Evolution of GPU virtualization to resource pooling

Abstract

With the rapid development of artificial intelligence, the demand for Graphics Processing Unit (GPU) resources is also increasing rapidly. To improve the efficiency and utilization of GPU resources, virtualization technology has been widely used in the field of GPUs. This article reviews the evolution from GPU virtualization to resource pooling, including device simulation, GPU pass-through, hardware-assisted virtualization, GPU full virtualization, GPU remotesharing, and GPU resource pools. The advantages and disadvantages of each stage and the challenges faced during the evolution process are also analyzed. This article discusses the difficulties and solutions of GPU resource pool construction, as well as the construction steps and framework, providing a reference for the research and application of GPU resource pooling.

A Comprehensive Analysis of Nvidia's Technological Innovations, Market Strategies, and Future Prospects

“…This not only streamlines resource management but also enhances the efficiency of virtual desktop environments, showcasing Nvidia's commitment to optimizing computational resources. Liang et al (2023) traced the evolution of GPU computing, emphasizing CUDA as the operating system on GPU. This historical perspective underscores Nvidia's pivotal role in General-Purpose computing on Graphics, shaping the trajectory of GPU computing over the years.…”