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Optimal code selection in DAGs

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M. Anton ErtlAuthors Info & Claims

POPL '99: Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages

Pages 242 - 249

https://doi.org/10.1145/292540.292562

Published: 01 January 1999 Publication History

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Abstract

We extend the tree parsing approach to code selection to DAGs. In general, our extension does not produce the optimal code selection for all DAGs (this problem would be NP-complete), but for certain code selection grammars, it does. We present a method for checking whether a code selection grammar belongs to this set of DAG-optimal grammars, and use this method to check code selection grammars adapted from lcc: the grammars for the MIPS and SPARC architectures are DAG-optimal, and the code selection grammar for the 386 architecture is almost DAG-optimal.

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Cited By

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Thier PErtl MKrall ADubach CXue J(2018)Fast and flexible instruction selection with constraintsProceedings of the 27th International Conference on Compiler Construction10.1145/3178372.3179501(93-103)Online publication date: 24-Feb-2018
https://dl.acm.org/doi/10.1145/3178372.3179501
Kessler C(2018)Compiling for VLIW DSPsHandbook of Signal Processing Systems10.1007/978-3-319-91734-4_27(979-1020)Online publication date: 14-Oct-2018
https://doi.org/10.1007/978-3-319-91734-4_27
Blindell GCarlsson MLozano RSchulte C(2017)Complete and Practical Universal Instruction SelectionACM Transactions on Embedded Computing Systems10.1145/312652816:5s(1-18)Online publication date: 27-Sep-2017
https://dl.acm.org/doi/10.1145/3126528
Show More Cited By

Index Terms

Optimal code selection in DAGs
1. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Source code generation
2. Theory of computation

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POPL '99: Proceedings of the 26th ACM SIGPLAN-SIGACT symposium on Principles of programming languages

January 1999

324 pages

ISBN:1581130953

DOI:10.1145/292540

Chairmen:
Andrew Appel
Princeton Univ., Princeton, NJ
,
Alex Aiken
Univ. of California, Berkeley

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: 01 January 1999

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POPL99

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POPL99: Symposium on Prinicples of Programming Languages 1999

January 20 - 22, 1999

Texas, San Antonio, USA

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POPL '99 Paper Acceptance Rate 24 of 136 submissions, 18%;

Overall Acceptance Rate 824 of 4,130 submissions, 20%

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POPL '25

Sponsor:
sigplan

The 52nd Annual ACM SIGPLAN Symposium on Principles of Programming Languages

January 19 - 25, 2025

Denver , CO , USA

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Cited By

View all

Thier PErtl MKrall ADubach CXue J(2018)Fast and flexible instruction selection with constraintsProceedings of the 27th International Conference on Compiler Construction10.1145/3178372.3179501(93-103)Online publication date: 24-Feb-2018
https://dl.acm.org/doi/10.1145/3178372.3179501
Kessler C(2018)Compiling for VLIW DSPsHandbook of Signal Processing Systems10.1007/978-3-319-91734-4_27(979-1020)Online publication date: 14-Oct-2018
https://doi.org/10.1007/978-3-319-91734-4_27
Blindell GCarlsson MLozano RSchulte C(2017)Complete and Practical Universal Instruction SelectionACM Transactions on Embedded Computing Systems10.1145/312652816:5s(1-18)Online publication date: 27-Sep-2017
https://dl.acm.org/doi/10.1145/3126528
Hjort Blindell GCastañeda Lozano RCarlsson MSchulte C(2015)Modeling Universal Instruction SelectionPrinciples and Practice of Constraint Programming10.1007/978-3-319-23219-5_42(609-626)Online publication date: 13-Aug-2015
https://doi.org/10.1007/978-3-319-23219-5_42
Kessler C(2013)Compiling for VLIW DSPsHandbook of Signal Processing Systems10.1007/978-1-4614-6859-2_36(1177-1214)Online publication date: 10-May-2013
https://doi.org/10.1007/978-1-4614-6859-2_36
Murray AFranke BEidt CHoller ASrinivasan UAmarasinghe S(2012)Compiling for automatically generated instruction set extensionsProceedings of the Tenth International Symposium on Code Generation and Optimization10.1145/2259016.2259019(13-22)Online publication date: 31-Mar-2012
https://dl.acm.org/doi/10.1145/2259016.2259019
Youn JLee JPaek YLee JScharwaechter HLeupers R(2011)Fast graph-based instruction selection for multi-output instructionsSoftware—Practice & Experience10.1002/spe.103441:6(717-736)Online publication date: 1-May-2011
https://dl.acm.org/doi/10.1002/spe.1034
Buchwald SZwinkau AKathail VTatge RBarua R(2010)Instruction selection by graph transformationProceedings of the 2010 international conference on Compilers, architectures and synthesis for embedded systems10.1145/1878921.1878926(31-40)Online publication date: 24-Oct-2010
https://dl.acm.org/doi/10.1145/1878921.1878926
Kessler C(2010)Compiling for VLIW DSPsHandbook of Signal Processing Systems10.1007/978-1-4419-6345-1_22(603-638)Online publication date: 16-Jul-2010
https://doi.org/10.1007/978-1-4419-6345-1_22
Ebner DBrandner FScholz BKrall AWiedermann PKadlec A(2008)Generalized instruction selection using SSA-graphsACM SIGPLAN Notices10.1145/1379023.137566343:7(31-40)Online publication date: 12-Jun-2008
https://dl.acm.org/doi/10.1145/1379023.1375663
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