research-article

FlashNet: flash/network stack co-design

Authors:

Animesh Trivedi,

Nikolas Ioannou,

Bernard Metzler,

Patrick Stuedi,

Jonas Pfefferle,

Ioannis Koltsidas,

Kornilios Kourtis,

Thomas R. GrossAuthors Info & Claims

SYSTOR '17: Proceedings of the 10th ACM International Systems and Storage Conference

Article No.: 15, Pages 1 - 14

https://doi.org/10.1145/3078468.3078477

Published: 22 May 2017 Publication History

Abstract

During the past decade, network and storage devices have undergone rapid performance improvements, delivering ultra-low latency and several Gbps of bandwidth. Nevertheless, current network and storage stacks fail to deliver this hardware performance to the applications, often due to the loss of IO efficiency from stalled CPU performance. While many efforts attempt to address this issue solely on either the network or the storage stack, achieving high-performance for networked-storage applications requires a holistic approach that considers both.

In this paper, we present FlashNet, a software IO stack that unifies high-performance network properties with flash storage access and management. FlashNet builds on RDMA principles and abstractions to provide a direct, asynchronous, end-to-end data path between a client and remote flash storage. The key insight behind FlashNet is to co-design the stack's components (an RDMA controller, a flash controller, and a file system) to enable cross-stack optimizations and maximize IO efficiency. In micro-benchmarks, FlashNet improves 4kB network IOPS by 38.6% to 1.22M, decreases access latency by 43.5% to 50.4 µsecs, and prolongs the flash lifetime by 1.6--5.9× for writes. We illustrate the capabilities of FlashNet by building a Key-Value store, and porting a distributed data store that uses RDMA on it. The use of FlashNet's RDMA API improves the performance of KV store by 2×, and requires minimum changes for the ported data store to access remote flash devices.

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SYSTOR '17: Proceedings of the 10th ACM International Systems and Storage Conference

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ISBN:9781450350358

DOI:10.1145/3078468

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IBM Research
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Northeastern University
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University of Toronto

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