Fusing Adds and Shifts for Efficient Dot Products

Dot products are heavily used in applications like graphics, signal processing, navigation, and artificial intelligence (AI). These AI models in particular impose significant computational demands on modern computers. Current accelerators typically implement dot product hardware as a row of multipliers followed by a tree of adders. However, treating multiplication and summation operations separately leads to sub-optimal hardware. In contrast, we obtain significant area savings by considering the dot product operation as a whole. We propose <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FASED</monospace>, which fuses components of a Booth multiplier with the adder tree to eliminate a significant portion of full adders from a baseline INT8×INT8,4,2 design. Compared to popular dot product hardware units, <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FASED</monospace> reduces area by up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$1.9\times$</tex-math></inline-formula>.

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Publication Details

Journal
IEEE Computer Architecture Letters
Published
2025-11-26
DOI
https://doi.org/10.1109/lca.2025.3637718
Primary Topic
Numerical Methods and Algorithms
Type
article
Field-Weighted Citation Impact
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article

Fusing Adds and Shifts for Efficient Dot Products

Gennady Pekhimenko, Karthik Ganesan, Mark C. Jeffrey, Pavel Golikov
IEEE Computer Architecture Letters
Numerical Methods and Algorithms
article

Fusing Adds and Shifts for Efficient Dot Products

Gennady Pekhimenko, Karthik Ganesan, Mark C. Jeffrey, Pavel Golikov
article en

Abstract

Dot products are heavily used in applications like graphics, signal processing, navigation, and artificial intelligence (AI). These AI models in particular impose significant computational demands on modern computers. Current accelerators typically implement dot product hardware as a row of multipliers followed by a tree of adders. However, treating multiplication and summation operations separately leads to sub-optimal hardware. In contrast, we obtain significant area savings by considering the dot product operation as a whole. We propose <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FASED</monospace>, which fuses components of a Booth multiplier with the adder tree to eliminate a significant portion of full adders from a baseline INT8×INT8,4,2 design. Compared to popular dot product hardware units, <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FASED</monospace> reduces area by up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$1.9\times$</tex-math></inline-formula>.

IEEE Computer Architecture LettersVol. 25(1)
University of Toronto (CA)
Openalex Percentile: Top 63%
Numerical Methods and Algorithms
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