Design of Partial Product Generator Circuit for Approximate Radix-8 Booth Multiplier with Lower Delay

Singh, Pooja; Kumar, Manish

doi:10.1007/978-981-19-0312-0_53

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Other1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, two different approximate multipliers DMAxM1 and DMAxM2 are designed based on Karatsuba algorithm [10] and radix-8 booth multiplication [11]. After implementing DMAxM1 and DMAxM2 with algorithmic simulation, a detailed analysis of the circuit performance index and error evaluation index is made.…”

Section: Introductionmentioning

confidence: 99%

Low-power approximate multipliers for artificial intelligence chips

Xiao

2023

Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023)

View full text Add to dashboard Cite

With the rapid development of deep learning-based neural network models, traditional general-purpose chips can hardly meet the needs of large-scale neural network computing tasks, so artificial intelligence chips come out along with the trend. In the application area of artificial intelligence chips, many computational tasks are related to multiplication, and multipliers are used very frequently. Due to the complexity and optimizability of multipliers themselves, their approximate design can effectively reduce the power consumption and improve the computational power of artificial intelligence chips. In this paper, we design two approximate multipliers based on Karatsuba algorithm and radix-8 booth multiplication, which reduce the power consumption by more than 45% and can be well adapted to various different neural network models to replace the exact multiplication unit of artificial intelligence chips.

show abstract

Section: Introductionmentioning

confidence: 99%

Low-power approximate multipliers for artificial intelligence chips

Xiao

2023

Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023)

View full text Add to dashboard Cite

show abstract

Design of Partial Product Generator Circuit for Approximate Radix-8 Booth Multiplier with Lower Delay

Cited by 1 publication

References 11 publications

Low-power approximate multipliers for artificial intelligence chips

Low-power approximate multipliers for artificial intelligence chips

Contact Info

Product

Resources

About