Scalable and modularized RTL compilation of Convolutional Neural Networks onto FPGA

@article{Ma2016ScalableAM,
  title={Scalable and modularized RTL compilation of Convolutional Neural Networks onto FPGA},
  author={Yufei Ma and Naveen Suda and Yu Cao and Jae-sun Seo and Sarma B. K. Vrudhula},
  journal={2016 26th International Conference on Field Programmable Logic and Applications (FPL)},
  year={2016},
  pages={1-8}
}
  • Yufei Ma, Naveen Suda, S. Vrudhula
  • Published 1 August 2016
  • Computer Science
  • 2016 26th International Conference on Field Programmable Logic and Applications (FPL)
Despite its popularity, deploying Convolutional Neural Networks (CNNs) on a portable system is still challenging due to large data volume, intensive computation and frequent memory access. Although previous FPGA acceleration schemes generated by high-level synthesis tools (i.e., HLS, OpenCL) have allowed for fast design optimization, hardware inefficiency still exists when allocating FPGA resources to maximize parallelism and throughput. A direct hardware-level design (i.e., RTL) can improve… 
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