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Bridging Quantization and Deployment: A Fixed-Point Workflow for FPGA Accelerators

Obed M. Mogaka, Håkan Forsberg , Masoud Daneshtalab · Proceedings of the 28th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS) , 2025

DOI

Abstract

We present a fixed-point quantization-to-deployment workflow that automates the precision-selection and hardware generation steps for deep learning accelerators on FPGAs, closing the gap between post-training quantization research and practical synthesis-ready RTL.

Citation

@inproceedings{mogaka2025ddecs,
  author = {Mogaka, Obed M. and Forsberg, Håkan and Daneshtalab, Masoud},
  title = {Bridging Quantization and Deployment: A Fixed-Point Workflow for {FPGA} Accelerators},
  booktitle = {Proceedings of the 28th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)},
  year = {2025},
  pages = {123--126},
  doi = {10.1109/DDECS63720.2025.11006791},
  keywords = {FPGA, quantization, deep learning, hardware accelerator, fixed-point}
}