Abstract
Stochastic computing (SC) has been applied on the implementations of complex arithmetic functions. Complicated polynomial-based approximations lead to large hardware complexity of previous SC circu ...
Highlights
Stochastic computing (SC) is an attractive approximate computing method which performs basic computing operations based on probabilities [1]–[3]
EXPERIMENTAL RESULTS we present the experimental results of the proposed approximation method and corresponding hardware implementations based on SC
If the outputs of a function do not locate inside [0, 1], the function can be scaled into range [0, 1] by simple multiplications and additions, and the scaled version of the function can be implemented with the proposed method
Summary
Stochastic computing (SC) is an attractive approximate computing method which performs basic computing operations based on probabilities [1]–[3]. This paper provides a novel approximation method and low-complexity hardware architectures for arithmetic functions. 2) Using NAND and AND gates as the basic computing components, very low-complexity hardware architectures are provided for different kinds of arithmetic functions. The computations in the range [0, 0.5) and [0.5, 1] can reuse the same NAND gates and AND gates, so Eq (19) requires nearly the same hardware complexity with the monotonic functions. THE PROPOSED HARDWARE ARCHITECTURES the hardware architectures for the three kinds of arithmetic functions are introduced in detail
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