A logarithmic approach to energy-efficient GPU arithmetic for mobile devices

Lastras, Miguel; Parhami, Behrooz

doi:10.1109/acssc.2013.6810695

Cited by 7 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the approximation coefficients in each sub-segment, the converter performance such as accuracy, power consumption, delay time, and area overhead are determined. Various prior work were adopted to make trade-off between accuracy level and hardware implementation cost [20][21][22][23][24][25][26][27]. The entire range may be divided into nonuniform sub-segments or uniform sub-segments of equal length.…”

Section: Logarithmic and Antilogarithmic Converters Implementation Approachesmentioning

confidence: 99%

Low Power Multiplication/Division Computing Unit forIOTApplications

Ellaithy

2021

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

Internet of things (IOT) makes limitation on power consumption for sensors and portable devices. Thus exact computation for multiplication and division processes are not allowed due to the huge amount of power consumption. To address these limitations, a low power multiplication/division computing unit is proposed. This approach is based on transforming the complex and power-hungry multiplication and division operations to a simple addition and subtraction process. Then, the efficient piecewise uniform approximation logarithmic and antilogarithmic converters are utilized to complete the computation process. Synthesis of the proposed computing unit using 90 nm CMOS technology, 1.0 V supply voltage standard cell library with 'typical corner' operating condition, reveal that significant power dissipation savings are possible at no performance penalty, when compared with approximate computing approach.

show abstract

Section: Logarithmic and Antilogarithmic Converters Implementation Approachesmentioning

confidence: 99%