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CrossPrefetch: Accelerating I/O Prefetching for Modern Storage

Authors:

Rekha Pitchumani,

Manish Parashar,

Sudarsun KannanAuthors Info & Claims

ASPLOS '24: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 1

Pages 102 - 116

https://doi.org/10.1145/3617232.3624872

Published: 17 April 2024 Publication History

Abstract

We introduce CrossPrefetch, a novel cross-layered I/O prefetching mechanism that operates across the OS and a user-level runtime to achieve optimal performance. Existing OS prefetching mechanisms suffer from rigid interfaces that do not provide information to applications on the prefetch effectiveness, suffer from high concurrency bottlenecks, and are inefficient in utilizing available system memory. CrossPrefetch addresses these limitations by dividing responsibilities between the OS and runtime, minimizing overhead, and achieving low cache misses, lock contentions, and higher I/O performance.

CrossPrefetch tackles the limitations of rigid OS prefetching interfaces by maintaining and exporting cache state and prefetch effectiveness to user-level runtimes. It also addresses scalability and concurrency bottlenecks by distinguishing between regular I/O and prefetch operations paths and introduces fine-grained prefetch indexing for shared files. Finally, CrossPrefetch designs low-interference access pattern prediction combined with support for adaptive and aggressive techniques to exploit memory capacity and storage bandwidth. Our evaluation of CrossPrefetch, encompassing microbenchmarks, macrobenchmarks, and real-world workloads, illustrates performance gains of up to 1.22x-3.7x in I/O throughput. We also evaluate CrossPrefetch across different file systems and local and remote storage configurations.

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Cited By

Zhang JNguyen MKashyap SKannan S(2024)Context-aware Prefetching for Near-Storage AcceleratorsProceedings of the 16th ACM Workshop on Hot Topics in Storage and File Systems10.1145/3655038.3665956(131-136)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3655038.3665956

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Information

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cover image ACM Conferences

ASPLOS '24: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 1

April 2024

494 pages

ISBN:9798400703720

DOI:10.1145/3617232

General Chairs:
Nael Abu-Ghazaleh,
Rajiv Gupta,
Program Chairs:
Madan Musuvathi,
Dan Tsafrir

Copyright © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 17 April 2024

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ASPLOS '24: 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 1

April 27 - May 1, 2024

CA, La Jolla, USA

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Cited By

Zhang JNguyen MKashyap SKannan S(2024)Context-aware Prefetching for Near-Storage AcceleratorsProceedings of the 16th ACM Workshop on Hot Topics in Storage and File Systems10.1145/3655038.3665956(131-136)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3655038.3665956

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