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Abstract: Compute-in-memory (CIM) is a new computing paradigm that addresses the memory-wall problem in hardware accelerator design for deep learning. The input vector and weight matrix multiplication ...
Abstract: The model-based power allocation has been investigated for decades, but this approach requires mathematical models to be analytically tractable and it has high computational complexity.
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