… Deep Neural Networks (DNNs) are very popular … accelerators. This article provides a
comprehensive survey and analysis of hardware approximation techniques for DNN accelerators. …

… a hardware neural network accelerator would be broad. In this paper, we want to highlight that
a hardware neural network accelerator … evaluate software neural network implementations …

… a number of neural network accelerators to achieve high … accelerators. In summary,
this review can serve as a reference for hardware researchers in the area of neural networks…

… Therefore, high energy-efficient hardware accelerator is … UNPU: An energy-efficient deep
neural network accelerator … -scalable convolutional neural network processor in 28nm fdsoi." In …

… hardware accelerator. In this article an overview of existing neural network hardware accelerators
… acceleration of the inference of convolutional neural networks (CNNs) used for image …

… This paper presents three different hardware accelerators implemented on Xilinx’s Zynq SoC
… As proof of concept, the hardware was tested with a character level language model made …

… In this work, we propose a hardware accelerator for sparse … Experiments demonstrate that
our accelerator can achieve … speedup over previous dense CNN accelerators on FPGAs. …

… , designing hardware accelerators that … accelerators for specific classes of neural networks
are emerging [22] [34], so too do we expect to see further specialization of CNN accelerators …

… Convolutional Neural Network FPGA accelerator that achieves … of the CNN FPGA accelerator
designed to efficiently compute … at run-time (without requiring hardware re-compilation), (2) …

… In this paper we have considered the problem of designing and building optimized hardware
accelerators for deep neural networks that achieve minimal power consumption while …