Abstract: Compute-in-memory (CIM) is a promising approach for realizing energy-efficient deep neural network (DNN) accelerators. Previous CIM works focusing on uniform quantization (UQ) demonstrated a ...
Abstract: A 15-transistor (15T) SRAM cell-based fully-digital computing-in-memory (CIM) macro is proposed for artificial intelligence accelerations. The CIM macro not only supports simultaneous read + ...
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