Ballooning Graphics Memory Space in Full GPU Virtualization Environments

Abstract

Advances in virtualization technology have enabled multiple virtual machines (VMs) to share resources in a physical machine (PM). With the widespread use of graphics-intensive applications, such as two-dimensional (2D) or 3D rendering, many graphics processing unit (GPU) virtualization solutions have been proposed to provide high-performance GPU services in a virtualized environment. Although elasticity is one of the major benefits in this environment, the allocation of GPU memory is still static in the sense that after the GPU memory is allocated to a VM, it is not possible to change the memory size at runtime. This causes underutilization of GPU memory or performance degradation of a GPU application due to the lack of GPU memory when an application requires a large amount of GPU memory. In this paper, we propose a GPU memory ballooning solution calledgBalloonthat dynamically adjusts the GPU memory size at runtime according to the GPU memory requirement of each VM and the GPU memory sharing overhead. ThegBalloonextends the GPU memory size of a VM by detecting performance degradation due to the lack of GPU memory. ThegBalloonalso reduces the GPU memory size when the overcommitted or underutilized GPU memory of a VM creates additional overhead for the GPU context switch or the CPU load due to GPU memory sharing among the VMs. We implemented thegBalloonby modifying thegVirt, a full GPU virtualization solution for Intel’s integrated GPUs. Benchmarking results show that thegBalloondynamically adjusts the GPU memory size at runtime, which improves the performance by up to 8% against thegVirtwith 384 MB of high global graphics memory and 32% against thegVirtwith 1024 MB of high global graphics memory.