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cs.AR2023
Retrospective: EIE: Efficient Inference Engine on Sparse and Compressed Neural Network
Song Han, Xingyu Liu, Huizi Mao +4
EIE proposed to accelerate pruned and compressed neural networks, exploiting weight sparsity, activation sparsity, and 4-bit weight-sharing in neural network accelerators. Since pu…
cs.AR2016★ 13 cited
FPMax: a 106GFLOPS/W at 217GFLOPS/mm2 Single-Precision FPU, and a 43.7GFLOPS/W at 74.6GFLOPS/mm2 Double-Precision FPU, in 28nm UTBB FDSOI
Jing Pu, Sameh Galal, Xuan Yang +2
FPMax implements four FPUs optimized for latency or throughput workloads in two precisions, fabricated in 28nm UTBB FDSOI. Each unit's parameters, e.g pipeline stages, booth encodi…