H-BFQ: Supporting Multi-Level Hierarchical Cgroup in BFQ Scheduler

Oh, Kyung-Yul; Park, Jonggyu; Eom, Young Ik

doi:10.1109/bigcomp48618.2020.00-48

Cited by 4 publications

(5 citation statements)

References 4 publications

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Section: ) Improving Block I/o Latency For Fast Nvme Devicesmentioning

confidence: 99%

“…Previous works [100], [241], [260], [261], [262], [263], [264], [265] propose several techniques to mitigate block I/O latencies for fast NVMe devices. These techniques include software [100], [261], [262], [263], [264], [265] and hardware solutions [241], [260] to provide lower I/O access latency [100], [263], [264], page fault handling [260], and I/O scheduling [241], [261], [265]. Even though these techniques are promising solutions to reduce the high block I/O latencies, they require substantial changes in the hardware and the software stack, which are outside the scope of this work, but can also be used in our proposed system.…”

Section: ) Improving Block I/o Latency For Fast Nvme Devicesmentioning

confidence: 99%

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Extending Memory Capacity in Modern Consumer Systems With Emerging Non-Volatile Memory: Experimental Analysis and Characterization Using the Intel Optane SSD

Oliveira,

Ghose,

Gómez-Luna

et al. 2023

IEEE Access

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DRAM scalability is becoming a limiting factor to the available memory capacity in consumer devices. As a potential solution, manufacturers have introduced emerging non-volatile memories (NVMs) into the market, which can be used to increase the memory capacity of consumer devices by augmenting or replacing DRAM. In this work, we provide the first analysis of the impact of extending the main memory space of consumer devices using off-the-shelf NVMs. We equip real web-based Chromebook computers with the Intel Optane solid-state drive (SSD), which contains state-of-the-art low-latency NVM, and use the NVM as swap space. We analyze the performance and energy consumption of the Optane-equipped Chromebooks, and compare this with (i) a baseline system with double the amount of DRAM than the system with the NVM-based swap space; and (ii) a system where the Intel Optane SSD is naively replaced with a state-of-theart NAND-flash-based SSD. Our experimental analysis reveals that while Optane-based swap space provides a cost-effective way to alleviate the DRAM capacity bottleneck in consumer devices, naive integration of the Optane SSD leads to several system-level overheads, mostly related to (1) the Linux block I/O layer, which can negatively impact overall performance; and (2) the off-chip traffic to the swap space, which can negatively impact energy consumption. To reduce the Linux block I/O layer overheads, we tailor several system-level mechanisms (i.e., the I/O scheduler and the I/O request completion mechanism) to the currentlyrunning application's access pattern. To reduce the off-chip traffic overhead, we leverage an operating system feature (called Zswap) that allocates some DRAM space to be used as a compressed in-DRAM cache for data swapped between DRAM and the Intel Optane SSD, significantly reducing energy consumption caused by the off-chip traffic to the swap space. We conclude that emerging NVMs are a cost-effective solution to alleviate the DRAM capacity bottleneck in consumer devices, which can be further enhanced by tailoring system-level mechanisms to better leverage the characteristics of our workloads and the NVM.

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Section: ) Improving Block I/o Latency For Fast Nvme Devicesmentioning

confidence: 99%

Section: ) Improving Block I/o Latency For Fast Nvme Devicesmentioning

confidence: 99%

Extending Memory Capacity in Modern Consumer Systems With Emerging Non-Volatile Memory: Experimental Analysis and Characterization Using the Intel Optane SSD

Oliveira,

Ghose,

Gómez-Luna

et al. 2023

IEEE Access

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“…In conventional systems, CFQ and BFQ I/O schedulers use this I/O weight value (blkio.weight) [11], [20] when they decide how many I/Os will be dispatched from the request queues in the block layer [18]. Specifically, the CFQ scheduler gives higher-weighted applications more time for processing I/O so that the block-level I/O proportionality can be achieved according to their I/O weights [21].…”

Section: Cgroup and Proportional I/o Sharingmentioning

confidence: 99%

Weight-Aware Cache for Application-Level Proportional I/O Sharing

Park

Eom

2022

IEEE Trans. Comput.

Self Cite

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Virtualization technology has enabled server consolidation where multiple servers are co-located on a single physical machine to improve resource utilization. In such systems, proportional I/O sharing is critical to meet the SLO (Service-Level Objectives) of the applications running in each virtual instance. However, previous studies focus on block-level I/O proportionality without considering the upper-layer I/O caches, which handle I/O requests on behalf of the underlying storage devices, thereby failing to achieve application-level proportional I/O sharing. To overcome this limitation, we propose a new cache management scheme, Weight-aware Cache (WaC), which reflects the I/O weights on cache allocation and reclamation. Specifically, WaC prioritizes higher-weighted applications in the lock acquisition process of cache allocation by re-ordering the lock waiting queue based on I/O weight. Additionally, WaC keeps the number of cache entries of each application proportional to its I/O weight, through weight-aware cache reclamation. To verify the efficacy of our scheme, we implement and evaluate WaC on both the page cache and bcache. The experimental results demonstrate that our scheme improves I/O proportionality with negligible overhead in various cases.

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“…Improving Block I/O Latency for Fast NVMe Devices. Previous works [97,227,[237][238][239][240][241] propose several techniques to mitigate block I/O latencies for fast NVMe devices. These techniques include software [97,[238][239][240][241] and hardware solutions [227,237] to provide lower I/O access latency [97,240,241], page fault handling [237], and I/O scheduling [227,238].…”

Section: Related Workmentioning

confidence: 99%

“…Previous works [97,227,[237][238][239][240][241] propose several techniques to mitigate block I/O latencies for fast NVMe devices. These techniques include software [97,[238][239][240][241] and hardware solutions [227,237] to provide lower I/O access latency [97,240,241], page fault handling [237], and I/O scheduling [227,238]. Even though these techniques are promising solutions to reduce the high block I/O latencies, they require substantial changes in the hardware and the software stack, which are outside the scope of this work, but can also be used in our proposed system.…”

Section: Related Workmentioning

confidence: 99%