A DRAM LUT-based computing scheme uses one row activation per scalar-vector batch and per-mat independent column reads to cut activation energy, plus an HBM accelerator that counts quantized exponents for transformer inference.
Lacc: Exploiting lookup table-based fast and accurate vector multiplication in dram-based cnn accelerator,
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Towards Efficient LUT-based PIM: A Scalable and Low-Power Approach for Modern Workloads
A DRAM LUT-based computing scheme uses one row activation per scalar-vector batch and per-mat independent column reads to cut activation energy, plus an HBM accelerator that counts quantized exponents for transformer inference.