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G-KVM: A Full GPU Virtualization on KVM

机译:G-KVM:KVM上的完整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)最初是为计算机图形应用程序设计的,由于其强大的计算能力,已在许多领域广泛用于通用计算。在云计算时代,GPU虚拟化已成为一项重要技术,可以更好地管理数据中心中的GPU。但是,当前大多数解决方案都不是完全虚拟化。他们需要修改来宾驱动程序或库,或者限制硬件共享功能。唯一完整的GPU虚拟化解决方案是GPUvm,但是只能在Xen虚拟机管理程序上执行。在本文中,我们介绍了一种在KVM(基于内核的虚拟机)上的完整GPU虚拟化解决方案,称为G-KVM。我们的工作不仅是将GPUvm直接移植到KVM,因为Xen和KVM在其系统架构上有根本的区别。 G-KVM的两个主要变化是聚合器和QEMU设备模型。实验表明,在Xen虚拟机管理程序上,G-KVM的MMIO操作性能优于GPUvm。对于计算密集型实验,G-KVM的执行时间可以达到本机性能的近82%,这与GPUvm相似。性能扩展实验表明,具有G-KVM的单台计算机的性能可以扩展到多个虚拟机。

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