Hardware accelerator for vision transformers using dynamic token pruning, ReLU replacement, FFN pruning, and row-wise dataflow to reach 2.31 TOPS/W in 28nm CMOS with under 2% accuracy loss.
A 28nm 27.5TOPS/W approximate- computing-based transformer processor with asymptotic sparsity spec- ulating and out-of-order computing
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Low Power Vision Transformer Accelerator with Hardware-Aware Pruning and Optimized Dataflow
Hardware accelerator for vision transformers using dynamic token pruning, ReLU replacement, FFN pruning, and row-wise dataflow to reach 2.31 TOPS/W in 28nm CMOS with under 2% accuracy loss.