Abstract: As radio interference technology continues to improve, the scale of interferometric array becomes larger and larger. Its observation capacity also gradually increases. Yet real-time processing of big data becomes problematic. To tackle this kind of problem, this article takes the radio interferometer correlator's need of data computing and transmission, and the characteristics of the radio interferometric array signal into consideration and develops a set of generic correlator based on GPU cluster for the data processing work of "TianLai" project. First of all, considering radio signal's characteristics of correlation calculation, computing tasks are assigned to different GPU nodes according to their frequency bands, and the network load on each node is properly balanced; then these tasks are completed by the corresponding nodes and the results are sent to the storage nodes in real time; finally, the whole system is deployed with reference to the data processing scheme of the GPU cluster correlator, and a performance test is carried out based on the first stage requirements of "TianLai" project. According to the results, the node computing performance of the cluster correlator has been speeded up:it is around 46% of the theoretical peak performance. Compared with the traditional correlator, the GPU-cluster-based correlator is superior owing to its short development cycle, strong scalability, simple deployment and other advantages.