GPU virtualization is the process of dividing a physical graphics processing unit (GPU) into multiple virtual GPUs that can be allocated to different virtual machines or applications. This technology allows multiple users or workloads to share a single physical GPU, maximizing its utilization and efficiency. By virtualizing GPUs, organizations can achieve better resource management, improved performance, and cost savings.

One common approach to GPU virtualization is through the use of hypervisors or virtualization software that can partition the GPU resources and allocate them to virtual machines as needed. This enables applications running on different virtual machines to access dedicated portions of the GPU without interfering with each other. GPU virtualization is particularly beneficial in environments where multiple users need access to GPU resources simultaneously, such as in cloud computing, virtual desktop infrastructure (VDI), and high-performance computing (HPC) environments.

Overall, GPU virtualization plays a crucial role in enabling efficient and scalable GPU resource management in modern computing environments. It helps organizations make better use of their GPU resources, improve workload performance, and enhance the overall user experience. With the increasing demand for GPU-accelerated applications and services, GPU virtualization is expected to continue evolving and playing a key role in optimizing resource utilization and enhancing computing capabilities.