Mercurial > hg > graal-jvmci-8
annotate doc/design/graal_compiler.tex @ 2682:c5739b99762a
New field store / guard / frame state example.
author | Thomas Wuerthinger <thomas@wuerthinger.net> |
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date | Mon, 16 May 2011 17:26:31 +0200 |
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1 \documentclass[twocolumn]{svjour3} |
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2 \usepackage{listings} |
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3 \usepackage[pdftex]{graphicx} |
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4 \usepackage{environ} |
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5 \usepackage{amsmath} |
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6 \usepackage{amsfonts} |
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7 \usepackage[english]{babel} |
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8 \usepackage[utf8]{inputenc} |
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9 \usepackage{lmodern} |
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10 \usepackage[T1]{fontenc} |
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11 \usepackage{color} |
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12 |
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13 \input{graphdrawing} |
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15 \renewcommand*\descriptionlabel[1]{\hspace\labelsep\normalfont\bf #1} |
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16 |
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17 \newcommand{\Sa}{{\Large$^*$}} |
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18 \newcommand{\Sb}{{\Large$^\dag$}} |
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19 \newcommand{\Sc}{{\Large$^\S$}} |
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20 |
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22 \newcommand{\mynote}[2]{ | |
23 \textcolor{red}{\fbox{\bfseries\sffamily\scriptsize#1} | |
24 {\small\textsf{\emph{#2}}} | |
25 \fbox{\bfseries\sffamily\scriptsize }}} | |
26 | |
27 \newcommand\TODO[1]{\mynote{TODO}{#1}} | |
28 \newcommand\cw[1]{\mynote{CW}{#1}} | |
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29 \newcommand\ls[1]{\mynote{LS}{#1}} |
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30 \newcommand\nodename[1]{\texttt{#1}} |
2562 | 31 |
32 | |
33 | |
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34 \smartqed % flush right qed marks, e.g. at end of proof |
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35 |
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36 \journalname{Graal Compiler Design} |
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37 \def\makeheadbox{{% |
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38 \hbox to0pt{\vbox{\baselineskip=10dd\hrule\hbox |
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39 to\hsize{\vrule\kern3pt\vbox{\kern3pt |
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40 \hbox{\bfseries The Graal Compiler - Design and Strategy} |
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41 \kern3pt}\hfil\kern3pt\vrule}\hrule}% |
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42 \hss}}} |
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43 |
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44 \begin{document} |
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45 |
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46 \author{Thomas W\"{u}rthinger \Sa, Lukas Stadler \Sc, Gilles Duboscq \Sa} |
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47 \institute{\Sa Oracle, \Sc Johannes Kepler University, Linz} |
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48 |
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49 \date{Created: \today} |
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50 |
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51 \title{The Graal Compiler} |
2604 | 52 \subtitle{Design and Strategy \\ \textcolor{red}{work in progress (Oracle internal)}} |
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53 |
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54 \maketitle |
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55 |
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56 \abstract{ |
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57 The Graal compiler (simply referred to as \emph{the compiler} in the rest of this document) aims at improving C1X, the Java port of the HotSpot client compiler, both in terms of modularity and peak performance. |
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58 The compiler should work with the Maxine VM and the HotSpot VM. |
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59 This document contains information about the proposed design and strategy for developing the compiler.} |
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60 |
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61 \section{Context} |
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62 |
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63 In 2009, the Maxine team started with creating C1X, a Java port of the HotSpot client compiler, and integrated it into the Maxine VM. |
2604 | 64 Part of this effort was the development of a clear and clean compiler-runtime interface that allows the separation of the compiler and the VM. |
65 This compiler-runtime interface enables the use of one compiler for multiple VMs. | |
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66 In June 2010, we started integrating C1X into the HotSpot VM and we called the resulting system Graal~VM. |
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67 Currently, the Graal~VM is fully functional and runs benchmarks (SciMark, DaCapo) at a similar speed as the HotSpot client compiler. |
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68 |
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69 \section{Goals} |
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70 The compiler effort aims at rewriting the high-level intermediate representation of C1X with two main goals: |
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71 \begin{description} |
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72 \item[Modularity:] A modular design of the compiler should simplify the implementation of new languages, new back-ends, and new optimizations. |
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73 \item[Peak Performance:] A more powerful intermediate representation should enable the implementation of aggressive optimizations that impact the peak performance of the resulting machine code. |
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74 \end{description} |
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75 |
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76 \section{Design} |
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77 For the implementation of the compiler, we rely on the following design decisions: |
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78 \begin{description} |
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79 \item[Graph Representation:] |
2562 | 80 The compiler's intermediate representation is modeled as a graph with nodes that are connected with directed edges. |
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81 There is only a single node base class and every node has an associated graph object that does not change during the node's lifetime. |
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82 Every node is serializable and has an id that is unique within its graph. |
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83 Every edge is classified as either a control flow edge (anti-dependency) or a data flow edge (dependency) and represented as a simple pointer from the source node to the target node. |
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84 It is possible to replace a node with another node without traversing the full graph. |
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85 The graph does not allow data flow edge cycles or control flow edge cycles. |
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86 We achieve this by explicitely modelling loops (see Section~\ref{sec:loops}). |
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87 \item[Extensibility:] |
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88 The compiler is extensible by allowing developers to add new compiler phases and new node subclasses without modifying the compiler's sources. |
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89 A node has an abstract way of expressing its semantics and new compiler phases can ask compiler nodes for their properties and capabilities. |
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90 We use the ``everything is an extension'' concept. |
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91 Even standard compiler optimizations are internally modeled as extensions, to show that the extension mechanism exposes all necessary functionality. |
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92 \item[Detailing:] |
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93 The compilation starts with a graph that contains nodes that represent the operations of the source language (e.g., one node for an array store to an object array). |
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94 During the compilation, the nodes are replaced with more detailed nodes (e.g., the array store node is split into a null check, a bounds check, a store check, and a memory access). |
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95 Compiler phases can choose whether they want to work on the earlier versions of the graph (e.g., escape analysis) or on later versions (e.g., null check elimination). |
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96 \item[Generality:] |
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97 The compiler does not require Java as its input. |
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98 This is achieved by having a graph as the starting point of the compilation and not a Java bytecodes array. |
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99 Building the graph from the Java bytecodes must happen before giving a method to the compiler. |
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100 This enables front-ends for different languages (e.g., Ruby or JavaScript) to provide their own graph. |
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101 Also, there is no dependency on a specific back-end, but the output of the compiler is a graph that can then be converted to a different representation in a final compiler phase. |
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102 \end{description} |
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103 |
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104 \section{Milestones} |
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105 \label{sec:mile} |
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106 The compiler is developed starting from the current C1X source code base. |
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107 This helps us testing the compiler at every intermediate development step on a variety of Java benchmarks. |
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108 We define the following development milestones and when they are considered to be achieved (see Section~\ref{sec:conclusions} for planned dates): |
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109 \begin{description} |
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110 \item[M1:] We have a fully working Graal~VM version with a stripped down C1X compiler that does not perform any optimizations. |
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111 \item[M2:] We modified the high-level intermediate representation to be based on the compiler graph data structure. |
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112 \item[M3:] We have reimplemented and reenabled compiler optimizations in the compiler that previously existed in C1X. |
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113 \item[M4:] We have reintegrated the new compiler into the Maxine VM and can use it as a Maxine VM bootstrapping compiler. |
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114 \end{description} |
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115 |
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116 After those four milestones, we see three different possible further development directions that can be followed in parallel: |
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117 \begin{itemize} |
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118 \item Removal of the XIR template mechanism and replacement with a snippet mechanism that works with the compiler graph. |
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119 \item Improvements for peak performance (loop optimizations, escape analysis, bounds check elimination, processing additional interpreter runtime feedback). |
2604 | 120 \item Implementation of a prototype front-end for a different language, e.g., JavaScript. |
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121 \end{itemize} |
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122 |
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123 \section{Project Source Structure} |
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124 In order to support the goal of a modular compiler, the code will be divided into the following source code projects (as subprojects of \textbf{com.oracle.max.graal}). |
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125 |
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126 \begin{description} |
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127 \item[graph] contains the abstract node implementation, the graph implementation and all the associated tools and auxiliary classes. |
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128 \item[nodes] contains the implementation of known basic nodes (e.g., phi nodes, control flow nodes, \ldots). |
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129 Additional node classes should go into separate projects and be specializations of the known basic nodes. |
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130 \item[java] contains code for building graphs from Java bytecodes and Java-specific nodes. |
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131 \item[opt] contains optimizations such as global value numbering or conditional constant propagation. |
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132 \item[compiler] contains the compiler, including: |
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133 \begin{itemize} |
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134 \item Scheduling of the compilation phases. |
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135 \item Implementation of the \emph{compiler interface} (CI). |
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136 \item Implementation of the final compilation phase that produces the low-level representation. |
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137 \item Machine code creation, including debug info. |
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138 \end{itemize} |
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139 \end{description} |
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140 |
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141 |
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142 \section{Graph} |
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143 |
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144 The \emph{intermediate representation}~(IR) of the compiler is designed as a directed graph. |
2604 | 145 The graph deals out ids for new nodes and can be queried for the node corresponding to a given id as well as for an unordered list of nodes of the graph. |
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146 Graphs can manage side data structures, which will be automatically invalidated and lazily recomputed whenever the graph changes. Examples for side data structures are dominator trees and temporary schedules. These side data structures will usually be understood by more than one optimization. |
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147 |
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148 The nodes of the graph have the following properties: |
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149 \begin{itemize} |
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150 \item Each node is always associated with a single graph and this association is immutable. |
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151 \item Each node has an immutable id that is unique within its associated graph. |
2604 | 152 \item Nodes can have a data dependency, which means that one node requires the result of another node as its input. The fact that the result of the first node needs to be computed before the second node can be executed introduces a partial order to the set of nodes. |
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153 \item Nodes can have a control flow dependency, which means that the execution of one node will be followed by the execution of another node. This includes conditional execution, memory access serialization and other reasons, and again introduces a partial order to the set of nodes. |
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154 \item Nodes can only have data and control dependencies to nodes which belong to the same graph. |
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155 \item Control dependencies and data dependencies each represent a \emph{directed acyclic graph} (DAG) on the same set of nodes. This means that data dependencies always point upwards, and control dependencies always point downwards in a drawing of the graph. Situations that normally incur cycles (like loops) are represented by special nodes (see Section~\ref{sec:loops}). |
2619 | 156 \item Ordering between nodes is specified only to the extent which is required to correctly express the semantics of a given program. This gives the compiler flexibility for the possible scheduling of a node and therefore wiggle room for optimizations. For algorithms that require a fixed ordering of nodes, a temporary schedule can always be generated. |
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157 \item Both data and control dependencies can be traversed in both directions, so that each node can be traversed in four directions (see Figure~\ref{fig:directions}): |
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158 \begin{itemize} |
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159 \item \emph{inputs} are all nodes that this node has data dependencies on. |
2604 | 160 \item \emph{usages} are all nodes whose inputs contain this node. |
161 \item \emph{successors} are all nodes that have to be after this node in control flow. | |
162 \item \emph{predecessors} are all nodes whose successors contain this node. | |
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163 \end{itemize} |
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164 \item Only inputs and successors can be changed, and changes to them will update the usages and predecessors. |
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165 \item Every node must be able to support cloning and serialization. |
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166 \item Inlining should always be performed as embedding one graph into another graph. |
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167 \item Nodes cannot be reassigned to another graph, they are cloned instead. |
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168 \item The edges of a node also define \textit{happens-before} and \textit{happens-after} relationships as shown in Figure~\ref{fig:directions}. |
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169 \end{itemize} |
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170 |
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171 \begin{figure}[h] |
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172 \centering |
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173 \begin{digraphenv}{scale=0.5}{graphdirections} |
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174 \node{node1}{Node} |
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175 \textnode{inputs}{inputs} |
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176 \textnode{usages}{usages} |
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177 \textnode{successors}{successors} |
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178 \textnode{predecessors}{predecessors} |
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179 \data{node1}{inputs} |
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180 \control{node1}{successors} |
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181 \data{usages}{node1} |
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182 \control{predecessors}{node1} |
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183 \node{node2}{Node} |
2604 | 184 \textnode{before}{happens-before} |
185 \textnode{after}{happens-after} | |
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186 \data{node2}{before} |
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187 \control{node2}{after} |
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188 \data{after}{node2} |
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189 \control{before}{node2} |
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190 \end{digraphenv} |
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191 \caption{A node and its edges.} |
2604 | 192 \label{fig:directions} |
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193 \end{figure} |
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194 |
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195 \section{Control Flow} |
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196 |
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197 Control flow is managed in way where the predecessor node contains direct pointers to its successor nodes. |
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198 We reserve the term \textit{instruction} for nodes that are embedded in the control flow. |
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199 This is opposite to the approach taken in the server compiler, where control flow and data flow edges point in the same direction. |
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200 The advantage that we see in our approach is that there is no need for projection nodes in case of control flow splits. |
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201 An \texttt{If} instruction can directly point to its true and false successors without any intermediate nodes. |
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202 This makes the graph more compact and simplifies graph traversal. |
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203 |
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204 Listing~\ref{lst:cfg2} shows an example Java program with an if statement where both paths do not contain any instruction with side effects. |
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205 The \texttt{If} instruction can directly point its true and false successors to a \texttt{Merge} instruction. |
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206 A \texttt{Phi} node that selects the appropriate value is appended to the \texttt{Merge} instruction. |
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207 The \texttt{Return} instruction then has a data dependency on the \texttt{Phi} node. |
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208 |
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209 \begin{lstlisting}[label=lst:cfg2, caption=Control flow in the graph., captionpos=b] |
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210 if (condition) { return 0; } |
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211 else { return 1; } |
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212 \end{lstlisting} |
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213 |
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214 \begin{figure}[h] |
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215 \centering |
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216 \begin{digraphenv}{scale=0.5}{cfg2} |
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217 \textnode{entry}{Entry} |
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218 \textnode{condition}{condition} |
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219 \textnode{const0}{0} |
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220 \textnode{const1}{1} |
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221 \nodesplit{if}{If} |
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222 \control{entry}{if} |
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223 \controllabel{if:succ1}{merge} |
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224 \controllabel{if:succ2}{merge} |
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225 \data{if}{condition} |
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226 \node{merge}{Merge} |
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227 \node{return}{Return} |
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228 \nodetri{phi}{Phi} |
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229 \datalabel{phi:in1}{merge} |
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230 \datalabel{phi:in2}{const0} |
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231 \datalabel{phi:in3}{const1} |
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232 \data{return}{phi} |
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233 \control{merge}{return} |
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234 \end{digraphenv} |
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235 \caption{A simple loop with two exits.} |
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236 \label{fig:exc1} |
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237 \end{figure} |
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238 |
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239 \section{Exceptions} |
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240 \label{sec:Exceptions} |
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241 |
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242 We do not throw runtime exceptions (e.g., \texttt{IndexOutOf\-BoundsException}, \texttt{NullPointerException}, or \texttt{Out\-Of\-MemoryException}), but deoptimize instead. |
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243 This reduces the places in the compiled code where an exact bytecode location and debug information must be known. |
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244 Additionally, this greatly reduces the number of exception handler edges in the compiled code. |
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245 The main advantage of this technique is however, that we are free in moving around bounds checks, memory allocation, memory accesses with implicit null checks, etc. |
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246 |
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247 There are only two kinds of instruction that need explicit exception edges, because they are the only instructions that can throw exceptions in compiled code: \texttt{Throw} instructions and \texttt{Invoke} instructions. |
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248 They are modelled as instructions with an additional control flow continuation that points to an \texttt{ExceptionDispatch} instruction. |
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249 The exception dispatch instruction decides based on the type of the exception object whether the control should flow to the catch handler or to another exception dispatch. |
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250 If there is no catch handler in the currently compiled method, then the control flows into the \texttt{Unwind} instruction that handles the exception by forwarding it to the caller. |
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251 Listing~\ref{lst:exc1} shows an example Java program with nested try blocks and Figure \ref{fig:exc1} shows the corresponding compiler graph. |
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252 |
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253 \begin{lstlisting}[label=lst:exc1, caption=Exception dispatch in the compiler graph., captionpos=b] |
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254 try { m1(); |
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255 try { m2(); |
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256 } catch(ExtendedException e) { ... } |
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257 m3(); |
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258 throw exception; |
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259 } catch(Exception e) { ... } |
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260 \end{lstlisting} |
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261 |
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262 \begin{figure}[h] |
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263 \centering |
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264 \begin{digraphenv}{scale=0.5}{exc1} |
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265 \textnode{entry}{Entry} |
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266 \textnode{catch1}{catch1} |
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267 \textnode{catch2}{catch2} |
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268 \nodesplit{m1}{Invoke m1} |
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269 \nodesplit{m2}{Invoke m2} |
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270 \nodesplit{m3}{Invoke m3} |
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271 \nodesplit{dispatch1}{ExceptionDispatch} |
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272 \nodesplit{dispatch2}{ExceptionDispatch} |
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273 \node{throw}{Throw} |
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274 \node{unwind}{Unwind} |
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275 \control{entry}{m1} |
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276 \controllabel{m1:succ1}{m2} |
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277 \controllabel{m1:succ2}{dispatch2} |
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278 \controllabel{m2:succ1}{m3} |
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279 \controllabel{m2:succ2}{dispatch1} |
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280 \controllabel{m3:succ1}{throw} |
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281 \controllabel{m3:succ2}{dispatch2} |
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282 \control{throw}{dispatch2} |
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283 \controllabel{dispatch1:succ2}{catch1} |
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284 \controllabel{dispatch1:succ1}{dispatch2} |
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285 \controllabel{dispatch2:succ2}{catch2} |
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286 \controllabel{dispatch2:succ1}{unwind} |
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287 \end{digraphenv} |
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288 \caption{A simple loop with two exits.} |
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289 \label{fig:exc1} |
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290 \end{figure} |
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291 |
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292 \section{Loops} |
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293 \label{sec:loops} |
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294 Loops form a first-class construct in the IR that is expressed by specialized IR nodes during all optimization phases. |
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295 We only compile methods with a control flow where every loop has a single entry point. |
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296 This entry point is a \nodename{LoopBegin} instruction. |
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297 This instruction is connected to a \nodename{LoopEnd} instruction that merges all control flow paths that do not exit the loop. |
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298 The edge between the \nodename{LoopBegin} and the \nodename{LoopEnd} is the backedge of the loop. |
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299 It goes from the beginning to the end in order to make the graph acyclic. |
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300 An algorithm that traverses the control flow has to explicitely decide whether it wants to incorporate backedges (i.e., special case of the treatment of \nodename{LoopEnd}) or ignore them. |
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301 Figure \ref{fig:loop1} shows a simple example with a loop with a single entry and two exits. |
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302 |
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303 \begin{figure}[h] |
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304 \centering |
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305 \begin{digraphenv}{scale=0.5}{layout1} |
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306 \textnode{BeforeLoop}{Loop entry} |
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307 \textnode{Exit1}{First loop exit} |
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308 \textnode{Exit2}{Second loop exit} |
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309 \nodesplit{LoopBegin}{LoopBegin} |
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310 \node{LoopEnd}{LoopEnd} |
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311 \nodesplit{If1}{If} |
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312 \nodesplit{If2}{If} |
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313 \controllabel{LoopBegin:succ1}{LoopEnd} |
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314 \controllabel{LoopBegin:succ2}{If1} |
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315 \controllabel{If1:succ1}{If2} |
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316 \controllabel{If2:succ1}{LoopEnd} |
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317 \controllabel{BeforeLoop}{LoopBegin} |
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318 \controllabel{If1:succ2}{Exit1} |
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319 \controllabel{If2:succ2}{Exit2} |
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320 \end{digraphenv} |
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321 \caption{A simple loop with two exits.} |
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323 \end{figure} |
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324 |
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325 \subsection{Loop Phis} |
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326 Data flow in loops is modelled with special phi nodes at the beginning and the end of the loop. |
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327 The \nodename{LoopEnd} instruction merges every value that flows into the next loop iteration in associated \nodename{LoopEndPhi} nodes. |
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328 A corresponding \nodename{LoopBeginPhi} node that is associated with the loop header has a control flow dependency on the \nodename{LoopEndPhi} node. |
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329 Listing~\ref{lst:loop} shows a simple counting loop that is used as an example in the rest of this section. |
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330 Figure~\ref{fig:loop2} shows how the loop is modelled immediately after building the graph. |
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331 |
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332 \begin{lstlisting}[label=lst:loop, caption=Loop example that counts from 0 to n-1., captionpos=b] |
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333 for(int i=0; i<n; ++i) { } |
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334 \end{lstlisting} |
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335 |
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336 \begin{figure}[h] |
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337 \centering |
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338 \begin{digraphenv}{scale=0.5}{layout2} |
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339 \textnode{BeforeLoop}{Loop entry} |
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340 \textnode{Exit}{Loop exit} |
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341 \textnode{n}{n} |
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342 \textnode{Constant0}{0} |
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343 \textnode{Constant1}{1} |
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344 \nodesplit{LoopBegin}{LoopBegin} |
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345 \node{LoopEnd}{LoopEnd} |
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346 \nodesplit{If1}{If} |
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347 \controllabel{LoopBegin:succ1}{LoopEnd} |
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348 \controllabel{LoopBegin:succ2}{If1} |
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349 \nodebi{Compare}{<} |
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350 \nodebi{LoopBeginPhi}{LoopBeginPhi} |
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351 \nodebi{Add}{+} |
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352 \datalabel{Add:in1}{LoopBeginPhi} |
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353 \datalabel{Add:in2}{Constant1} |
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354 \nodebi{LoopEndPhi}{LoopEndPhi} |
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355 \control{LoopBeginPhi}{LoopEndPhi} |
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356 \data{LoopEndPhi:in1}{LoopEnd} |
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357 \data{LoopEndPhi:in2}{Add} |
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358 \datalabel{LoopBeginPhi:in1}{LoopBegin} |
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359 \datalabel{LoopBeginPhi:in2}{Constant0} |
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360 \datalabel{Compare:in1}{LoopBeginPhi} |
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361 \datalabel{Compare:in2}{n} |
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362 \data{If1}{Compare} |
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363 \controllabel{If1:succ1}{LoopEnd} |
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364 \controllabel{BeforeLoop}{LoopBegin} |
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365 \controllabel{If1:succ2}{Exit} |
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366 \end{digraphenv} |
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367 \caption{Graph for a loop counting from 0 to n-1.} |
2604 | 368 \label{fig:loop2} |
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369 \end{figure} |
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370 |
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371 \subsection{Loop Counters} |
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372 The compiler is capable of recognizing variables that are only increased within a loop. |
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373 A potential overflow of such a variable is prohibited with a guard before the loop (this is not necessary in this example, because the loop variable cannot overflow). |
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374 Figure \ref{fig:loop3} shows the compiler graph of the example loop after the loop counter transformation. |
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375 |
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376 |
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377 \begin{figure}[h] |
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378 \centering |
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379 \begin{digraphenv}{scale=0.5}{layout3} |
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380 \textnode{BeforeLoop}{Loop entry} |
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381 \textnode{Exit}{Loop exit} |
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382 \textnode{n}{n} |
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383 \textnode{Constant0}{0} |
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384 \textnode{Constant1}{1} |
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385 \nodesplit{LoopBegin}{LoopBegin} |
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386 \node{LoopEnd}{LoopEnd} |
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387 \nodesplit{If1}{If} |
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388 \controllabel{LoopBegin:succ1}{LoopEnd} |
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389 \controllabel{LoopBegin:succ2}{If1} |
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390 \nodebi{Compare}{<} |
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391 \nodetri{LoopCounter}{LoopCounter} |
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392 \datalabel{LoopCounter:in1}{LoopBegin} |
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393 \datalabeltext{LoopCounter:in2}{Constant0}{init} |
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394 \datalabeltext{LoopCounter:in3}{Constant1}{stride} |
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395 \datalabel{Compare:in1}{LoopCounter} |
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396 \datalabel{Compare:in2}{n} |
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397 \data{If1}{Compare} |
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398 \controllabel{If1:succ1}{LoopEnd} |
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399 \controllabel{BeforeLoop}{LoopBegin} |
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400 \controllabel{If1:succ2}{Exit} |
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401 \end{digraphenv} |
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402 \caption{Graph after loop counter transformation.} |
2604 | 403 \label{fig:loop3} |
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404 \end{figure} |
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405 |
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406 \subsection{Bounded Loops} |
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407 |
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408 If the total maximum number of iterations of a loop is fixed, then the loop is converted into a bounded loop. |
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409 The total number of iterations always denotes the number of full iterations of the loop with the control flowing from the loop begin to the loop end. |
2604 | 410 If the total number of iterations is reached, the loop is exited directly from the loop header. |
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411 In the example, we can infer from the loop exit with the comparison on the loop counter that the total number of iterations of the loop is limited to n. |
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412 Figure \ref{fig:loop4} shows the compiler graph of the example loop after the bounded loop transformation. |
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413 |
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414 \begin{figure}[h] |
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415 \centering |
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416 \begin{digraphenv}{scale=0.5}{layout4} |
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417 \textnode{BeforeLoop}{Loop entry} |
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418 \textnode{Exit}{Loop exit} |
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419 \textnode{n}{n} |
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420 \textnode{Constant0}{0} |
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421 \textnode{Constant1}{1} |
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422 \nodesplittri{LoopBegin}{BoundedLoopBegin} |
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423 \node{LoopEnd}{LoopEnd} |
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424 \controllabel{LoopBegin:succ1}{LoopEnd} |
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425 \controllabel{LoopBegin:succ2}{LoopEnd} |
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426 \controllabel{LoopBegin:succ3}{Exit} |
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427 \nodetri{LoopCounter}{LoopCounter} |
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428 \datalabel{LoopCounter:in1}{LoopBegin} |
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429 \datalabeltext{LoopCounter:in2}{Constant0}{init} |
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430 \datalabeltext{LoopCounter:in3}{Constant1}{stride} |
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431 \data{LoopBegin}{n} |
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432 \controllabel{BeforeLoop}{LoopBegin} |
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433 \end{digraphenv} |
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434 \caption{Graph after bounded loop transformation.} |
2604 | 435 \label{fig:loop4} |
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436 \end{figure} |
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437 |
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438 \subsection{Vectorization} |
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439 |
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440 If we have now a bounded loop with no additional loop exit and no associated phi nodes (only associated loop counters), we can vectorize the loop. |
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441 We replace the loop header with a normal instruction that produces a vector of values from 0 to the number of loop iterations minus 1. |
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442 The loop counters are replaced with \texttt{VectorAdd} and \texttt{VectorMul} nodes. |
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443 The vectorization is only possible if every node of the loop can be replaced with a corresponding vector node. |
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444 Figure \ref{fig:loop5} shows the compiler graph of the example loop after vectorization. |
2604 | 445 The vector nodes all work on an ordered list of integer values and are subject to canonicalization and global value numbering like any other node. |
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446 |
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447 |
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448 \begin{figure}[h] |
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449 \centering |
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450 \begin{digraphenv}{scale=0.5}{layout5} |
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451 \textnode{Entry}{Entry} |
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452 \textnode{Exit}{Exit} |
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453 \textnode{n}{n} |
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454 \textnode{Constant0}{0} |
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455 \textnode{Constant1}{1} |
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456 \node{Vector}{Vector} |
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457 \nodebi{VectorAdd}{VectorAdd} |
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458 \nodebi{VectorMul}{VectorMul} |
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459 \control{Entry}{Vector} |
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460 \control{Vector}{Exit} |
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461 \datalabel{VectorAdd:in1}{Vector} |
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462 \datalabel{VectorAdd:in2}{Constant0} |
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463 \datalabel{VectorMul:in1}{VectorAdd} |
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464 \datalabel{VectorMul:in2}{Constant1} |
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465 \data{Vector}{n} |
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466 \end{digraphenv} |
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467 \caption{Graph after vectorization.} |
2604 | 468 \label{fig:loop5} |
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469 \end{figure} |
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470 |
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471 |
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472 \section{Frame States} |
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473 A frame state captures the state of the program like it is seen in by an interpreter of the program. |
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474 The frame state contains the information that is local to the current activation and will therefore disappear during SSA-form constructions or other compiler optimizations. |
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475 For Java, the frame state is defined in terms of the Java bytecode specification (i.e., the values of the local variables, the operand stack, and the locked monitors). |
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476 However, a frame state is not a concept specific to Java (e.g., the Crankshaft JavaScript engine uses frame states in their optimizing compiler to model the values of the AST interpreter). |
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477 |
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478 Frame states are necessary to support the deoptimization of the program, which is the precondition for performing aggressive optimizations that use optimistic assumptions. |
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479 Therefore every point in the optimizing compiler that may revert execution back to the interpreter needs a valid frame state. |
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480 However, the point where the interpreter continues execution need not correspond exactly to the execution position of the compiled code, because many Java bytecode instructions can be safely reexecuted. |
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481 Thus, frame states need only be generated for the states after instructions that cannot be reexecuted, because they modify the state of the program. |
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482 Examples for such instructions are: |
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483 |
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484 \begin{itemize} |
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485 \item Array stores (in Java bytecodes {\tt IASTORE, LASTORE, FASTORE, \\DASTORE, AASTORE, BASTORE, CASTORE, SASTORE}) |
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486 \item Field stores (in Java bytecodes {\tt PUTSTATIC, PUTFIELD}) |
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487 \item Method calls (in Java bytecodes {\tt INVOKEVIRTUAL, INVOKESPECIAL, \\INVOKESTATIC, INVOKEINTERFACE}) |
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488 \item Synchronization (in Java bytecodes {\tt MONITORENTER, MONITOREXIT}) |
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489 \end{itemize} |
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490 |
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491 Within the graph a frame state is represented as a node that is attached to the instruction that caused it to be generated using a control dependency (see Figure~\ref{fig:fs1}). |
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492 Frame states also have data dependencies on the contents of the state: the local variables and the expression stack. |
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493 |
2604 | 494 The frame state at the method beginning does not have to be explicitely in the graph, because it can always be reconstructed at a later stage. |
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495 We save the frame state at control flow merges if there is at least one frame state on any control flow path between a node and its immediate dominator. |
2604 | 496 |
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497 |
2578 | 498 \begin{figure}[h] |
499 \centering | |
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500 \begin{digraphenv}{scale=0.5}{fs1} |
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501 \nodetrisplit{store1}{ArrayStore} |
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502 \nodebi{load1}{ArrayLoad} |
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503 \controllabel{store1:succ1}{load1} |
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504 \nodetrisplit{store2}{FieldStore} |
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505 \control{load1}{store2} |
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506 end [shape=plaintext, label="...", width="2.0"] |
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507 store2:succ1:s -> end:n [color=red]; |
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508 % |
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509 \nodeframestate{fs1}{FrameState} |
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510 \controllabel{store1:succ2}{fs1} |
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511 \nodeframestate{fs2}{FrameState} |
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512 \controllabel{store2:succ2}{fs2} |
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513 \end{digraphenv} |
2578 | 514 \caption{Simple example using two frame states.} |
2604 | 515 \label{fig:fs1} |
2578 | 516 \end{figure} |
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517 |
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518 |
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519 A deoptimization node needs a valid frame state that specifies the location and state where the interpreter should continue. |
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520 The algorithm for constructing frame states makes sure that every possible location in the graph has a well-defined frame state that can be used by a deoptimization instruction. |
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521 Therefore, there are no direct links between the deoptimization instruction and its frame state thus allowing the deoptimization instructions to move freely around. |
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522 |
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523 \subsection{Partial Escape Analysis} |
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524 |
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525 A partial escape analysis can help to further reduce the number of frame states. |
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526 A field or array store does not create a new frame state, when the object that is modified did not have a chance to escape between its creation and the store. |
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527 |
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528 Listing~\ref{lst:escape1} shows an example of a method that creates two \texttt{Point} objects, connects them, and returns them. |
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529 The object allocation of the first \texttt{Point} object does not need a frame state. |
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530 We can always reexecute the \texttt{NEW} bytecode again in the interpreter. |
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531 The \texttt{Point} object allocated by the compiler will then simply disappear after the next garbage collection. |
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532 The following field store is a thread-local memory store, because the \texttt{Point} object did not have any chance to escape. |
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533 Same applies to the assignment of the \texttt{next} field and the third field assignment. |
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534 Therefore, the whole method \texttt{getPoint} does not need an explicit frame state, because at any time during execution of this method, we can deoptimize and continue execution in the interpreter at the first bytecode of the method. |
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535 |
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536 \begin{lstlisting}[label=lst:escape1, caption=Example method that needs no frame state., captionpos=b] |
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537 void getPoint() { |
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538 Point p = new Point(); |
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539 p.x = 1; |
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540 p.next = new Point(); |
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541 p.next.x = 2; |
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542 return p; |
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543 } |
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544 \end{lstlisting} |
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545 |
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546 The reduction of frame states makes it easier for the compiler to perform memory optimizations like memory access coalescing. |
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547 We believe that this reduction on frame states is the key to effective vectorization and other compiler optimizations where compilers of compilers of unmanaged languages have advantages. |
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548 |
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549 \subsection{Guards} |
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550 A guard is a node that deoptimizes based on a conditional expression. |
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551 Guards are not attached to a certain frame state, they can move around freely and will always use the correct frame state when the nodes are scheduled (i.e., the last emitted frame state). |
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552 The node that is guarded by the deoptimization has a data dependency on the guard and the guard in turn has a data dependency on the condition. |
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553 A guard must not be moved above any \texttt{If} nodes. |
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554 Therefore, we use \texttt{Anchor} instructions after a control flow split and a data dependency from the guard to this anchor. |
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555 The anchor is the most distant instruction that is postdominated by the guarded instruction and the guard can be scheduled anywhere between those two nodes. |
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556 This ensures maximum flexibility for the guard instruction and guarantees that we only deoptimize if the control flow would have reached the guarded instruction (without taking exceptions into account). |
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557 |
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558 To illustrate the strengths of this approach, we show the graph for the Java code snippet shown in \ref{lst:guard1}. |
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559 The example looks artificial, but in case of method inlining, this is a pattern that is not unlikely to be present in a normal Java program. |
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560 Figure \ref{fig:guard0} shows the compiler graph for the example method after graph building. |
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561 The field stores are both represented by a single instruction and the null check that is implicitely incorporated in the field store. |
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562 |
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563 \begin{lstlisting}[label=lst:guard1, caption=Example method that demonstrates the strengths of modelling the guards explicitely., captionpos=b] |
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564 void init(Point p) { |
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565 if (p != null) { |
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566 p.x = 0; |
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567 } |
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568 p.y = 0; |
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569 } |
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570 \end{lstlisting} |
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571 |
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572 \begin{figure}[h] |
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573 \centering |
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574 \begin{digraphenv}{scale=0.5}{guard0} |
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575 \textnode{entry}{Entry} |
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576 \nodesplit{if}{If} |
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577 \node{merge}{Merge} |
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578 \node{return}{Return} |
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579 \node{cmpnull}{NonNull} |
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580 \textnode{p}{p} |
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581 \textnode{const0}{0} |
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582 \nodebisplit{store1}{FieldStore x} |
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583 \nodebisplit{store2}{FieldStore y} |
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584 \nodeframestate{fs1}{FrameState} |
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585 \nodeframestate{fs2}{FrameState} |
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586 \datalabel{store1:in1}{p} |
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587 \datalabel{store2:in1}{p} |
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588 \datalabel{store1:in2}{const0} |
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589 \datalabel{store2:in2}{const0} |
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590 \control{entry}{if} |
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591 \data{if}{cmpnull} |
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592 \controllabel{if:succ1}{merge} |
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593 \controllabel{if:succ2}{store1} |
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594 \controllabel{store1:succ1}{merge} |
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595 \controllabel{store1:succ2}{fs1} |
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596 \control{merge}{store2} |
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597 \controllabel{store2:succ1}{return} |
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598 \controllabel{store2:succ2}{fs2} |
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599 \data{cmpnull}{p} |
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600 \end{digraphenv} |
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601 \caption{Initial graph with the two field stores.} |
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602 \label{fig:guard0} |
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603 \end{figure} |
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604 |
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605 Figure~\ref{fig:guard1} shows the example graph at a later compilation phase when the field store instructions are lowered to memory store instructions and explicitely modelled null check guards. |
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606 The guards are attached to anchor instructions that delimit their possible schedule. |
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607 The first guard must not be moved outside the \texttt{if} block; the second guard may be moved before the \texttt{If} instruction, because at this point it is already guaranteed that the second store is executed. |
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608 |
2578 | 609 \begin{figure}[h] |
610 \centering | |
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611 \begin{digraphenv}{scale=0.5}{guard1} |
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612 \textnode{entry}{Entry} |
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613 \node{anchor1}{Anchor} |
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614 \node{anchor2}{Anchor} |
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615 \nodesplit{if}{If} |
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616 \node{merge}{Merge} |
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617 \node{return}{Return} |
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618 \node{cmpnull}{NonNull} |
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619 \textnode{p}{p} |
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620 \textnode{const0}{0} |
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621 \nodeguard{guard1}{Guard} |
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622 \nodeguard{guard2}{Guard} |
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623 \nodetrisplit{store1}{MemStore 16 (int)} |
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624 \nodetrisplit{store2}{MemStore 20 (int)} |
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625 \nodeframestate{fs1}{FrameState} |
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626 \nodeframestate{fs2}{FrameState} |
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627 \data{store1:in1}{p} |
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628 \data{store2:in1}{p} |
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629 \data{store1:in2}{const0} |
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630 \data{store2:in2}{const0} |
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631 \data{store1:in3}{guard1} |
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632 \data{store2:in3}{guard2} |
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633 \data{guard1:in1}{anchor2} |
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634 \data{guard2:in1}{anchor1} |
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635 \data{guard1:in2}{cmpnull} |
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636 \data{guard2:in2}{cmpnull} |
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637 \control{entry}{anchor1} |
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638 \control{anchor1}{if} |
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639 \data{if}{cmpnull} |
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640 \controllabel{if:succ1}{merge} |
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641 \controllabel{if:succ2}{anchor2} |
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642 \control{anchor2}{store1} |
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643 \controllabel{store1:succ1}{merge} |
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644 \controllabel{store1:succ2}{fs1} |
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645 \control{merge}{store2} |
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646 \controllabel{store2:succ1}{return} |
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647 \controllabel{store2:succ2}{fs2} |
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648 \data{cmpnull}{p} |
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649 \end{digraphenv} |
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650 \caption{A load guarded by a null check guard.} |
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651 \label{fig:guard1} |
2578 | 652 \end{figure} |
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653 |
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654 The first guard can be easily removed, because it is guarded by an \texttt{If} instruction that checks the same condition. |
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655 Therefore we can remove the guard and the anchor from the graph and this gives us the graph shown in Figure \ref{fig:guard2}. |
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656 |
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657 There is another optimization for guard instructions: If two guards that are anchored to the true and false branch of the same \texttt{If} instruction have the same condition, they can be merged, so that the resulting guard is anchored at the most distant node of which the \texttt{If} instruction is a postdominator. |
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658 |
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659 |
2578 | 660 \begin{figure}[h] |
661 \centering | |
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662 \begin{digraphenv}{scale=0.5}{guard2} |
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663 \textnode{entry}{Entry} |
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664 \node{anchor1}{Anchor} |
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665 \nodesplit{if}{If} |
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666 \node{merge}{Merge} |
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667 \node{return}{Return} |
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668 \node{cmpnull}{NonNull} |
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669 \textnode{p}{p} |
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670 \textnode{const0}{0} |
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671 \nodeguard{guard2}{Guard} |
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672 \nodetrisplit{store1}{MemStore 16 (int)} |
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673 \nodetrisplit{store2}{MemStore 20 (int)} |
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674 \nodeframestate{fs1}{FrameState} |
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675 \nodeframestate{fs2}{FrameState} |
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676 \data{store1:in1}{p} |
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677 \data{store2:in1}{p} |
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678 \data{store1:in2}{const0} |
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679 \data{store2:in2}{const0} |
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680 \data{store2:in3}{guard2} |
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681 \data{guard2:in1}{anchor1} |
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|
682 \data{guard2:in2}{cmpnull} |
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|
683 \control{entry}{anchor1} |
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684 \control{anchor1}{if} |
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685 \data{if}{cmpnull} |
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686 \controllabel{if:succ1}{merge} |
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687 \controllabel{if:succ2}{store1} |
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688 \controllabel{store1:succ1}{merge} |
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689 \controllabel{store1:succ2}{fs1} |
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690 \control{merge}{store2} |
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691 \controllabel{store2:succ1}{return} |
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692 \controllabel{store2:succ2}{fs2} |
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|
693 \data{cmpnull}{p} |
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|
694 \end{digraphenv} |
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695 \caption{After removing redundant guards.} |
2618
15774da89658
Incorporated comments from Peter. Renamings trap=>guard and guard/split=>anchor.
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|
696 \label{fig:guard2} |
2578 | 697 \end{figure} |
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698 |
2682
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699 The remaining guard can now be moved above the \texttt{If} condition and be used to eliminate the need for the \texttt{If} node. |
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700 From this point on, the guard can however no longer be moved below the first memory store. |
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|
701 We use a control dependency from the guard to the field store to express this condition. |
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702 The link between the second store and the guard and the control flow merge instruction is no longer necessary. |
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|
703 |
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|
704 \begin{figure}[h] |
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|
705 \centering |
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|
706 \begin{digraphenv}{scale=0.5}{guard3} |
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|
707 \textnode{entry}{Entry} |
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|
708 \node{anchor1}{Anchor} |
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|
709 \node{return}{Return} |
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|
710 \node{cmpnull}{NonNull} |
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|
711 \textnode{p}{p} |
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712 \textnode{const0}{0} |
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|
713 \nodeguard{guard2}{Guard} |
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|
714 \nodetrisplit{store1}{MemStore 16 (int)} |
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|
715 \nodetrisplit{store2}{MemStore 20 (int)} |
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|
716 \nodeframestate{fs1}{FrameState} |
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|
717 \nodeframestate{fs2}{FrameState} |
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|
718 \data{store1:in1}{p} |
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|
719 \data{store2:in1}{p} |
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|
720 \data{store1:in2}{const0} |
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|
721 \data{store2:in2}{const0} |
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|
722 \data{store2:in3}{guard2} |
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|
723 \data{guard2:in1}{anchor1} |
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|
724 \data{guard2:in2}{cmpnull} |
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|
725 \control{guard2}{store1} |
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|
726 \control{entry}{anchor1} |
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|
727 \control{anchor1}{store1} |
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|
728 \controllabel{store1:succ2}{fs1} |
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|
729 \control{store1}{store2} |
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|
730 \controllabel{store2:succ1}{return} |
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|
731 \controllabel{store2:succ2}{fs2} |
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|
732 \data{cmpnull}{p} |
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|
733 \end{digraphenv} |
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|
734 \caption{After eliminating an if with a guard.} |
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|
735 \label{fig:guard3} |
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|
736 \end{figure} |
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|
737 |
2679
07aa0a31fffb
Rewrote frame state to be not-so-Java-specific. Clarified and reduced the usage of the term "node".
Thomas Wuerthinger <thomas@wuerthinger.net>
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|
738 At some point during the compilation, guards need to be fixed, which means that appropriate data and control dependencies will be inserted so that they cannot move outside the scope of the associated frame state. |
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|
739 This will generate deoptimization-free zones that can be targeted by the most aggressive optimizations. |
2682
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|
740 A simple algorithm for this removal of frame states would be to move all guards as far upwards as possible and then the guards are fixed using anchor nodes. |
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|
741 In our example, the guard is already fixed, so there is no deoptimization point that uses any of the memory store frame states. |
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New field store / guard / frame state example.
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|
742 Therefore we can delete the frame states from the graph (see Figure \ref{fig:guard4}). |
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|
743 |
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|
744 \begin{figure}[h] |
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|
745 \centering |
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New field store / guard / frame state example.
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|
746 \begin{digraphenv}{scale=0.5}{guard4} |
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|
747 \textnode{entry}{Entry} |
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|
748 \node{anchor1}{Anchor} |
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|
749 \node{return}{Return} |
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|
750 \node{cmpnull}{NonNull} |
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|
751 \textnode{p}{p} |
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|
752 \textnode{const0}{0} |
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|
753 \nodeguard{guard2}{Guard} |
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|
754 \nodetrisplit{store1}{MemStore 16 (int)} |
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|
755 \nodetrisplit{store2}{MemStore 20 (int)} |
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|
756 \data{store1:in1}{p} |
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|
757 \data{store2:in1}{p} |
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|
758 \data{store1:in2}{const0} |
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|
759 \data{store2:in2}{const0} |
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|
760 \data{store2:in3}{guard2} |
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|
761 \data{guard2:in1}{anchor1} |
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|
762 \data{guard2:in2}{cmpnull} |
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|
763 \control{guard2}{store1} |
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|
764 \control{entry}{anchor1} |
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|
765 \control{anchor1}{store1} |
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|
766 \control{store1}{store2} |
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|
767 \controllabel{store2:succ1}{return} |
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|
768 \data{cmpnull}{p} |
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|
769 \end{digraphenv} |
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|
770 \caption{After removing the frame states.} |
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|
771 \label{fig:guard4} |
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|
772 \end{figure} |
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changeset
|
773 |
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changeset
|
774 Now we can use memory coalescing to combine the two stores without frame state to adjacent locations in the same object. |
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|
775 This is only possible if the first store does not have a frame state. |
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|
776 Figure \ref{fig:guard5} shows the resulting graph. |
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|
777 |
2577
ac2029d0898f
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|
778 |
2578 | 779 \begin{figure}[h] |
780 \centering | |
2682
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|
781 \begin{digraphenv}{scale=0.5}{guard5} |
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|
782 \textnode{entry}{Entry} |
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|
783 \node{anchor1}{Anchor} |
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784 \node{return}{Return} |
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785 \node{cmpnull}{NonNull} |
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786 \textnode{p}{p} |
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787 \textnode{const0}{0} |
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788 \nodeguard{guard2}{Guard} |
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789 \nodetrisplit{store1}{MemStore 16 (long)} |
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790 \data{store1:in1}{p} |
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791 \data{store1:in2}{const0} |
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792 \data{guard2:in1}{anchor1} |
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793 \data{guard2:in2}{cmpnull} |
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794 \control{guard2}{store1} |
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795 \control{entry}{anchor1} |
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796 \control{anchor1}{store1} |
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797 \controllabel{store1:succ1}{return} |
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798 \data{cmpnull}{p} |
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799 \end{digraphenv} |
2682
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800 \caption{After coalescing the two memory stores.} |
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801 \label{fig:guard5} |
2578 | 802 \end{figure} |
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803 |
2682
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804 A memory store that immediately follows a null check guard instruction on the same object, can be combined into a store with an implicit null check (that deoptimizes instead of throwing the exception). |
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805 Therefore, we can remove the guard again and also the anchor is no longer necessary. |
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806 Figure~\ref{fig:guard6} shows now that fully optimized graph that is generated for Listing~\ref{lst:guard1}. |
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807 |
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808 \begin{figure}[h] |
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809 \centering |
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810 \begin{digraphenv}{scale=0.5}{guard6} |
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811 \textnode{entry}{Entry} |
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812 \node{return}{Return} |
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813 \textnode{p}{p} |
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814 \textnode{const0}{0} |
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815 \nodetrisplit{store1}{DeoptimizingMemStore 16 (long)} |
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816 \data{store1:in1}{p} |
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817 \data{store1:in2}{const0} |
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818 \control{entry}{store1} |
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819 \controllabel{store1:succ1}{return} |
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820 \end{digraphenv} |
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821 \caption{Fully optimized method.} |
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822 \label{fig:guard6} |
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823 \end{figure} |
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824 |
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825 |
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826 \section{Conclusions} |
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827 \label{sec:conclusions} |
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828 This document sketched the strategy for the Graph compiler. |
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829 We already reached M1 (as defined in Section~\ref{sec:mile}) and have the following plans for M2 to M4: |
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830 \begin{description} |
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831 \item[M2:] June 30th, 2011 |
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832 \item[M3:] August 15th, 2011 |
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833 \item[M4:] September 30th, 2011 |
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834 \end{description} |
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835 After we reached M4, we want to create a new project road map that further improves the Graal compiler with respect to its two main goals: Modularity and peak performance. |
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836 |
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837 \end{document} |