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

机译:雾计算中由于GPU传递而导致虚拟机性能下降的缓解技术

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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.
机译:在雾计算环境中,随着数据大小的增加和计算的复杂化,对高性能计算的需求也在增加。改善虚拟机(VM)性能的最流行的方法之一是为VM分配图形处理单元(GPU),以支持图形处理单元(GPGPU)操作上的通用计算。直接传递通常在VM中用于GPU,在云中非常流行,因为VM可以使用GPU的全部功能,并且不会因虚拟化而导致性能下降。直接传递对于提高VM的性能非常有用。但是,由于在基于VM的中央处理单元(CPU)使用时间进行操作的VM调度器中未考虑GPU使用时间,因此执行GPGPU操作的VM降低了其他VM的性能。在本文中,我们通过实验分析了执行GPGPU操作(GPGPU密集型VM)的VM对其他VM的影响。然后,我们提出了一种通过动态分配虚拟机的资源使用时间并防止GPGPU密集型虚拟机优先级抢占来减轻其他虚拟机性能下降的方法。

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