כתבה
arXiv cs.AI ·
DiffLUT-Net: רשת FPGA עם חיבורים למודנים
DiffLUT-Net: Differentiable Training of FPGA LUT Networks with Learnable Connectivity
אנו מציגים את DiffLUT-Net, רשת FPGA עם חיבורים למודנים, שנלמדים מראש. הקוד זמין ב-GitHub.
תקציר מקורי באנגליתarXiv:2609.09254v1 Announce Type: cross Abstract: Field-programmable gate arrays (FPGAs) enable efficient neural-network inference, but most deployment flows either accelerate multiply-accumulate operations or convert pretrained quantized models into lookup tables (LUTs). We present DiffLUT-Net, an FPGA-native network connected by six-input LUTs that are trained from scratch. We jointly learn the 64 truth-table entries of a LUT and the source to each of its six input ports using a differentiable LUT function relaxation and hardware source selection. After training, the truth tables and connections are discretized, unused logic can be pruned, and the network is exported directly as synthesizable Verilog. Across five benchmarks, DiffLUT-Net achieves favorable accuracy-resource trade-offs. Th
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arxiv.org
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