Late Breaking Results: On-the-Fly Hadamard Hypervector Processing for Efficient Hyperdimensional Computing

Inspired by the human brain, Hyperdimensional Computing (HDC) processes information efficiently by operating in high-dimensional space using hypervectors. While previous works focus on optimizing pregenerated hypervectors in software, this study introduces a novel on-the-fly vector generation method...

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Bibliographic Details
Published in:2025 62nd ACM/IEEE Design Automation Conference (DAC) pp. 1 - 2
Main Authors: Masum, Abu Kaisar Mohammad, Moghadam, Mehran Shoushtari, Moon, Sabrina Hassan, Ahmed, Ahmed Mamdouh Mohamed, Najafi, M. Hassan, Reis, Dayane, Aygun, Sercan
Format: Conference Proceeding
Language:English
Published: IEEE 22.06.2025
Subjects:
Accuracy
Computational efficiency
Computer architecture
Design automation
Encoding
Hardware
In-memory computing
Iterative methods
Software
Vectors
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Summary:Inspired by the human brain, Hyperdimensional Computing (HDC) processes information efficiently by operating in high-dimensional space using hypervectors. While previous works focus on optimizing pregenerated hypervectors in software, this study introduces a novel on-the-fly vector generation method in hardware with O(1) complexity, compared to the O(N) iterative search used in conventional approaches to find the best orthogonal hypervectors. Our approach leverages Hadamard binary coefficients and unary computing to simplify encoding into addition-only operations after the generation stage in ASIC, implemented using inmemory computing. The proposed design significantly improves accuracy and computational efficiency across multiple benchmark datasets.
DOI:10.1109/DAC63849.2025.11133357