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Generation Scavenging: A non-disruptive high performance storage reclamation algorithm

Author:

David UngarAuthors Info & Claims

SDE 1: Proceedings of the first ACM SIGSOFT/SIGPLAN software engineering symposium on Practical software development environments

April 1984

Pages 157 - 167

https://doi.org/10.1145/800020.808261

Published: 25 April 1984 Publication History

Abstract

Many interactive computing environments provide automatic storage reclamation and virtual memory to ease the burden of managing storage. Unfortunately, many storage reclamation algorithms impede interaction with distracting pauses. Generation Scavenging is a reclamation algorithm that has no noticeable pauses, eliminates page faults for transient objects, compacts objects without resorting to indirection, and reclaims circular structures, in one third the time of traditional approaches.

We have incorporated Generation Scavenging in Berkeley Smalltalk(BS), our Smalltalk-80 implementation, and instrumented it to obtain performance data. We are also designing a microprocessor with hardware support for Generation Scavenging.

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Cited By

Yamazaki TNakamaru TShioya RUgawa TChiba S(2023)Collecting Cyclic Garbage across Foreign Function Interfaces: Who Takes the Last Piece of Cake?Proceedings of the ACM on Programming Languages10.1145/35912447:PLDI(591-614)Online publication date: 6-Jun-2023
https://dl.acm.org/doi/10.1145/3591244
Chilukuri AAkram SBlackburn SPetrank E(2023)Analyzing and Improving the Scalability of In-Memory Indices for Managed Search EnginesProceedings of the 2023 ACM SIGPLAN International Symposium on Memory Management10.1145/3591195.3595272(15-29)Online publication date: 6-Jun-2023
https://dl.acm.org/doi/10.1145/3591195.3595272
Raza AChrysogelos PAnadiotis AAilamaki A(2023)One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version StorageProceedings of the ACM on Management of Data10.1145/35886991:1(1-25)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.1145/3588699
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Index Terms

Generation Scavenging: A non-disruptive high performance storage reclamation algorithm
1. Information systems
  1. Information storage systems
    1. Storage management
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
  2. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        File systems management
        Memory management
        Virtual memory

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Published In

cover image ACM Conferences

SDE 1: Proceedings of the first ACM SIGSOFT/SIGPLAN software engineering symposium on Practical software development environments

April 1984

196 pages

ISBN:0897911318

DOI:10.1145/800020

ACM SIGSOFT Software Engineering Notes Volume 9, Issue 3
May 1984
196 pages
ISSN:0163-5948
DOI:10.1145/390010
Editor:
Peter Henderson
Issue’s Table of Contents
ACM SIGPLAN Notices Volume 19, Issue 5
May 1984
196 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/390011
Editor:
Peter Henderson
Issue’s Table of Contents

Copyright © 1984 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 ACM 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 April 1984

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Cited By

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https://dl.acm.org/doi/10.1145/3591244
Chilukuri AAkram SBlackburn SPetrank E(2023)Analyzing and Improving the Scalability of In-Memory Indices for Managed Search EnginesProceedings of the 2023 ACM SIGPLAN International Symposium on Memory Management10.1145/3591195.3595272(15-29)Online publication date: 6-Jun-2023
https://dl.acm.org/doi/10.1145/3591195.3595272
Raza AChrysogelos PAnadiotis AAilamaki A(2023)One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version StorageProceedings of the ACM on Management of Data10.1145/35886991:1(1-25)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.1145/3588699
Kolokasis IEvdorou GAkram SKozanitis CPapagiannis AZakkak FPratikakis PBilas AAamodt TJerger NSwift M(2023)TeraHeap: Reducing Memory Pressure in Managed Big Data FrameworksProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 310.1145/3582016.3582045(694-709)Online publication date: 25-Mar-2023
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Zhao WBlackburn SMcKinley KJhala RDillig I(2022)Low-latency, high-throughput garbage collectionProceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation10.1145/3519939.3523440(76-91)Online publication date: 9-Jun-2022
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Yang YWu MChen HZang BBarbalace ABhatotia PAlvisi LCadar C(2021)Bridging the performance gap for copy-based garbage collectors atop non-volatile memoryProceedings of the Sixteenth European Conference on Computer Systems10.1145/3447786.3456246(343-358)Online publication date: 21-Apr-2021
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Banerjee SDevecsery DChen PNarayanasamy S(2020)Sound garbage collection for C using pointer provenanceProceedings of the ACM on Programming Languages10.1145/34282444:OOPSLA(1-28)Online publication date: 13-Nov-2020
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