research-article

Energy-Efficient Approximate Multiplication for Digital Signal Processing and Classification Applications

Authors:

Srinivasan Narayanamoorthy,

Hadi Asghari Moghaddam,

Zhenhong Liu,

Taejoon Park,

Nam Sung KimAuthors Info & Claims

IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Volume 23, Issue 6

Pages 1180 - 1184

https://doi.org/10.1109/TVLSI.2014.2333366

Published: 01 June 2015 Publication History

Abstract

The need to support various digital signal processing (DSP) and classification applications on energy-constrained devices has steadily grown. Such applications often extensively perform matrix multiplications using fixed-point arithmetic while exhibiting tolerance for some computational errors. Hence, improving the energy efficiency of multiplications is critical. In this brief, we propose multiplier architectures that can tradeoff computational accuracy with energy consumption at design time. Compared with a precise multiplier, the proposed multiplier can consume 58% less energy/op with average computational error of $\sim 1$ %. Finally, we demonstrate that such a small computational error does not notably impact the quality of DSP and the accuracy of classification applications.

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Farahani SReshadinezhad MFatemieh S(2024)New design for error-resilient approximate multipliers used in image processing in CNTFET technologyThe Journal of Supercomputing10.1007/s11227-023-05623-380:3(3694-3712)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s11227-023-05623-3
Pradhan CLetras MTeich J(2023)Efficient Table-based Function Approximation on FPGAs Using Interval Splitting and BRAM InstantiationACM Transactions on Embedded Computing Systems10.1145/358073722:4(1-24)Online publication date: 25-Jan-2023
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Towhidy AOmidi RMohammadi K(2023)On the Design of Iterative Approximate Floating-Point MultipliersIEEE Transactions on Computers10.1109/TC.2022.321646572:6(1623-1635)Online publication date: 1-Jun-2023
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Index Terms

Energy-Efficient Approximate Multiplication for Digital Signal Processing and Classification Applications
1. Hardware
  1. Integrated circuits
    1. Logic circuits
      1. Arithmetic and datapath circuits
  2. Very large scale integration design

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Very Large Scale Integration (VLSI) Systems

IEEE Transactions on Very Large Scale Integration (VLSI) Systems Volume 23, Issue 6

June 2015

192 pages

ISSN:1063-8210

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IEEE Educational Activities Department

United States

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Published: 01 June 2015

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https://dl.acm.org/doi/10.1007/s11227-023-05623-3
Pradhan CLetras MTeich J(2023)Efficient Table-based Function Approximation on FPGAs Using Interval Splitting and BRAM InstantiationACM Transactions on Embedded Computing Systems10.1145/358073722:4(1-24)Online publication date: 25-Jan-2023
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Towhidy AOmidi RMohammadi K(2023)On the Design of Iterative Approximate Floating-Point MultipliersIEEE Transactions on Computers10.1109/TC.2022.321646572:6(1623-1635)Online publication date: 1-Jun-2023
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