Article

Incremental whole program optimization and compilation

Authors:

Patrick W. Sathyanathan,

Ten H. TzenAuthors Info & Claims

CGO '17: Proceedings of the 2017 International Symposium on Code Generation and Optimization

Pages 221 - 232

Published: 04 February 2017 Publication History

Abstract

Most modern compilers for statically typed high level languages perform whole program optimization and compilation in order to generate highly optimized code. Whole program analysis and optimization has the advantage of providing the compiler with visibility to the entire program. This allows information to be propagated across procedures to improve the quality of the generated code. The main disadvantage of existing systems with this capability however, is that recompiling a program after an edit incurs the cost of reanalyzing and regenerating code for all functions.

Compiler throughput is crucial for developers' everyday edit-compile-test cycle as well as build lab's automated rolling build. Improving the throughput of such builds significantly improves developer productivity and lab efficiency.

We present a practical and extensible framework for incremental whole program optimization (WPO) and compilation. It uses two program abstractions, namely a dependence graph representing the program entities that the code for each function depends upon, and lattices of data-flow information that affect the code generated. These abstractions are used to minimize the number of functions that must be reanalyzed and recompiled after a program edit. The framework uses a simple and fast checksum technique for detecting edits to functions and variables, and experimental evidence that this technique works well in practice. We also present a novel mechanism for achieving the no code generation diff requirement in the presence of multi-level inline expansion.

The system has been successfully implemented in the state-of-the-art commercial quality Visual C/C++ compiler and achieves up to 7X compilation speedup for typical edits.

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Cited By

Nougrahiya ANandivada V(2024)Homeostasis: Design and Implementation of a Self-Stabilizing CompilerACM Transactions on Programming Languages and Systems10.1145/364930846:2(1-58)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.1145/3649308
El Hajj IJablin TMilojicic DHwu W(2017)SAVI objects: sharing and virtuality incorporatedProceedings of the ACM on Programming Languages10.1145/31338691:OOPSLA(1-24)Online publication date: 12-Oct-2017
https://dl.acm.org/doi/10.1145/3133869

Incremental whole program optimization and compilation
1. Software and its engineering
  1. Software notations and tools

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Information & Contributors

Information

Published In

cover image ACM Conferences

CGO '17: Proceedings of the 2017 International Symposium on Code Generation and Optimization

February 2017

317 pages

ISBN:9781509049318

General Chair:
Vijay Janapa Reddi
University of Texas at Austin, USA
,
Program Chairs:
Aaron Smith
Microsoft Research, UK / University of Edinburgh, UK
,
Lingjia Tang
University of Michigan, USA

Sponsors

SIGPLAN: ACM Special Interest Group on Programming Languages
SIGMICRO: ACM Special Interest Group on Microarchitectural Research and Processing
IEEE-CS: Computer Society

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IEEE Press

Publication History

Published: 04 February 2017

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CGO '17

Sponsor:

CGO '17: 15th Annual IEEE/ACM International Symposium on Code Generation and Optimization

February 4 - 8, 2017

Austin, USA

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CGO '17 Paper Acceptance Rate 26 of 116 submissions, 22%;

Overall Acceptance Rate 312 of 1,061 submissions, 29%

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Cited By

Nougrahiya ANandivada V(2024)Homeostasis: Design and Implementation of a Self-Stabilizing CompilerACM Transactions on Programming Languages and Systems10.1145/364930846:2(1-58)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.1145/3649308
El Hajj IJablin TMilojicic DHwu W(2017)SAVI objects: sharing and virtuality incorporatedProceedings of the ACM on Programming Languages10.1145/31338691:OOPSLA(1-24)Online publication date: 12-Oct-2017
https://dl.acm.org/doi/10.1145/3133869

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