Fairness-Efficiency Allocation of CPU-GPU Heterogeneous Resources
| Autor: | Jianguo Yao, Bingsheng He, Haibing Guan, Zhengwei Qi, Qiumin Lu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Information Systems and Management
Computer Networks and Communications Computer science Heuristic (computer science) business.industry Cloud gaming Distributed computing Cloud computing computer.software_genre Computer Science Applications Hardware and Architecture Virtual machine Resource allocation Algorithm design Resource management Performance improvement business computer |
| Zdroj: | IEEE Transactions on Services Computing. 12:474-488 |
| ISSN: | 2372-0204 |
| Popis: | Considering the performance improvement the cloud technology provides by processing workloads in parallel, applications and services are now migrating to online clouds. In a cloud platform, workloads can be executed in a virtualized environment to have a great improvement of the resource utilization. However, there is a new challenge in the allocation problem, which is quantifying and optimizing the fairness and efficiency of heterogeneous resources (CPUs and GPUs) required by applications such as cloud gaming. The solving approach needs scalarization methods of the requirement vector, relevant functions for fairness metrics, and an acceptable algorithm to solve that, where the difficulties mainly locate. We design an iterative, dynamic-adaptive heuristic solving algorithm Fairness-Efficiency Allocation (FEA) and optimize the implementation on a virtualized platform, which collects runtime data, allocates resources and reports differences. Data are recorded and analyzed to discover the effect of the allocation in different situations, including the promotion of fairness and the effect on the frame rate of the workloads. The result indicates that there is a considerable fairness improvement after the resource allocation, especially in situations that many virtual machines are executing simultaneously. Compared with the VGASA strategy, the fairness metric value improved 45 percent in three virtual machines’ situation. |
| Databáze: | OpenAIRE |
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