GPU Local Memory Translation Table with Dirty Flags for VM Migration
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Solution Overview
Problem
Current virtualization technologies for graphics processing units (GPUs) face challenges in efficiently managing and migrating local memory, particularly in virtual machine environments, leading to inefficiencies in display output and resource allocation.
Innovation Solution
Implementing a local memory translation table (LMTT) with active and dirty flags to manage device memory translation, enabling efficient GPU local memory management and accelerated migration during virtual machine live migration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtualization technologies are used to share GPU resources among multiple virtual machines, then resource utilization is improved, but memory management complexity and migration overhead increase
Solution Approach 1:
The patent divides the GPU memory management into separate components: a local memory translation table (LMTT) for fast address translation within the GPU, and a host memory management system for overall memory control. This segmentation allows each component to handle specific tasks efficiently, reducing the complexity burden on the entire system while maintaining high resource utilization across virtual machines.
Solution Approach 2:
The LMTT acts as an intermediary between virtual machine memory requests and physical GPU memory. It translates virtual addresses to physical addresses locally within the GPU, eliminating the need for constant host processor intervention in memory management operations. This intermediary structure simplifies the overall memory management complexity while enabling efficient multi-VM resource sharing.
2Adaptability or versatility
If GPU local memory is migrated during virtual machine live migration, then virtual machine mobility is improved, but display output efficiency and migration speed deteriorate
Solution Approach 1:
The patent implements dirty page tracking that identifies which memory pages have been modified before migration is needed. By preliminarily marking dirty pages in the LMTT, the system prepares migration data in advance, allowing only modified pages to be transferred during live migration. This preliminary action significantly reduces migration speed requirements while maintaining virtual machine mobility.
Solution Approach 2:
Instead of migrating entire GPU memory spaces, the patent copies only the dirty pages that have been modified. The LMTT maintains mappings for both original and migrated memory regions, allowing seamless copying of only necessary data during migration. This selective copying approach maintains virtual machine mobility while dramatically improving migration speed by transferring minimal data.
3Productivity
If a local memory translation table with dirty flags is implemented, then memory translation efficiency is improved, but device complexity increases
Solution Approach 1:
The patent merges the memory translation table and dirty page flags into a single integrated LMTT structure within the GPU. Instead of implementing separate translation and tracking mechanisms, the system combines these functions into one unified table that handles both address translation and modification tracking. This merging improves memory translation efficiency by consolidating operations while managing the increased complexity through integration rather than multiplication of components.
Data Source
AI summary
Embodiments described herein provide techniques to facilitate access to local memory of a graphics processor by a guest software domain. The guest software domain can access the local memory via an address translation system that includes a local memory translation table. In one embodiment, accessed and/or dirty bits are enabled in the local memory translation table, which may be used to accelerate the GPU local memory portion of VM Migration for a VM that includes a vGPU.