Abstract: The current fault diagnosis technology of electric energy metering device has a large amount of calculation, which leads to the low efficiency and low accuracy of the electric energy metering device fault diagnosis. For this reason, the fault diagnosis technology of electric energy metering device based on parallel computing is proposed. The information clustering technology is used to sample the information of electric energy metering devices, preprocess data through threshold method, remove redundant data, and establish the discriminant function. The parallel computing method is used to process fault data, execute multiple fault data processing instructions at the same time, and the discriminant function is used to judge the probability of failure and gather the same kind of failure data together to realize the fault diagnosis of the electric energy metering device. The experimental results show that the proposed method greatly improves the efficiency and accuracy of fault diagnosis for electric energy metering device, and under the data volume of 17 MB and 1 024 MB, the researched technology can complete the fault diagnosis in a relatively short time.