Approximate Divider Design Based on Counting-Based Stochastic Computing Division

2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD (MLCAD)(2021)

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摘要
Stochastic computing (SC) promises extremely low cost and energy efficiency for error-tolerant arithmetic operations in many emerging applications such as image processing and deep neural networks. Existing SC-based nonlinear functions like division, however, require highly correlated bit-streams, which does not fit well with the existing SC computing framework in which randomness is required for ...
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