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·인용수 3
·2018
GVTS: Global Virtual Time Fair Scheduling to Support Strict Fairness on Many Cores
Changdae Kim, Seungbeom Choi, Jaehyuk Huh
IF 6IEEE Transactions on Parallel and Distributed Systems
초록

Proportional fairness in CPU scheduling has been widely adopted to fairly distribute CPU shares corresponding to their weights. With the emergence of cloud environments, the proportionally fair scheduling has been extended to groups of threads or nested groups to support virtual machines or containers. Such proportional fairness has been supported by popular schedulers, such as Linux Completely Fair Scheduler (CFS) through virtual time scheduling. However, CFS, with a distributed runqueue per CPU, implements the virtual time scheduling locally. Across different queues, the virtual times of threads are not strictly maintained to avoid potential scalability bottlenecks. The uneven fluctuation of CPU shares caused by the limitations of CFS not only violates the fairness support for CPU assignments, but also significantly increases the tail latencies of latency-sensitive applications. To mitigate the limitations of CFS, this paper proposes a global virtual-time fair scheduler (GVTS), which enforces global virtual time fairness for threads and thread groups, even if they run across many physical cores. The new scheduler employs the hierarchical enforcement of target virtual time to enhance the scalability of schedulers, which is aware of the topology of CPU organization. We implemented GVTS in Linux kernel 4.6.4 with several optimizations to provide global virtual time efficiently. Our experimental results show that GVTS can almost eliminate the fairness violation of CFS for both non-grouped and grouped executions. Furthermore, GVTS can curtail the tail latency when latency-sensitive applications are co-running with batch tasks.

키워드
Computer scienceScalabilityLinux kernelVirtual machineScheduling (production processes)Cloud computingDistributed computingLatency (audio)Thread (computing)Parallel computing
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article
IF / 인용수
6 / 3
게재 연도
2018