实现一个全局GPU管理插件的Slurm

Xue Wu, Xiang Long
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引用次数: 2

摘要

Slurm是一款广泛应用于Linux集群的资源管理软件。它有几个CPU选择插件,具有适合不同场景的不同分配策略。但是GPU的分配受到所选CPU位置的限制,因为GPU只能由在同一节点上运行的进程访问。此限制可能导致gpu等待作业,即使集群中有空闲的gpu。本文提出了一个面向Slurm的全局GPU管理插件。该插件采用远程GPU虚拟化方法,将GPU分离成全局GPU池,并将GPU分配过程与CPU解耦。池中的gpu可用于集群中任何节点上的CUDA作业。此外,我们还实现了两种GPU选择策略:最佳匹配策略和局部优先策略。实验表明,全局GPU管理插件缩短了作业的等待时间,有效地利用了集群中的GPU资源。
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Implementation of a global GPU management plugin for Slurm
Slurm is a widely used resource management software for Linux cluster. It has several CPU selection plugins with different allocation strategies suitable for different scenarios. But the GPU allocation is constrained by the selected CPU's location because GPUs can only be accessed by the process running on the same node. This restriction may cause job waiting for GPUs even if there are some free GPUs in the cluster. This paper presents a global GPU management plugin for Slurm. The plugin using remote GPU virtualization method detaches the GPUs to form a global GPU pool and decouples the GPU allocation procedure from the CPU's. GPUs in the pool are available to CUDA jobs on any node in the cluster. Furthermore, we implement two GPU selection strategy, best fit and local first. Experiments show the global GPU management plugin shorter the job's waiting time and makes efficient use of GPUs in the cluster.
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