… We have reviewed many FPGA based deep neural network accelerators from a few
important aspects of hardware design such as algorithmic optimization, hardware architecture, …

… a survey of techniques for designing FPGA-based accelerators for CNNs. Figure 1 shows …
background on FPGAs and CNNs and identifies the challenges in FPGA-based acceleration of …

… Various FPGA-based accelerator designs have been … on neural network inference accelerators
based on FPGA and … of FPGA-based neural network inference accelerator design and …

… computation with FPGA based accelerator design. … We select our proposed cross-layer
accelerator for comparison. … Overall, our FPGA based implementation achieves up to a 17.42x …

… -efficient neural network accelerator … -art neural network accelerator designs to evaluate
the techniques introduced and estimate the achievable performance of FPGA-based accelerator …

… the Alexnet convolutional neural network, we implement a 5-layer accelerator for MNIST …
precision on a Virtex7 FPGA. We compare performance on FPGA platform with the performance …

… This work proposes an end-to-end FPGAbased CNN accelerator with all the layers mapped
on one chip so that different layers can work concurrently in a pipelined structure to increase …

… simplifies the design flow of NN accelerators for the machine learning or AI … accelerators
burnt to our FPGA board exhibit great power efficiency compared to state-of-the-art FPGA-based …

… the operation of feedforward stage with its FpGa hardware accelerator design. … hardware
accelerator, we use the EGOY XZ7 development board which includes Xilinx ZynqY7020 FpGa. …

… , an FPGAbased accelerator is a good choice, and previous designs have showed great
benefits brought by FPGA-based accelerators[5]… We implement an FPGA-based accelerator with …