In this paper, we propose an efficient hardware architecture for CNN that provides high speed, low power, and small area targeting ASIC implementation of CNN ...
This paper proposes an efficient hardware architecture for CNN that provides high speed, low power, and small area targeting ASIC implementation of CNN ...
The proposed accelerator architecture exploits parallel memory access, and N-way high speed and approximate MAC units in the convolutional layer as well as the ...
Feb 10, 2022 · [2]. In this paper, we propose a CNN accelerator architecture with. parallel on-chip memory ...
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The approximated hardware units like approximate multipliers can also be utilized to improve the training performance of CNNs in terms of speed, area and power ...
Mar 16, 2022 · Specifically, our work focuses and provides in-depth discussion of DNN-specific approximate techniques that are implemented in the hardware ...
Mar 30, 2023 · In this paper, an approximate PE is dedicatedly devised for CNN accelerators by synergistically considering the data representation, multiplication and ...
Our Convolutional Neural Network Architecture. High Speed, Approximate Arithmetic Based Convolutional Neural Network Accelerator. Conference Paper. Full-text ...
This work introduces an accelerator for Convolutional Neural Network (CNN), based on a hybrid optoelectronic computing architecture and residue number system ( ...