On the other hand, FPGA is a promising hardware platform for accelerating deep neural networks (DNNs) thanks to its re-programmability and power efficiency. In this chapter, we review essential computations in latest DNN models and their algorithmic optimizations. We then investigate various ...
Recently, rapid growth of modern applications based on deep learning algorithms has further improved research and implementations. Especially, various accelerators for deep CNN have been proposed based on FPGA platform because it has advantages of high performance, reconfigu...
More specifically, several deep CNN accelerators have been planned on FPGA-based platform, due to its fast development round, reconfigure-ability, and high performance. The FPGA is extremely faster than the CPU because it based on parallel mechanism, as well as, consumes very low energy. This ...
Guan, Y., et al.: FP-DNN: An automated framework for mapping deep neural networks onto FPGAs with RTL-HLS hybrid templates. In: FCCM Symposium (2017) Google Scholar Guo, K., et al.: [DL] A survey of FPGA-based neural network inference accelerators. ACM TRETS 12(1), 1–26 (2019...
Recently, rapid growth of modern applications based on deep learning algorithms has further improved research and implementations. Especially, various accelerators for deep CNN have been proposed based on FPGA platform because it has advantages of high performance, reconfigurability,...
英文引用格式：SHI Y Q，JING N F.Evaluation method based on FPGA emulation for resistive neural network accelerators［J］. Computer Engineering，2021，47（12）：209-214.Evaluation Method Based on FPGA Emulation for Resistive Neural Network Accelerators SHI Yongquan，JING Naifeng （School of Electronic...
In these years, most of neural network accelerators are implemented on FPGA for high throughout, low power consumption and movable portability [9]. For real-time applications like target detection, speech recognition and video processing, various FPGA based neural network accelerators have been ...
Mittal S (2020) A survey of fpga-based accelerators for convolutional neural networks. Neural Comput Applic 32(4):1109–1139 Article Google Scholar Wu R, Guo X, Du J, Li J (2021) Accelerating neural network inference on fpga-based platforms—a survey. Electronics 10(9) Howard AG, Zhu ...
Li, “DeepBurning: Automatic Generation of FPGA-based Learning Accelerators for the Neural Network ...
SILICON VALLEY, Calif., June 24, 2020 -- AI software innovator Mipsology today announced that its Zebra neural network accelerating software has been integrated into the latest build of Xilinx's Alveo U50 data center accelerator card, the industry's first low profile adaptable accelerator with ...