Abstract: Compute-In-Memory (CiM) is emerging as a promising paradigm to design energy-efficient hardware accelerators for AI, addressing the processor-memory data transfer bottleneck. The popularity ...
Abstract: Matrix-matrix multiplication (MM) of large matrices plays a crucial role in various applications, including machine learning. MM requires significant computational resources, but accessing ...
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