Performance Modeling for CNN Inference Accelerators on FPGA.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems(2020)
摘要
The recently reported successes of convolutional neural networks (CNNs) in many areas have generated wide interest in the development of field-programmable gate array (FPGA)-based accelerators. To achieve high performance and energy efficiency, an FPGA-based accelerator must fully utilize the limited computation resources and minimize the data communication and memory access, both of which are imp...
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关键词
Random access memory,Field programmable gate arrays,Computational modeling,Convolution,System-on-chip,Delays,Kernel
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