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In order to add GVT-D support, we need pass through stolen memory and opregion memroy to the post-launched VM. To implement this, we first reserve the GPA for stolen memory and opregion memory through post-launched VM e820 table. Then we would build EPT mapping between the GPA and the stolen memory and opregion memory real HPA. The last, we need to return the GPA to post-launched VM if it wants to read the stolen memory and opregion memory address and prevent post-launched VM to write the stolen memory and opregion memory address register for now. We do the GPA reserve and GPA to HPA EPT mapping in ACRN-DM and the stolen memory and opregion memory CFG space register access emulation in ACRN-HV. Tracked-On: #4371 Signed-off-by: Li Fei1 <fei1.li@intel.com> |
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acpi_parser | ||
arch/x86 | ||
boot | ||
bsp/ld | ||
common | ||
debug | ||
dm | ||
hw | ||
include | ||
lib | ||
pre_build | ||
release | ||
scenarios | ||
scripts | ||
Kconfig | ||
MAINTAINERS | ||
Makefile | ||
README.rst |
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/