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GaiaGPU: Sharing GPUs in Container Clouds

机译:GaiaGPU:在容器云中共享GPU

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摘要

Containers are widely used in clouds due to their lightweight and scalability. GPUs have powerful parallel processing capabilities that are adopted to accelerate the execution of applications. In a cloud environment, containers may require one or more GPUs to fulfill the resource requirement of application execution, while on the other hand exclusive GPU resource of a container usually results in underutilized resource. Therefore, how to share GPUs among containers becomes an attractive problem to cloud providers. In this paper, we propose an approach, called GaiaGPU, to sharing GPU memory and computing resources among containers. GaiaGPU partitions physical GPUs into multiple virtual GPUs and assigns the virtual GPUs to containers as request. Elastic resource allocation and dynamic resource allocation are adopted to improve resource utilization. The experimental results show that GaiaGPU only causes 1.015% of overhead by average and it effectively allocates and isolates GPU resources among containers
机译:容器因其轻巧和可扩展性而广泛用于云中。 GPU具有强大的并行处理功能,可用来加速应用程序的执行。在云环境中,容器可能需要一个或多个GPU来满足应用程序执行的资源要求,而另一方面,容器的专有GPU资源通常会导致资源利用不足。因此,如何在容器之间共享GPU成为云提供商关注的问题。在本文中,我们提出了一种称为GaiaGPU的方法,可以在容器之间共享GPU内存和计算资源。 GaiaGPU将物理GPU划分为多个虚拟GPU,并根据请求将虚拟GPU分配给容器。采用弹性资源分配和动态资源分配来提高资源利用率。实验结果表明,GaiaGPU平均仅产生1.015%的开销,并且可以有效地在容器之间分配和隔离GPU资源。

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