MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...
Abstract: Numerous studies have proposed hardware architectures to accelerate sparse matrix multiplication, but these approaches often incur substantial area and power overhead, significantly ...
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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