FAME: An FPGA-Based Platform for Approximate Multipliers Evaluation with Pattern-Guided DNN Retraining
The platform exploits the reconfigurable logic of Field-Programmable Gate Arrays to implement approximate multipliers directly in hardware, eliminating the need for LUT-based emulation on CPU/GPU platforms and thereby enabling efficient DNN inference while significantly reducing evaluation time on large datasets.
Rappy Saha, Nima Amirafshar, Jude Haris et al.
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