The emergence of HPC cloud has inspired service provider to deploy GPU in the cloud ecosystem (e.g., Amazon EC2 GPU instance, Aliyun GPU Server). GPU as a computing accelerator is playing an indispensable role in clouding computing. Due to the intrinsic sharing feature of cloud, GPU sharing does not only boost the utilization, lower the cost, but also makes it easier to manage. GPU virtualization comes to solve this problem through Hypervisor and cooperation of software and hardware. This paper collects the methodologies of GPU virtualization and makes a classification and analysis. In addition, it concludes the existing problems and proposes the future works of GPU virtualization.