Article

ThinLTO: scalable and incremental LTO

Authors:

Teresa Johnson,

Xinliang David LiAuthors Info & Claims

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

Pages 111 - 121

Published: 04 February 2017 Publication History

Abstract

Cross-Module Optimization (CMO) is an effective means for improving runtime performance, by extending the scope of optimizations across source module boundaries. Two CMO approaches are Link-Time Optimization (LTO) and Lightweight Inter-Procedural Optimization (LIPO). However, each of these solutions has limitations that prevent it from being enabled by default. ThinLTO is a new approach that attempts to address these limitations, with a goal of being enabled more broadly. ThinLTO aims to be as scalable as a regular non-LTO build, enabling CMO on large applications and machines without large memory configurations, while also integrating well with distributed and incremental build systems. This is achieved through fast purely summary-based Whole-Program Analysis (WPA), the only serial step, without reading or writing the program’s Intermediate Representation (IR). Instead, CMO is applied during fully parallel optimization backends.

This paper describes the motivation behind ThinLTO, its overall design, and current implementation in LLVM. Results from SPEC cpu2006 benchmarks and several large real-world applications illustrate that ThinLTO can scale as well as a non-LTO build while enabling most of the CMO performed with a full LTO build.

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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

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Published: 04 February 2017

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CGO '17

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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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https://dl.acm.org/doi/10.1145/3652032.3657575
Li JLi QWan HXue CHong JPark J(2024)Binary Folding Compression for Efficient Software DistributionProceedings of the 39th ACM/SIGAPP Symposium on Applied Computing10.1145/3605098.3636006(169-176)Online publication date: 8-Apr-2024
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