The invention discloses a double-
path protection approximate multiplier for neural network acceleration. According to the method, multiplication is decomposed into addition operation of an index and a mantissa on the basis of the McCheer logarithm principle, and the design comprises three parts, namely a
decomposition unit, a parallel addition unit and a reconstruction unit; wherein the parallel addition unit comprises an index path and a mantissa path, the index path adopts an approximate
triple modular redundancy addition structure, and high-reliability
fault tolerance is realized through three parallel addition modules and a majority voter; and a mantissa path adopts a truncation self-detection
adder structure, truncation calculation is performed on high effective bits, and fault detection and result switching are performed based on structural invariants, so that lightweight
fault tolerance is realized. And the reconstruction unit combines the results of the exponential path and the mantissa path through a
barrel-shaped shifter, and outputs an approximate product result. The area and
power consumption can be remarkably reduced, high reliability and high efficiency are both achieved, and the method is suitable for scenes such as neural network acceleration and safety-critical calculation.