RQP reduces search cost up to 20.58x versus standard monotonic HGQ workflows on jet substructure classification while producing competitive Pareto frontiers for FPGA neural network accelerators.
PolyLUT: learning piece- wise polynomials for ultra-low latency FPGA LUT-based inference
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RQP: Resource-Oriented Quantiser Pruning for Neural Networks on FPGAs
RQP reduces search cost up to 20.58x versus standard monotonic HGQ workflows on jet substructure classification while producing competitive Pareto frontiers for FPGA neural network accelerators.