Design of Energy Efficient Arithmetic VLSI Circuits

Advanced electronics have become an integral part of human lives, from Smartphones in our pockets to the modern vehicles on the road and to the satellites that orbit the earth. Power consumption has become a major constraint in these applications, often employing data- intensive digital signal processing systems and architectures. While enormous transistor density at the nanoscale has been increased in the Very Large-Scale Integration (VLSI) multicore era comparable to Moore's law, improving the performance of computing systems has become extremely difficult. Sustaining technological advancements for such energy-constrained devices has paved the way for new areas in research. “Approximate Computing (AC)” has become one of the most promising paradigms, a field that has gainedsignificant attention in the quest for energy efficiency in recent years. AC algorithms are numerically approximate rather than accurate. Inherent error resilience is the primary source of motivation behind AC. Recent research demonstrates that error resilience is pervasive in cyber search, deep learning, multimedia, recognition and data mining. Arithmetic units are the fundamental building blocks in most of the data dominated applications at the micro- architectural level of abstraction. AC is optimal for power and area efficient arithmetic circuits.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2024-08-12
DOI
https://doi.org/10.55041/ijsrem37054
Primary Topic
Low-power high-performance VLSI design
Type
article
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article

Design of Energy Efficient Arithmetic VLSI Circuits

P Sumalatha, T. Ragavandra Vishnu
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Low-power high-performance VLSI design
article

Design of Energy Efficient Arithmetic VLSI Circuits

P Sumalatha, T. Ragavandra Vishnu
article en

Abstract

Advanced electronics have become an integral part of human lives, from Smartphones in our pockets to the modern vehicles on the road and to the satellites that orbit the earth. Power consumption has become a major constraint in these applications, often employing data- intensive digital signal processing systems and architectures. While enormous transistor density at the nanoscale has been increased in the Very Large-Scale Integration (VLSI) multicore era comparable to Moore's law, improving the performance of computing systems has become extremely difficult. Sustaining technological advancements for such energy-constrained devices has paved the way for new areas in research. “Approximate Computing (AC)” has become one of the most promising paradigms, a field that has gainedsignificant attention in the quest for energy efficiency in recent years. AC algorithms are numerically approximate rather than accurate. Inherent error resilience is the primary source of motivation behind AC. Recent research demonstrates that error resilience is pervasive in cyber search, deep learning, multimedia, recognition and data mining. Arithmetic units are the fundamental building blocks in most of the data dominated applications at the micro- architectural level of abstraction. AC is optimal for power and area efficient arithmetic circuits.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 08(008)
Affordable and clean energy
Openalex Percentile: Top 90%
Low-power high-performance VLSI design
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