… , a hardware accelerator for the convolution layer of CNN was proposed. The accelerator …
Our future work is to evaluate the ARM processor against custom hardware accelerator in other …

… conventional accelerators cannot maximize the performance of quantized neural networks
(… the limitations of the previous dynamic precision-scalable hardware accelerators [5]–[7], we …

… hardware optimizations, analyzed in the following, that are required for energy-efficient
acceleration of DL models. This work analyzes several hardware … on dedicated accelerators. The …

… such as hardware accelerators of deep neural networks (DNN). In … a resilience analysis of
a hardware accelerator of ResNet DNN … , convolutional neural network, hardware accelerator …

… neural network accelerator designs. We introduce the techniques on both the software and
hardware … We compare state-of-the-art neural network accelerator designs to evaluate the …

… Abstract—Spiking Neural Networks (SNN) are an emerging type of biologically plausible …
Artificial Neural Network (ANN). This work presents the development of a hardware accelerator …

… Deep convolutional neural networks (CNNs) have recently … of CNNs, custom hardware
accelerators are vital for boosting … it a promising platform for hardware acceleration of CNNs. In …

… Therefore, hardware accelerators are the best choice to … in hardware accelerators such as
pruning and quantization. In this paper, a low-power dedicated CNN hardware accelerator is …

… monly seen in conventional neural networks and allow for small… hardware cost of conventional
GRNG makes the hardware … , an FPGA-based hardware accelerator design for variational …

… In this section, we present the architecture of the hardware accelerator for running
DCNNs in the feedforward prediction phase. The capabilities and the limitations of this …