research-article

Region-based memory management for GPU programming languages: enabling rich data structures on a spartan host

Authors:

Andrew LumsdaineAuthors Info & Claims

OOPSLA '14: Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications

Pages 141 - 155

https://doi.org/10.1145/2660193.2660244

Published: 15 October 2014 Publication History

Abstract

Graphics processing units (GPUs) can effectively accelerate many applications, but their applicability has been largely limited to problems whose solutions can be expressed neatly in terms of linear algebra. Indeed, most GPU programming languages limit the user to simple data structures - typically only multidimensional rectangular arrays of scalar values. Many algorithms are more naturally expressed using higher level language features, such as algebraic data types (ADTs) and first class procedures, yet building these structures in a manner suitable for a GPU remains a challenge. We present a region-based memory management approach that enables rich data structures in Harlan, a language for data parallel computing. Regions enable rich data structures by providing a uniform representation for pointers on both the CPU and GPU and by providing a means of transferring entire data structures between CPU and GPU memory. We demonstrate Harlan's increased expressiveness on several example programs and show that Harlan performs well on more traditional data-parallel problems.

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Cited By

Paudyal PLee JBanerjee AGupta S(2019)A Comparison of Techniques for Sign Language Alphabet Recognition Using Armband WearablesACM Transactions on Interactive Intelligent Systems10.1145/31509749:2-3(1-26)Online publication date: 27-Mar-2019
https://dl.acm.org/doi/10.1145/3150974
Sciascio CStrohmaier DErrecalde MVeas E(2019)Interactive Quality Analytics of User-generated ContentACM Transactions on Interactive Intelligent Systems10.1145/31509739:2-3(1-42)Online publication date: 27-Mar-2019
https://dl.acm.org/doi/10.1145/3150973
Goodarzi BKhorasani FSarkar VGoswami D(2019)High Performance Multilevel Graph Partitioning on GPU2019 International Conference on High Performance Computing & Simulation (HPCS)10.1109/HPCS48598.2019.9188120(769-778)Online publication date: Jul-2019
https://doi.org/10.1109/HPCS48598.2019.9188120
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Index Terms

Region-based memory management for GPU programming languages: enabling rich data structures on a spartan host
1. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Runtime environments
    2. General programming languages
      1. Language types
        Concurrent programming languages
        Distributed programming languages
        Functional languages
        Parallel programming languages
  2. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Memory management
        Garbage collection

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cover image ACM Conferences

OOPSLA '14: Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications

October 2014

946 pages

ISBN:9781450325851

DOI:10.1145/2660193

General Chair:
Andrew Black
Portland State University, USA
,
Program Chair:
Todd Millstein
University of California, Los Angeles, USA

ACM SIGPLAN Notices Volume 49, Issue 10
OOPSLA '14
October 2014
907 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/2714064
Editor:
Andy Gill
University of Kansas, Lawrence, KS
Issue’s Table of Contents

Copyright © 2014 ACM.

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Published: 15 October 2014

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SPLASH '14: Conference on Systems, Programming, and Applications: Software for Humanity

October 20 - 24, 2014

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OOPSLA '14 Paper Acceptance Rate 52 of 186 submissions, 28%;

Overall Acceptance Rate 268 of 1,244 submissions, 22%

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Cited By

Paudyal PLee JBanerjee AGupta S(2019)A Comparison of Techniques for Sign Language Alphabet Recognition Using Armband WearablesACM Transactions on Interactive Intelligent Systems10.1145/31509749:2-3(1-26)Online publication date: 27-Mar-2019
https://dl.acm.org/doi/10.1145/3150974
Sciascio CStrohmaier DErrecalde MVeas E(2019)Interactive Quality Analytics of User-generated ContentACM Transactions on Interactive Intelligent Systems10.1145/31509739:2-3(1-42)Online publication date: 27-Mar-2019
https://dl.acm.org/doi/10.1145/3150973
Goodarzi BKhorasani FSarkar VGoswami D(2019)High Performance Multilevel Graph Partitioning on GPU2019 International Conference on High Performance Computing & Simulation (HPCS)10.1109/HPCS48598.2019.9188120(769-778)Online publication date: Jul-2019
https://doi.org/10.1109/HPCS48598.2019.9188120
Hovgaard AHenriksen TElsman M(2019)High-Performance Defunctionalisation in FutharkZivilgesellschaft und Wohlfahrtsstaat im Wandel10.1007/978-3-030-18506-0_7(136-156)Online publication date: 24-Apr-2019
https://doi.org/10.1007/978-3-030-18506-0_7
Shahar SBergman SSilberstein M(2018)ActivePointersACM SIGOPS Operating Systems Review10.1145/3273982.327399052:1(84-95)Online publication date: 28-Aug-2018
https://dl.acm.org/doi/10.1145/3273982.3273990
Kannan SGavrilovska AGupta VSchwan K(2018)HeteroOSACM SIGOPS Operating Systems Review10.1145/3273982.327398552:1(13-26)Online publication date: 28-Aug-2018
https://dl.acm.org/doi/10.1145/3273982.3273985
Alam HZhang TErez MEtsion Y(2018)Do-It-Yourself Virtual Memory TranslationACM SIGOPS Operating Systems Review10.1145/3273982.327398452:1(1-12)Online publication date: 28-Aug-2018
https://dl.acm.org/doi/10.1145/3273982.3273984
Springer MWauligmann PMasuhara HElsman MGrelck CKloeckner APadua DSolomonik E(2017)Modular array-based GPU computing in a dynamically-typed languageProceedings of the 4th ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming10.1145/3091966.3091974(48-55)Online publication date: 18-Jun-2017
https://dl.acm.org/doi/10.1145/3091966.3091974
Ko BHan SPark YJeon MLee B(2017)A Comparative Study of Programming Environments Exploiting Heterogeneous SystemsIEEE Access10.1109/ACCESS.2017.27087385(10081-10092)Online publication date: 2017
https://doi.org/10.1109/ACCESS.2017.2708738
Shahar SBergman SSilberstein M(2016)ActivePointersACM SIGARCH Computer Architecture News10.1145/3007787.300120044:3(596-608)Online publication date: 18-Jun-2016
https://dl.acm.org/doi/10.1145/3007787.3001200
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