Abstract: Computing-in-memory (CIM) has been proved to perform high energy efficiency and significant acceleration effect for high computational parallelism neural networks. Floating-point numbers and ...

Abstract: Approximate computing is well-suited for error-tolerant applications, as it improves hardware performance with only minor precision loss. Although approximate computing has advanced floating ...

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