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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Microcode handles the stateful, multi-step operations -- stack switches, descriptor loading, V86 frame management -- that are too irregular for fixed hardware.。91视频对此有专业解读
make bench-single ARGS="--110m=models/model.safetensors --benchmark_filter=110m"