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An Empirical Study on Deoptimization in the Graal Compiler

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10369462" target="_blank" >RIV/00216208:11320/17:10369462 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.4230/LIPIcs.ECOOP.2017.30" target="_blank" >http://dx.doi.org/10.4230/LIPIcs.ECOOP.2017.30</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.4230/LIPIcs.ECOOP.2017.30" target="_blank" >10.4230/LIPIcs.ECOOP.2017.30</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    An Empirical Study on Deoptimization in the Graal Compiler

  • Original language description

    Managed language platforms such as the Java Virtual Machine or the Common Language Runtime rely on a dynamic compiler to achieve high performance. Besides making optimization decisions based on the actual program execution and the underlying hardware platform, a dynamic compiler is also in an ideal position to perform speculative optimizations. However, these tend to increase the compilation costs, because unsuccessful speculations trigger deoptimization and recompilation of the affected parts of the program, wasting previous work. Even though speculative optimizations are widely used, the costs of these optimizations in terms of extra compilation work has not been previously studied. In this paper, we analyze the behavior of the Graal dynamic compiler integrated in Oracle&apos;s HotSpot Virtual Machine. We focus on situations which cause program execution to switch from machine code to the interpreter, and compare application performance using three different deoptimization strategies which influence the amount of extra compilation work done by Graal. Using an adaptive deoptimization strategy, we managed to improve the average start-up performance of benchmarks from the DaCapo, ScalaBench, and Octane benchmark suites, mostly by avoiding wasted compilation work. On a single-core system, we observed an average speed-up of 6.4% for the DaCapo and ScalaBench workloads, and a speed-up of 5.1% for the Octane workloads; the improvement decreases with an increasing number of available CPU cores. We also find that the choice of a deoptimization strategy has negligible impact on steady-state performance. This indicates that the cost of speculation matters mainly during start-up, where it can disturb the delicate balance between executing the program and the compiler, but is quickly amortized in steady state.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/LTE117003" target="_blank" >LTE117003: ESTABLISH - Environmental Sensing To Act for a Better quality of LIfe: Smart Health</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 31st European Conference on Object-Oriented Programming

  • ISBN

    978-3-95977-035-4

  • ISSN

    1868-8969

  • e-ISSN

    neuvedeno

  • Number of pages

    30

  • Pages from-to

    1-30

  • Publisher name

    Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing

  • Place of publication

    Dagstuhl, Německo

  • Event location

    Barcelona, Španělsko

  • Event date

    Jun 18, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article