GPU infrastructure refers to the hardware and software systems that use Graphics Processing Units (GPUs) to accelerate computational workloads. It includes the physical GPU hardware, servers or clusters that host the GPUs, networking components that connect them, and the associated software stack—such as drivers, libraries, frameworks, and orchestration tools—that enable efficient deployment, scaling, and management of GPU resources. GPU infrastructure is commonly used in areas like machine learning, high-performance computing, data analytics, and rendering, where parallel processing can significantly improve performance.