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G-KVM: A Full GPU Virtualization on KVM

机译:G-KVM:KVM上的全GPU虚拟化

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摘要

Graphics processing Units (GPUs), which originally designed for computer graphics applications, have been widely adopted to general purpose computing in many domains owing to their massive computational power. In the era of cloud computing, GPU virtualization becomes an important technique for the better management of GPUs in data centers. However, most of current solutions are not full virtualization. They either need to modify the guest drivers or libraries, or restrict the hardware sharing capability. The only full GPU virtualization solution is GPUvm, which however can only be executed on Xen hypervisors. In this paper, we present a full GPU virtualization solution on KVM (Kernel-based Virtual Machine), called G-KVM. Our work is not merely a direct porting of GPUvm to KVM, since Xen and KVM have fundamental differences in their system architectures. Two major changes of G-KVM are aggregator and QEMU device model. The experiments show that G-KVM has better performance for MMIO operations than GPUvm on Xen hypervisor. For the compute-extensive experiments, execution time of G-KVM can achieve nearly 82% of native performance, which is similar to GPUvm. The performance scaling experiment shows that the performance of single machine with G-KVM can be scaled up to multiple virtual machines.
机译:图形处理单元(GPU)最初为计算机图形应用设计,已被广泛采用它们在许多域中的通用计算,由于其大量的计算能力。在云计算时代,GPU虚拟化成为数据中心更好管理GPU的重要技术。但是,大多数当前的解决方案都不完全虚拟化。他们需要修改客户端驱动程序或库,或限制硬件共享功能。唯一的全GPU虚拟化解决方案是GPUVM,但只能在Xen虚拟机管理程序上执行。在本文中,我们在KVM(基于内核虚拟机)上的完整GPU虚拟化解决方案,称为G-KVM。我们的作品不仅仅是GPUVM到KVM的直接移植,因为Xen和KVM对其系统架构具有根本差异。 G-KVM的两个主要变化是聚合器和QEMU设备模型。实验表明,G-KVM对Xen虚拟机管理程序的GPUVM具有更好的MMIO操作性能。对于计算广泛的实验,G-KVM的执行时间可以实现近82%的本机性能,类似于GPUVM。性能缩放实验表明,单台机器的性能可以缩放到多个虚拟机。

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