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When ACRN uses decode_instruction to emulate split-lock/uc-lock instruction, It is actually a try-decode to see if it is XCHG. If the instruction is XCHG instruction, ACRN must emulate it (inject #PF if it is triggered) with peer VCPUs paused, and advance the guest IP. If the instruction is a LOCK prefixed instruction with accessing the UC memory, ACRN Halted the peer VCPUs, and advance the IP to skip the LOCK prefix, and then let the VCPU Executes one instruction by enabling IRQ Windows vm-exit. For other cases, ACRN injects the exception back to VCPU without emulating it. So change the API to decode_instruction(vcpu, bool full_decode), when full_decode is true, the API does same thing as before. When full_decode is false, the different is if decode_instruction() meet unknown instruction, will keep return = -1 and do not inject #UD. We can use this to distinguish that an #UD has been skipped, and need inject #AC/#GP back. Tracked-On: #6299 Signed-off-by: Tao Yuhong <yuhong.tao@intel.com>
ACRN Hypervisor ############### The open source `Project ACRN`_ defines a device hypervisor reference stack and an architecture for running multiple software subsystems, managed securely, on a consolidated system by means of a virtual machine manager. It also defines a reference framework implementation for virtual device emulation, called the "ACRN Device Model". The ACRN Hypervisor is a Type 1 reference hypervisor stack, running directly on the bare-metal hardware, and is suitable for a variety of IoT and embedded device solutions. The ACRN hypervisor addresses the gap that currently exists between datacenter hypervisors, and hard partitioning hypervisors. The ACRN hypervisor architecture partitions the system into different functional domains, with carefully selected guest OS sharing optimizations for IoT and embedded devices. You can find out more about Project ACRN on the `Project ACRN documentation`_ website. .. _`Project ACRN`: https://projectacrn.org .. _`ACRN Hypervisor`: https://github.com/projectacrn/acrn-hypervisor .. _`Project ACRN documentation`: https://projectacrn.github.io/