The second approach offers broader feature support, seen in projects like Cloud Hypervisor or QEMU microvm. Built for heavier and more dynamic workloads, it supports hot-plugging memory and CPUs, which is useful for dynamic build runners that need to scale up during compilation. It also supports GPU passthrough, which is essential for AI workloads, while still maintaining the fast boot times of a microVM.
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过去这五年,是全球新冠疫情、地缘政治、产业重构的五年,也是数字化和智能化的五年,特别是人工智能这一变革性技术,正在重塑行业生态。传统行业以技术创新打破内卷桎梏,新兴产业则以技术破壁、开疆拓土。
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Author(s): Qin Qin, Yawen Hua, Luyao Hai, Meidie Wu, Siqi Jiang, Rongxing Ye, Jiangfeng Song, Yiliang Liu, Linsen Zhou