DocumentCode
172942
Title
GPU Passthrough Performance: A Comparison of KVM, Xen, VMWare ESXi, and LXC for CUDA and OpenCL Applications
Author
Walters, J.P. ; Younge, A.J. ; Dong In Kang ; Ke Thia Yao ; Mikyung Kang ; Crago, S.P. ; Fox, G.C.
Author_Institution
Inf. Sci. Inst., Univ. of Southern California, Arlington, VA, USA
fYear
2014
fDate
June 27 2014-July 2 2014
Firstpage
636
Lastpage
643
Abstract
As more scientific workloads are moved into the cloud, the need for high performance accelerators increases. Accelerators such as GPUs offer improvements in both performance and power efficiency over traditional multi-core processors, however, their use in the cloud has been limited. Today, several common hypervisors support GPU passthrough, but their performance has not been systematically characterized. In this paper we show that low overhead GPU passthrough is achievable across 4 major hypervisors and two processor microarchitectures. We compare the performance of two generations of NVIDIA GPUs within the Xen, VMWare ESXi, and KVM hypervisors, and we also compare the performance to that of Linux Containers (LXC). We show that GPU passthrough to KVM achieves 98 -- 100% of the base system´s performance across two architectures, while Xen and VMWare achieve 96 -- 99% of the base systems performance, respectively. In addition, we describe several valuable lessons learned through our analysis and share the advantages and disadvantages of each hypervisor/GPU passthrough solution.
Keywords
cloud computing; graphics processing units; parallel architectures; performance evaluation; CUDA; GPU passthrough performance; KVM; LXC; OpenCL; VMWare ESXi; Xen; cloud infrastructure; high performance accelerators; Benchmark testing; Cloud computing; Graphics processing units; Kernel; Linux; Virtual machine monitors; Virtual machining; GPU passthrough; KVM; LXC; VMWare; Xen; virtualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Cloud Computing (CLOUD), 2014 IEEE 7th International Conference on
Conference_Location
Anchorage, AK
Print_ISBN
978-1-4799-5062-1
Type
conf
DOI
10.1109/CLOUD.2014.90
Filename
6973796
Link To Document