Jung-Gi Park, Un-Sook Choi, Seungwoo Kum, Jaewon Moon, Kyungyong Lee
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Accelerator-Aware Kubernetes Scheduler for DNN Tasks on Edge Computing Environment
The compute capability of edge devices is expanding owing to the wide adoption of edge computing for various application scenarios and specialized hardware explicitly developed for an edge environ-ment. A container orchestration platform, Kubernetes is widely used to maintain edge computing resources efficiently, but it suf-fers from a limited scheduling capacity. We present a design and implementation of an accelerator information extraction module to improve the scheduling capability of a standard Kubernetes imple-mentation by providing rich hardware information. Furthermore, we present a plausible advancement of the Kubernetes scheduler by considering detailed workload characteristics and attached spe-cialized accelerator hardware information.