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arXiv · 2406.00360

L2R-CIPU: Efficient CNN Computation with Left-to-Right Composite Inner Product Units

Malik Zohaib Nisar·Mohammad Sohail Ibrahim·Muhammad Usman·Jeong-A Lee
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Abstract

This paper proposes a composite inner-product computation unit based on left-to-right (LR) arithmetic for the acceleration of convolution neural networks (CNN) on hardware. The efficacy of the proposed L2R-CIPU method has been shown on the VGG-16 network, and assessment is done on various performance metrics. The L2R-CIPU design achieves 1.06x to 6.22x greater performance, 4.8x to 15x more TOPS/W, and 4.51x to 53.45x higher TOPS/mm2 than prior architectures.

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Malik Zohaib Nisar, Mohammad Sohail Ibrahim, Muhammad Usman, Jeong-A Lee. 2024-06-01. L2R-CIPU: Efficient CNN Computation with Left-to-Right Composite Inner Product Units. https://arxiv.org/abs/2406.00360

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