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Computer Science > Hardware Architecture

arXiv:2406.00360 (cs)
[Submitted on 1 Jun 2024 (v1), last revised 8 Jul 2024 (this version, v3)]

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

Authors: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.
Subjects: Hardware Architecture (cs.AR)
Cite as: arXiv:2406.00360 [cs.AR]
  (or arXiv:2406.00360v3 [cs.AR] for this version)
  https://doi.org/10.48550/arXiv.2406.00360

Submission history

From: Muhammad Usman [view email]
[v1] Sat, 1 Jun 2024 08:25:16 UTC (3,416 KB)
[v2] Mon, 10 Jun 2024 13:21:08 UTC (2,370 KB)
[v3] Mon, 8 Jul 2024 18:21:49 UTC (2,438 KB)
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