L2R-CIPU: Efficient CNN Computation with Left-to-Right Composite Inner Product Units
<|reference_start|>L2R-CIPU: Efficient CNN Computation with Left-to-Right Composite Inner Product Units: 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.<|reference_end|>
@article{nisar2024l2r-cipu:,
    title={L2R-CIPU: Efficient CNN Computation with Left-to-Right Composite Inner
  Product Units},
    author={Malik Zohaib Nisar, Mohammad Sohail Ibrahim, Muhammad Usman, Jeong-A
  Lee},
    journal={arXiv preprint arXiv:2406.00360},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.00360},
    primaryClass={cs.AR}
}