The increasing deployment of artificial intelligence has placed unprecedent requirements on the computing power of cloud computing. Cloud service providers have integrated accelerators with massive parallel computing units in the data center. These accelerators need to be combined with existing virtualization platforms to partition the computing resources. The current mainstream accelerator virtualization solution is through the PCI passthrough approach, which however does not support fine-grained resource provisioning. Some manufacturers also start to provide time-sliced multiplexing schemes, and use drivers to cooperate with specific hardware to divide resources and time slices to different virtual machines, which unfortunately suffer from poor portability and flexibility. One alternative another but promising approach is based on API forwarding, which forwards the virtual machine's request to the back-end driver for processing through a separate driver model. Yet, the communication due to API forwarding can easily become the performance bottleneck. This study proposes Wormhole, an accelerator virtualization framework based on the C/S architecture that supports rapid delegated execution across virtual machines. It aims to provide upper-level users with an efficient and transparent way to accelerate accelerator virtualization with API forwarding while ensuring strong isolation between multiple users. By leveraging hardware virtualization feature, the framework minimizes performance degradation through exitless cross-VM control flow switch. Experimental results show that Wormhole’s prototype system can achieve up to 5 times performance improvement over the classic open-source virtualization solution such as GVirtuS in the training test of the classic model.