A study on Multiple-Instance GPU, Evolution, Architecture and Applications
Abstract
Multiple Instance GPU (MIG) is a promising
technology for improving the efficiency and scalability of GPUbased systems. MIG allows multiple users or workloads to share a single physical GPU while maintaining performance and resource isolation. This study covers the evolution of GPUs, the architecture of MIG, and various applications of MIG, including virtualization, deep learning inference, and high-performance computing. The study also discusses the architectural considerations of MIG for scalable GPU virtualization and the challenges in implementing MIG in real-world systems. The references provided offer further insights into the technical details of MIG and its potential for improving the performance and cost-effectiveness of GPU-based systems.
Keywords:
Graphics Processing Unit (GPU, Multiple Instance GPU (MIG), GPU virtualization, deep learning inference, high performance computing
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