO - IEEE Transactions on Very Large Scale Integration (VLSI) Systems
JF - IEEE Transactions on Very Large Scale Integration (VLSI) Systems
SN - 1063-8210
IS - 10
M1 - 7892033
ER -