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A Virtual Multi-Channel GPU Fair Scheduling Method for Virtual Machines.

Authors :
Tan, Huailiang
Tan, Yanjie
He, Xiaofei
Li, Kenli
Li, Keqin
Source :
IEEE Transactions on Parallel & Distributed Systems. 2/1/2019, Vol. 30 Issue 2, p257-270. 14p.
Publication Year :
2019

Abstract

In modern virtual computing environment, the 2D/3D rendering performance and parallel computing potential of GPU (graphics processing unit) must be fully exploited for multiple virtual machines (VMs). Existing GPU virtualization techniques are unable to take full advantage of a GPU's powerful 2D/3D hardware-accelerated graphics rendering performance or parallel computing potential, or it has not been considered that the internal resources of a GPU domain are fairly allocated between VMs with different performance requirements. Therefore, we propose a multi-channel GPU virtualization architecture (VMCG), model the corresponding credit allocating and transferring mechanisms, and redesign the virtual multi-channel GPU fair-scheduling algorithm. VMCG provides a separate V-Channel for each guest VM (DomU) that competes with other VMs for the same physical GPU resources, and each DomU submits command request blocks to its respective V-Channel according to the corresponding DomU ID. Through the virtual multi-channel GPU fair-scheduling algorithm, not only do multiple DomUs make full use of native GPU hardware acceleration, but the fairness of GPU resource allocation is significantly improved during GPU-intensive workloads from multiple DomUs running on the same host. Experimental results show that, for 2D/3D graphics applications, performance is close to 96 percent of that of the native GPU, performance is improved by approximately 500 percent for parallel computing applications, and GPU resource-allocation fairness is improved by approximately 60-80 percent. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10459219
Volume :
30
Issue :
2
Database :
Academic Search Index
Journal :
IEEE Transactions on Parallel & Distributed Systems
Publication Type :
Academic Journal
Accession number :
134231452
Full Text :
https://doi.org/10.1109/TPDS.2018.2865341