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Thursday, July 11 • 9:45am - 10:05am
Multi Queue Fair Queuing

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Modern high-speed devices (e.g., network adapters, storage, accelerators) use new host interfaces, which expose multiple software queues directly to the device. These multi-queue interfaces allow mutually distrusting applications to access the device without any cross-core interaction, enabling throughput in the order of millions of IOP/s on multicore systems. Unfortunately, while independent device access is scalable, it also introduces a new problem: unfairness. Mechanisms that were used to provide fairness for older devices are no longer tenable in the wake of multi-queue design, and straightforward attempts to re-introduce it would require cross-core synchronization that undermines the scalability for which multiple queues were designed.

To address these challenges, we present Multi-Queue Fair Queueing (MQFQ), the first fair, work-conserving scheduler suitable for multi-queue systems. Specifically, we (1) reformulate a classical fair queueing algorithm to accommodate multi-queue designs, and (2) describe a scalable implementation that bounds potential unfairness while minimizing synchronization overhead. Our implementation of MQFQ in Linux 4.15 demonstrates both fairness and high throughput. Evaluation with an NVMe over RDMA fabric (NVMf) device shows that MQFQ can reach up to 3.1 Million IOP/s on a single machine — $20\times$ higher than the state-of-the-art Linux Budget Fair Queueing. Compared to a system with no fairness, MQFQ reduces the slowdown caused by an antagonist from $3.78\times$ to $1.33\times$ for the FlashX workload and from $6.57\times$ to $1.03\times$ for the Aerospike workload ($2\times$ is considered "fair" slowdown).

Speakers
MH

Mohammad Hedayati

University of Rochester
KS

Kai Shen

Google
ML

Michael L. Scott

University of Rochester


Thursday July 11, 2019 9:45am - 10:05am PDT
USENIX ATC Track II: Grand Ballroom VII–IX