Mitigation technique for performance degradation of virtual machine owing to GPU pass-through in fog computing

As the size of data increases and computation becomes complicated in fog computing environments, the need for highperformance computation is increasing. One of the most popular ways to improve the performance of a virtual machine (VM) is to allocate a graphic processing unit (GPU) to the VM for supp...

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Vydané v:Journal of communications and networks Ročník 20; číslo 3; s. 257 - 265
Hlavní autori: Kang, Jihun, Yu, Heonchang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Seoul Editorial Department of Journal of Communications and Networks 01.06.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
한국통신학회
Predmet:
Central Processing Unit
Central processing units
Cloud computing
CPUs
Degradation
Edge computing
Fog computing
general purpose computing on graphic processing unit (GPGPU)
Graphics processing units
Performance degradation
Performance enhancement
Performance evaluation
performance isolation
Virtual environments
Virtual machine monitors
Virtualization
전자/정보통신공학
ISSN:1229-2370, 1976-5541
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Popis
Shrnutí:As the size of data increases and computation becomes complicated in fog computing environments, the need for highperformance computation is increasing. One of the most popular ways to improve the performance of a virtual machine (VM) is to allocate a graphic processing unit (GPU) to the VM for supporting general purpose computing on graphic processing unit (GPGPU) operations. The direct pass-through, often used for GPUs in VMs, is popular in the cloud because VMs can use the full functionality of the GPU and experience virtually no performance degradation owing to virtualization. Direct pass-through is very useful for improving the performance of VMs. However, since the GPU usage time is not considered in the VM scheduler that operates based on the central processing unit (CPU) usage time of the VM, the VM performing the GPGPU operation degrades the performance of other VMs. In this paper, we analyze the effect of the VM performing the GPGPU operation (GPGPU-intensive VM) on other VMs through experiments. Then, we propose a method to mitigate the performance degradation of other VMs by dynamically allocating the resource usage time of the VM and preventing the priority preemption of the GPGPU-intensive VM.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1229-2370
1976-5541
DOI:10.1109/JCN.2018.000038