Marchisio, A., Bussolino, B., Salvati, E., Martina, M., Masera, G., & Shafique, M. (2022). Enabling Capsule Networks at the Edge through Approximate Softmax and Squash Operations. In Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design (pp. 1–6). https://doi.org/10.1145/3531437.3539717
Complex Deep Neural Networks such as Capsule Networks (CapsNets) exhibit high learning capabilities at the cost of computeintensive operations. To enable their deployment on edge devices, we propose to leverage approximate computing for designing approximate variants of the complex operations like softmax and squash. In our experiments, we evaluate tradeoffs between area, power consumption, and critical path delay of the designs implemented with the ASIC design flow, and the accuracy of the quantized CapsNets, compared to the exact functions.
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Research Areas:
Computer Engineering and Software-Intensive Systems: 100%
