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1154 lines
36 KiB
HTML
1154 lines
36 KiB
HTML
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN"
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"http://www.w3.org/TR/html4/strict.dtd">
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<html>
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<head>
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<title>Kaleidoscope: Adding JIT and Optimizer Support</title>
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<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
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<meta name="author" content="Chris Lattner">
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<link rel="stylesheet" href="../llvm.css" type="text/css">
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</head>
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<body>
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<h1>Kaleidoscope: Adding JIT and Optimizer Support</h1>
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<ul>
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<li><a href="index.html">Up to Tutorial Index</a></li>
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<li>Chapter 4
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<ol>
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<li><a href="#intro">Chapter 4 Introduction</a></li>
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<li><a href="#trivialconstfold">Trivial Constant Folding</a></li>
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<li><a href="#optimizerpasses">LLVM Optimization Passes</a></li>
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<li><a href="#jit">Adding a JIT Compiler</a></li>
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<li><a href="#code">Full Code Listing</a></li>
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</ol>
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</li>
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<li><a href="LangImpl5.html">Chapter 5</a>: Extending the Language: Control
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Flow</li>
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</ul>
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<div class="doc_author">
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<p>Written by <a href="mailto:sabre@nondot.org">Chris Lattner</a></p>
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</div>
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<!-- *********************************************************************** -->
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<h2><a name="intro">Chapter 4 Introduction</a></h2>
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<!-- *********************************************************************** -->
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<div>
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<p>Welcome to Chapter 4 of the "<a href="index.html">Implementing a language
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with LLVM</a>" tutorial. Chapters 1-3 described the implementation of a simple
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language and added support for generating LLVM IR. This chapter describes
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two new techniques: adding optimizer support to your language, and adding JIT
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compiler support. These additions will demonstrate how to get nice, efficient code
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for the Kaleidoscope language.</p>
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</div>
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<!-- *********************************************************************** -->
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<h2><a name="trivialconstfold">Trivial Constant Folding</a></h2>
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<!-- *********************************************************************** -->
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<div>
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<p>
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Our demonstration for Chapter 3 is elegant and easy to extend. Unfortunately,
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it does not produce wonderful code. The IRBuilder, however, does give us
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obvious optimizations when compiling simple code:</p>
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<div class="doc_code">
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<pre>
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ready> <b>def test(x) 1+2+x;</b>
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Read function definition:
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define double @test(double %x) {
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entry:
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%addtmp = fadd double 3.000000e+00, %x
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ret double %addtmp
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}
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</pre>
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</div>
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<p>This code is not a literal transcription of the AST built by parsing the
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input. That would be:
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<div class="doc_code">
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<pre>
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ready> <b>def test(x) 1+2+x;</b>
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Read function definition:
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define double @test(double %x) {
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entry:
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%addtmp = fadd double 2.000000e+00, 1.000000e+00
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%addtmp1 = fadd double %addtmp, %x
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ret double %addtmp1
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}
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</pre>
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</div>
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<p>Constant folding, as seen above, in particular, is a very common and very
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important optimization: so much so that many language implementors implement
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constant folding support in their AST representation.</p>
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<p>With LLVM, you don't need this support in the AST. Since all calls to build
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LLVM IR go through the LLVM IR builder, the builder itself checked to see if
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there was a constant folding opportunity when you call it. If so, it just does
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the constant fold and return the constant instead of creating an instruction.
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<p>Well, that was easy :). In practice, we recommend always using
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<tt>IRBuilder</tt> when generating code like this. It has no
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"syntactic overhead" for its use (you don't have to uglify your compiler with
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constant checks everywhere) and it can dramatically reduce the amount of
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LLVM IR that is generated in some cases (particular for languages with a macro
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preprocessor or that use a lot of constants).</p>
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<p>On the other hand, the <tt>IRBuilder</tt> is limited by the fact
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that it does all of its analysis inline with the code as it is built. If you
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take a slightly more complex example:</p>
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<div class="doc_code">
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<pre>
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ready> <b>def test(x) (1+2+x)*(x+(1+2));</b>
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ready> Read function definition:
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define double @test(double %x) {
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entry:
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%addtmp = fadd double 3.000000e+00, %x
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%addtmp1 = fadd double %x, 3.000000e+00
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%multmp = fmul double %addtmp, %addtmp1
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ret double %multmp
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}
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</pre>
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</div>
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<p>In this case, the LHS and RHS of the multiplication are the same value. We'd
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really like to see this generate "<tt>tmp = x+3; result = tmp*tmp;</tt>" instead
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of computing "<tt>x+3</tt>" twice.</p>
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<p>Unfortunately, no amount of local analysis will be able to detect and correct
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this. This requires two transformations: reassociation of expressions (to
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make the add's lexically identical) and Common Subexpression Elimination (CSE)
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to delete the redundant add instruction. Fortunately, LLVM provides a broad
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range of optimizations that you can use, in the form of "passes".</p>
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</div>
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<!-- *********************************************************************** -->
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<h2><a name="optimizerpasses">LLVM Optimization Passes</a></h2>
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<!-- *********************************************************************** -->
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<div>
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<p>LLVM provides many optimization passes, which do many different sorts of
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things and have different tradeoffs. Unlike other systems, LLVM doesn't hold
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to the mistaken notion that one set of optimizations is right for all languages
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and for all situations. LLVM allows a compiler implementor to make complete
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decisions about what optimizations to use, in which order, and in what
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situation.</p>
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<p>As a concrete example, LLVM supports both "whole module" passes, which look
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across as large of body of code as they can (often a whole file, but if run
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at link time, this can be a substantial portion of the whole program). It also
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supports and includes "per-function" passes which just operate on a single
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function at a time, without looking at other functions. For more information
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on passes and how they are run, see the <a href="../WritingAnLLVMPass.html">How
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to Write a Pass</a> document and the <a href="../Passes.html">List of LLVM
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Passes</a>.</p>
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<p>For Kaleidoscope, we are currently generating functions on the fly, one at
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a time, as the user types them in. We aren't shooting for the ultimate
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optimization experience in this setting, but we also want to catch the easy and
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quick stuff where possible. As such, we will choose to run a few per-function
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optimizations as the user types the function in. If we wanted to make a "static
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Kaleidoscope compiler", we would use exactly the code we have now, except that
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we would defer running the optimizer until the entire file has been parsed.</p>
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<p>In order to get per-function optimizations going, we need to set up a
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<a href="../WritingAnLLVMPass.html#passmanager">FunctionPassManager</a> to hold and
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organize the LLVM optimizations that we want to run. Once we have that, we can
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add a set of optimizations to run. The code looks like this:</p>
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<div class="doc_code">
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<pre>
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FunctionPassManager OurFPM(TheModule);
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// Set up the optimizer pipeline. Start with registering info about how the
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// target lays out data structures.
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OurFPM.add(new TargetData(*TheExecutionEngine->getTargetData()));
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// Provide basic AliasAnalysis support for GVN.
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OurFPM.add(createBasicAliasAnalysisPass());
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// Do simple "peephole" optimizations and bit-twiddling optzns.
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OurFPM.add(createInstructionCombiningPass());
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// Reassociate expressions.
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OurFPM.add(createReassociatePass());
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// Eliminate Common SubExpressions.
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OurFPM.add(createGVNPass());
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// Simplify the control flow graph (deleting unreachable blocks, etc).
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OurFPM.add(createCFGSimplificationPass());
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OurFPM.doInitialization();
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// Set the global so the code gen can use this.
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TheFPM = &OurFPM;
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// Run the main "interpreter loop" now.
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MainLoop();
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</pre>
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</div>
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<p>This code defines a <tt>FunctionPassManager</tt>, "<tt>OurFPM</tt>". It
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requires a pointer to the <tt>Module</tt> to construct itself. Once it is set
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up, we use a series of "add" calls to add a bunch of LLVM passes. The first
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pass is basically boilerplate, it adds a pass so that later optimizations know
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how the data structures in the program are laid out. The
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"<tt>TheExecutionEngine</tt>" variable is related to the JIT, which we will get
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to in the next section.</p>
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<p>In this case, we choose to add 4 optimization passes. The passes we chose
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here are a pretty standard set of "cleanup" optimizations that are useful for
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a wide variety of code. I won't delve into what they do but, believe me,
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they are a good starting place :).</p>
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<p>Once the PassManager is set up, we need to make use of it. We do this by
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running it after our newly created function is constructed (in
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<tt>FunctionAST::Codegen</tt>), but before it is returned to the client:</p>
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<div class="doc_code">
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<pre>
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if (Value *RetVal = Body->Codegen()) {
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// Finish off the function.
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Builder.CreateRet(RetVal);
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// Validate the generated code, checking for consistency.
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verifyFunction(*TheFunction);
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<b>// Optimize the function.
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TheFPM->run(*TheFunction);</b>
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return TheFunction;
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}
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</pre>
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</div>
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<p>As you can see, this is pretty straightforward. The
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<tt>FunctionPassManager</tt> optimizes and updates the LLVM Function* in place,
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improving (hopefully) its body. With this in place, we can try our test above
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again:</p>
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<div class="doc_code">
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<pre>
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ready> <b>def test(x) (1+2+x)*(x+(1+2));</b>
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ready> Read function definition:
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define double @test(double %x) {
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entry:
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%addtmp = fadd double %x, 3.000000e+00
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%multmp = fmul double %addtmp, %addtmp
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ret double %multmp
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}
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</pre>
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</div>
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<p>As expected, we now get our nicely optimized code, saving a floating point
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add instruction from every execution of this function.</p>
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<p>LLVM provides a wide variety of optimizations that can be used in certain
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circumstances. Some <a href="../Passes.html">documentation about the various
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passes</a> is available, but it isn't very complete. Another good source of
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ideas can come from looking at the passes that <tt>llvm-gcc</tt> or
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<tt>llvm-ld</tt> run to get started. The "<tt>opt</tt>" tool allows you to
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experiment with passes from the command line, so you can see if they do
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anything.</p>
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<p>Now that we have reasonable code coming out of our front-end, lets talk about
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executing it!</p>
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</div>
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<!-- *********************************************************************** -->
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<h2><a name="jit">Adding a JIT Compiler</a></h2>
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<!-- *********************************************************************** -->
|
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<div>
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<p>Code that is available in LLVM IR can have a wide variety of tools
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applied to it. For example, you can run optimizations on it (as we did above),
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you can dump it out in textual or binary forms, you can compile the code to an
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assembly file (.s) for some target, or you can JIT compile it. The nice thing
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about the LLVM IR representation is that it is the "common currency" between
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many different parts of the compiler.
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</p>
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<p>In this section, we'll add JIT compiler support to our interpreter. The
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basic idea that we want for Kaleidoscope is to have the user enter function
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bodies as they do now, but immediately evaluate the top-level expressions they
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type in. For example, if they type in "1 + 2;", we should evaluate and print
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out 3. If they define a function, they should be able to call it from the
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command line.</p>
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<p>In order to do this, we first declare and initialize the JIT. This is done
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by adding a global variable and a call in <tt>main</tt>:</p>
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<div class="doc_code">
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<pre>
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<b>static ExecutionEngine *TheExecutionEngine;</b>
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...
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int main() {
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..
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<b>// Create the JIT. This takes ownership of the module.
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TheExecutionEngine = EngineBuilder(TheModule).create();</b>
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..
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}
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</pre>
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</div>
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<p>This creates an abstract "Execution Engine" which can be either a JIT
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compiler or the LLVM interpreter. LLVM will automatically pick a JIT compiler
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for you if one is available for your platform, otherwise it will fall back to
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the interpreter.</p>
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<p>Once the <tt>ExecutionEngine</tt> is created, the JIT is ready to be used.
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There are a variety of APIs that are useful, but the simplest one is the
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"<tt>getPointerToFunction(F)</tt>" method. This method JIT compiles the
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specified LLVM Function and returns a function pointer to the generated machine
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code. In our case, this means that we can change the code that parses a
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top-level expression to look like this:</p>
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<div class="doc_code">
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<pre>
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static void HandleTopLevelExpression() {
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// Evaluate a top-level expression into an anonymous function.
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if (FunctionAST *F = ParseTopLevelExpr()) {
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if (Function *LF = F->Codegen()) {
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LF->dump(); // Dump the function for exposition purposes.
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<b>// JIT the function, returning a function pointer.
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void *FPtr = TheExecutionEngine->getPointerToFunction(LF);
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// Cast it to the right type (takes no arguments, returns a double) so we
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// can call it as a native function.
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double (*FP)() = (double (*)())(intptr_t)FPtr;
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fprintf(stderr, "Evaluated to %f\n", FP());</b>
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}
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</pre>
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</div>
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<p>Recall that we compile top-level expressions into a self-contained LLVM
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function that takes no arguments and returns the computed double. Because the
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LLVM JIT compiler matches the native platform ABI, this means that you can just
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cast the result pointer to a function pointer of that type and call it directly.
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This means, there is no difference between JIT compiled code and native machine
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code that is statically linked into your application.</p>
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<p>With just these two changes, lets see how Kaleidoscope works now!</p>
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<div class="doc_code">
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<pre>
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ready> <b>4+5;</b>
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Read top-level expression:
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define double @0() {
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entry:
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ret double 9.000000e+00
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}
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<em>Evaluated to 9.000000</em>
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</pre>
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</div>
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<p>Well this looks like it is basically working. The dump of the function
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shows the "no argument function that always returns double" that we synthesize
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for each top-level expression that is typed in. This demonstrates very basic
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functionality, but can we do more?</p>
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<div class="doc_code">
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<pre>
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ready> <b>def testfunc(x y) x + y*2; </b>
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Read function definition:
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define double @testfunc(double %x, double %y) {
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entry:
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%multmp = fmul double %y, 2.000000e+00
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%addtmp = fadd double %multmp, %x
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ret double %addtmp
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}
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ready> <b>testfunc(4, 10);</b>
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Read top-level expression:
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define double @1() {
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entry:
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%calltmp = call double @testfunc(double 4.000000e+00, double 1.000000e+01)
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ret double %calltmp
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}
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<em>Evaluated to 24.000000</em>
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</pre>
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</div>
|
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<p>This illustrates that we can now call user code, but there is something a bit
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subtle going on here. Note that we only invoke the JIT on the anonymous
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functions that <em>call testfunc</em>, but we never invoked it
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|
on <em>testfunc</em> itself. What actually happened here is that the JIT
|
|
scanned for all non-JIT'd functions transitively called from the anonymous
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function and compiled all of them before returning
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|
from <tt>getPointerToFunction()</tt>.</p>
|
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<p>The JIT provides a number of other more advanced interfaces for things like
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freeing allocated machine code, rejit'ing functions to update them, etc.
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However, even with this simple code, we get some surprisingly powerful
|
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capabilities - check this out (I removed the dump of the anonymous functions,
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you should get the idea by now :) :</p>
|
|
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<div class="doc_code">
|
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<pre>
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ready> <b>extern sin(x);</b>
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Read extern:
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declare double @sin(double)
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|
ready> <b>extern cos(x);</b>
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Read extern:
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declare double @cos(double)
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ready> <b>sin(1.0);</b>
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Read top-level expression:
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define double @2() {
|
|
entry:
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ret double 0x3FEAED548F090CEE
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}
|
|
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<em>Evaluated to 0.841471</em>
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|
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ready> <b>def foo(x) sin(x)*sin(x) + cos(x)*cos(x);</b>
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Read function definition:
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|
define double @foo(double %x) {
|
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entry:
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%calltmp = call double @sin(double %x)
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%multmp = fmul double %calltmp, %calltmp
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%calltmp2 = call double @cos(double %x)
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%multmp4 = fmul double %calltmp2, %calltmp2
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%addtmp = fadd double %multmp, %multmp4
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ret double %addtmp
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}
|
|
|
|
ready> <b>foo(4.0);</b>
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|
Read top-level expression:
|
|
define double @3() {
|
|
entry:
|
|
%calltmp = call double @foo(double 4.000000e+00)
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ret double %calltmp
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}
|
|
|
|
<em>Evaluated to 1.000000</em>
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</pre>
|
|
</div>
|
|
|
|
<p>Whoa, how does the JIT know about sin and cos? The answer is surprisingly
|
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simple: in this
|
|
example, the JIT started execution of a function and got to a function call. It
|
|
realized that the function was not yet JIT compiled and invoked the standard set
|
|
of routines to resolve the function. In this case, there is no body defined
|
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for the function, so the JIT ended up calling "<tt>dlsym("sin")</tt>" on the
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|
Kaleidoscope process itself.
|
|
Since "<tt>sin</tt>" is defined within the JIT's address space, it simply
|
|
patches up calls in the module to call the libm version of <tt>sin</tt>
|
|
directly.</p>
|
|
|
|
<p>The LLVM JIT provides a number of interfaces (look in the
|
|
<tt>ExecutionEngine.h</tt> file) for controlling how unknown functions get
|
|
resolved. It allows you to establish explicit mappings between IR objects and
|
|
addresses (useful for LLVM global variables that you want to map to static
|
|
tables, for example), allows you to dynamically decide on the fly based on the
|
|
function name, and even allows you to have the JIT compile functions lazily the
|
|
first time they're called.</p>
|
|
|
|
<p>One interesting application of this is that we can now extend the language
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|
by writing arbitrary C++ code to implement operations. For example, if we add:
|
|
</p>
|
|
|
|
<div class="doc_code">
|
|
<pre>
|
|
/// putchard - putchar that takes a double and returns 0.
|
|
extern "C"
|
|
double putchard(double X) {
|
|
putchar((char)X);
|
|
return 0;
|
|
}
|
|
</pre>
|
|
</div>
|
|
|
|
<p>Now we can produce simple output to the console by using things like:
|
|
"<tt>extern putchard(x); putchard(120);</tt>", which prints a lowercase 'x' on
|
|
the console (120 is the ASCII code for 'x'). Similar code could be used to
|
|
implement file I/O, console input, and many other capabilities in
|
|
Kaleidoscope.</p>
|
|
|
|
<p>This completes the JIT and optimizer chapter of the Kaleidoscope tutorial. At
|
|
this point, we can compile a non-Turing-complete programming language, optimize
|
|
and JIT compile it in a user-driven way. Next up we'll look into <a
|
|
href="LangImpl5.html">extending the language with control flow constructs</a>,
|
|
tackling some interesting LLVM IR issues along the way.</p>
|
|
|
|
</div>
|
|
|
|
<!-- *********************************************************************** -->
|
|
<h2><a name="code">Full Code Listing</a></h2>
|
|
<!-- *********************************************************************** -->
|
|
|
|
<div>
|
|
|
|
<p>
|
|
Here is the complete code listing for our running example, enhanced with the
|
|
LLVM JIT and optimizer. To build this example, use:
|
|
</p>
|
|
|
|
<div class="doc_code">
|
|
<pre>
|
|
# Compile
|
|
clang++ -g toy.cpp `llvm-config --cppflags --ldflags --libs core jit native` -O3 -o toy
|
|
# Run
|
|
./toy
|
|
</pre>
|
|
</div>
|
|
|
|
<p>
|
|
If you are compiling this on Linux, make sure to add the "-rdynamic" option
|
|
as well. This makes sure that the external functions are resolved properly
|
|
at runtime.</p>
|
|
|
|
<p>Here is the code:</p>
|
|
|
|
<div class="doc_code">
|
|
<pre>
|
|
#include "llvm/DerivedTypes.h"
|
|
#include "llvm/ExecutionEngine/ExecutionEngine.h"
|
|
#include "llvm/ExecutionEngine/JIT.h"
|
|
#include "llvm/LLVMContext.h"
|
|
#include "llvm/Module.h"
|
|
#include "llvm/PassManager.h"
|
|
#include "llvm/Analysis/Verifier.h"
|
|
#include "llvm/Analysis/Passes.h"
|
|
#include "llvm/Target/TargetData.h"
|
|
#include "llvm/Transforms/Scalar.h"
|
|
#include "llvm/Support/IRBuilder.h"
|
|
#include "llvm/Support/TargetSelect.h"
|
|
#include <cstdio>
|
|
#include <string>
|
|
#include <map>
|
|
#include <vector>
|
|
using namespace llvm;
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Lexer
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
// The lexer returns tokens [0-255] if it is an unknown character, otherwise one
|
|
// of these for known things.
|
|
enum Token {
|
|
tok_eof = -1,
|
|
|
|
// commands
|
|
tok_def = -2, tok_extern = -3,
|
|
|
|
// primary
|
|
tok_identifier = -4, tok_number = -5
|
|
};
|
|
|
|
static std::string IdentifierStr; // Filled in if tok_identifier
|
|
static double NumVal; // Filled in if tok_number
|
|
|
|
/// gettok - Return the next token from standard input.
|
|
static int gettok() {
|
|
static int LastChar = ' ';
|
|
|
|
// Skip any whitespace.
|
|
while (isspace(LastChar))
|
|
LastChar = getchar();
|
|
|
|
if (isalpha(LastChar)) { // identifier: [a-zA-Z][a-zA-Z0-9]*
|
|
IdentifierStr = LastChar;
|
|
while (isalnum((LastChar = getchar())))
|
|
IdentifierStr += LastChar;
|
|
|
|
if (IdentifierStr == "def") return tok_def;
|
|
if (IdentifierStr == "extern") return tok_extern;
|
|
return tok_identifier;
|
|
}
|
|
|
|
if (isdigit(LastChar) || LastChar == '.') { // Number: [0-9.]+
|
|
std::string NumStr;
|
|
do {
|
|
NumStr += LastChar;
|
|
LastChar = getchar();
|
|
} while (isdigit(LastChar) || LastChar == '.');
|
|
|
|
NumVal = strtod(NumStr.c_str(), 0);
|
|
return tok_number;
|
|
}
|
|
|
|
if (LastChar == '#') {
|
|
// Comment until end of line.
|
|
do LastChar = getchar();
|
|
while (LastChar != EOF && LastChar != '\n' && LastChar != '\r');
|
|
|
|
if (LastChar != EOF)
|
|
return gettok();
|
|
}
|
|
|
|
// Check for end of file. Don't eat the EOF.
|
|
if (LastChar == EOF)
|
|
return tok_eof;
|
|
|
|
// Otherwise, just return the character as its ascii value.
|
|
int ThisChar = LastChar;
|
|
LastChar = getchar();
|
|
return ThisChar;
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Abstract Syntax Tree (aka Parse Tree)
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// ExprAST - Base class for all expression nodes.
|
|
class ExprAST {
|
|
public:
|
|
virtual ~ExprAST() {}
|
|
virtual Value *Codegen() = 0;
|
|
};
|
|
|
|
/// NumberExprAST - Expression class for numeric literals like "1.0".
|
|
class NumberExprAST : public ExprAST {
|
|
double Val;
|
|
public:
|
|
NumberExprAST(double val) : Val(val) {}
|
|
virtual Value *Codegen();
|
|
};
|
|
|
|
/// VariableExprAST - Expression class for referencing a variable, like "a".
|
|
class VariableExprAST : public ExprAST {
|
|
std::string Name;
|
|
public:
|
|
VariableExprAST(const std::string &name) : Name(name) {}
|
|
virtual Value *Codegen();
|
|
};
|
|
|
|
/// BinaryExprAST - Expression class for a binary operator.
|
|
class BinaryExprAST : public ExprAST {
|
|
char Op;
|
|
ExprAST *LHS, *RHS;
|
|
public:
|
|
BinaryExprAST(char op, ExprAST *lhs, ExprAST *rhs)
|
|
: Op(op), LHS(lhs), RHS(rhs) {}
|
|
virtual Value *Codegen();
|
|
};
|
|
|
|
/// CallExprAST - Expression class for function calls.
|
|
class CallExprAST : public ExprAST {
|
|
std::string Callee;
|
|
std::vector<ExprAST*> Args;
|
|
public:
|
|
CallExprAST(const std::string &callee, std::vector<ExprAST*> &args)
|
|
: Callee(callee), Args(args) {}
|
|
virtual Value *Codegen();
|
|
};
|
|
|
|
/// PrototypeAST - This class represents the "prototype" for a function,
|
|
/// which captures its name, and its argument names (thus implicitly the number
|
|
/// of arguments the function takes).
|
|
class PrototypeAST {
|
|
std::string Name;
|
|
std::vector<std::string> Args;
|
|
public:
|
|
PrototypeAST(const std::string &name, const std::vector<std::string> &args)
|
|
: Name(name), Args(args) {}
|
|
|
|
Function *Codegen();
|
|
};
|
|
|
|
/// FunctionAST - This class represents a function definition itself.
|
|
class FunctionAST {
|
|
PrototypeAST *Proto;
|
|
ExprAST *Body;
|
|
public:
|
|
FunctionAST(PrototypeAST *proto, ExprAST *body)
|
|
: Proto(proto), Body(body) {}
|
|
|
|
Function *Codegen();
|
|
};
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Parser
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// CurTok/getNextToken - Provide a simple token buffer. CurTok is the current
|
|
/// token the parser is looking at. getNextToken reads another token from the
|
|
/// lexer and updates CurTok with its results.
|
|
static int CurTok;
|
|
static int getNextToken() {
|
|
return CurTok = gettok();
|
|
}
|
|
|
|
/// BinopPrecedence - This holds the precedence for each binary operator that is
|
|
/// defined.
|
|
static std::map<char, int> BinopPrecedence;
|
|
|
|
/// GetTokPrecedence - Get the precedence of the pending binary operator token.
|
|
static int GetTokPrecedence() {
|
|
if (!isascii(CurTok))
|
|
return -1;
|
|
|
|
// Make sure it's a declared binop.
|
|
int TokPrec = BinopPrecedence[CurTok];
|
|
if (TokPrec <= 0) return -1;
|
|
return TokPrec;
|
|
}
|
|
|
|
/// Error* - These are little helper functions for error handling.
|
|
ExprAST *Error(const char *Str) { fprintf(stderr, "Error: %s\n", Str);return 0;}
|
|
PrototypeAST *ErrorP(const char *Str) { Error(Str); return 0; }
|
|
FunctionAST *ErrorF(const char *Str) { Error(Str); return 0; }
|
|
|
|
static ExprAST *ParseExpression();
|
|
|
|
/// identifierexpr
|
|
/// ::= identifier
|
|
/// ::= identifier '(' expression* ')'
|
|
static ExprAST *ParseIdentifierExpr() {
|
|
std::string IdName = IdentifierStr;
|
|
|
|
getNextToken(); // eat identifier.
|
|
|
|
if (CurTok != '(') // Simple variable ref.
|
|
return new VariableExprAST(IdName);
|
|
|
|
// Call.
|
|
getNextToken(); // eat (
|
|
std::vector<ExprAST*> Args;
|
|
if (CurTok != ')') {
|
|
while (1) {
|
|
ExprAST *Arg = ParseExpression();
|
|
if (!Arg) return 0;
|
|
Args.push_back(Arg);
|
|
|
|
if (CurTok == ')') break;
|
|
|
|
if (CurTok != ',')
|
|
return Error("Expected ')' or ',' in argument list");
|
|
getNextToken();
|
|
}
|
|
}
|
|
|
|
// Eat the ')'.
|
|
getNextToken();
|
|
|
|
return new CallExprAST(IdName, Args);
|
|
}
|
|
|
|
/// numberexpr ::= number
|
|
static ExprAST *ParseNumberExpr() {
|
|
ExprAST *Result = new NumberExprAST(NumVal);
|
|
getNextToken(); // consume the number
|
|
return Result;
|
|
}
|
|
|
|
/// parenexpr ::= '(' expression ')'
|
|
static ExprAST *ParseParenExpr() {
|
|
getNextToken(); // eat (.
|
|
ExprAST *V = ParseExpression();
|
|
if (!V) return 0;
|
|
|
|
if (CurTok != ')')
|
|
return Error("expected ')'");
|
|
getNextToken(); // eat ).
|
|
return V;
|
|
}
|
|
|
|
/// primary
|
|
/// ::= identifierexpr
|
|
/// ::= numberexpr
|
|
/// ::= parenexpr
|
|
static ExprAST *ParsePrimary() {
|
|
switch (CurTok) {
|
|
default: return Error("unknown token when expecting an expression");
|
|
case tok_identifier: return ParseIdentifierExpr();
|
|
case tok_number: return ParseNumberExpr();
|
|
case '(': return ParseParenExpr();
|
|
}
|
|
}
|
|
|
|
/// binoprhs
|
|
/// ::= ('+' primary)*
|
|
static ExprAST *ParseBinOpRHS(int ExprPrec, ExprAST *LHS) {
|
|
// If this is a binop, find its precedence.
|
|
while (1) {
|
|
int TokPrec = GetTokPrecedence();
|
|
|
|
// If this is a binop that binds at least as tightly as the current binop,
|
|
// consume it, otherwise we are done.
|
|
if (TokPrec < ExprPrec)
|
|
return LHS;
|
|
|
|
// Okay, we know this is a binop.
|
|
int BinOp = CurTok;
|
|
getNextToken(); // eat binop
|
|
|
|
// Parse the primary expression after the binary operator.
|
|
ExprAST *RHS = ParsePrimary();
|
|
if (!RHS) return 0;
|
|
|
|
// If BinOp binds less tightly with RHS than the operator after RHS, let
|
|
// the pending operator take RHS as its LHS.
|
|
int NextPrec = GetTokPrecedence();
|
|
if (TokPrec < NextPrec) {
|
|
RHS = ParseBinOpRHS(TokPrec+1, RHS);
|
|
if (RHS == 0) return 0;
|
|
}
|
|
|
|
// Merge LHS/RHS.
|
|
LHS = new BinaryExprAST(BinOp, LHS, RHS);
|
|
}
|
|
}
|
|
|
|
/// expression
|
|
/// ::= primary binoprhs
|
|
///
|
|
static ExprAST *ParseExpression() {
|
|
ExprAST *LHS = ParsePrimary();
|
|
if (!LHS) return 0;
|
|
|
|
return ParseBinOpRHS(0, LHS);
|
|
}
|
|
|
|
/// prototype
|
|
/// ::= id '(' id* ')'
|
|
static PrototypeAST *ParsePrototype() {
|
|
if (CurTok != tok_identifier)
|
|
return ErrorP("Expected function name in prototype");
|
|
|
|
std::string FnName = IdentifierStr;
|
|
getNextToken();
|
|
|
|
if (CurTok != '(')
|
|
return ErrorP("Expected '(' in prototype");
|
|
|
|
std::vector<std::string> ArgNames;
|
|
while (getNextToken() == tok_identifier)
|
|
ArgNames.push_back(IdentifierStr);
|
|
if (CurTok != ')')
|
|
return ErrorP("Expected ')' in prototype");
|
|
|
|
// success.
|
|
getNextToken(); // eat ')'.
|
|
|
|
return new PrototypeAST(FnName, ArgNames);
|
|
}
|
|
|
|
/// definition ::= 'def' prototype expression
|
|
static FunctionAST *ParseDefinition() {
|
|
getNextToken(); // eat def.
|
|
PrototypeAST *Proto = ParsePrototype();
|
|
if (Proto == 0) return 0;
|
|
|
|
if (ExprAST *E = ParseExpression())
|
|
return new FunctionAST(Proto, E);
|
|
return 0;
|
|
}
|
|
|
|
/// toplevelexpr ::= expression
|
|
static FunctionAST *ParseTopLevelExpr() {
|
|
if (ExprAST *E = ParseExpression()) {
|
|
// Make an anonymous proto.
|
|
PrototypeAST *Proto = new PrototypeAST("", std::vector<std::string>());
|
|
return new FunctionAST(Proto, E);
|
|
}
|
|
return 0;
|
|
}
|
|
|
|
/// external ::= 'extern' prototype
|
|
static PrototypeAST *ParseExtern() {
|
|
getNextToken(); // eat extern.
|
|
return ParsePrototype();
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Code Generation
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
static Module *TheModule;
|
|
static IRBuilder<> Builder(getGlobalContext());
|
|
static std::map<std::string, Value*> NamedValues;
|
|
static FunctionPassManager *TheFPM;
|
|
|
|
Value *ErrorV(const char *Str) { Error(Str); return 0; }
|
|
|
|
Value *NumberExprAST::Codegen() {
|
|
return ConstantFP::get(getGlobalContext(), APFloat(Val));
|
|
}
|
|
|
|
Value *VariableExprAST::Codegen() {
|
|
// Look this variable up in the function.
|
|
Value *V = NamedValues[Name];
|
|
return V ? V : ErrorV("Unknown variable name");
|
|
}
|
|
|
|
Value *BinaryExprAST::Codegen() {
|
|
Value *L = LHS->Codegen();
|
|
Value *R = RHS->Codegen();
|
|
if (L == 0 || R == 0) return 0;
|
|
|
|
switch (Op) {
|
|
case '+': return Builder.CreateFAdd(L, R, "addtmp");
|
|
case '-': return Builder.CreateFSub(L, R, "subtmp");
|
|
case '*': return Builder.CreateFMul(L, R, "multmp");
|
|
case '<':
|
|
L = Builder.CreateFCmpULT(L, R, "cmptmp");
|
|
// Convert bool 0/1 to double 0.0 or 1.0
|
|
return Builder.CreateUIToFP(L, Type::getDoubleTy(getGlobalContext()),
|
|
"booltmp");
|
|
default: return ErrorV("invalid binary operator");
|
|
}
|
|
}
|
|
|
|
Value *CallExprAST::Codegen() {
|
|
// Look up the name in the global module table.
|
|
Function *CalleeF = TheModule->getFunction(Callee);
|
|
if (CalleeF == 0)
|
|
return ErrorV("Unknown function referenced");
|
|
|
|
// If argument mismatch error.
|
|
if (CalleeF->arg_size() != Args.size())
|
|
return ErrorV("Incorrect # arguments passed");
|
|
|
|
std::vector<Value*> ArgsV;
|
|
for (unsigned i = 0, e = Args.size(); i != e; ++i) {
|
|
ArgsV.push_back(Args[i]->Codegen());
|
|
if (ArgsV.back() == 0) return 0;
|
|
}
|
|
|
|
return Builder.CreateCall(CalleeF, ArgsV, "calltmp");
|
|
}
|
|
|
|
Function *PrototypeAST::Codegen() {
|
|
// Make the function type: double(double,double) etc.
|
|
std::vector<Type*> Doubles(Args.size(),
|
|
Type::getDoubleTy(getGlobalContext()));
|
|
FunctionType *FT = FunctionType::get(Type::getDoubleTy(getGlobalContext()),
|
|
Doubles, false);
|
|
|
|
Function *F = Function::Create(FT, Function::ExternalLinkage, Name, TheModule);
|
|
|
|
// If F conflicted, there was already something named 'Name'. If it has a
|
|
// body, don't allow redefinition or reextern.
|
|
if (F->getName() != Name) {
|
|
// Delete the one we just made and get the existing one.
|
|
F->eraseFromParent();
|
|
F = TheModule->getFunction(Name);
|
|
|
|
// If F already has a body, reject this.
|
|
if (!F->empty()) {
|
|
ErrorF("redefinition of function");
|
|
return 0;
|
|
}
|
|
|
|
// If F took a different number of args, reject.
|
|
if (F->arg_size() != Args.size()) {
|
|
ErrorF("redefinition of function with different # args");
|
|
return 0;
|
|
}
|
|
}
|
|
|
|
// Set names for all arguments.
|
|
unsigned Idx = 0;
|
|
for (Function::arg_iterator AI = F->arg_begin(); Idx != Args.size();
|
|
++AI, ++Idx) {
|
|
AI->setName(Args[Idx]);
|
|
|
|
// Add arguments to variable symbol table.
|
|
NamedValues[Args[Idx]] = AI;
|
|
}
|
|
|
|
return F;
|
|
}
|
|
|
|
Function *FunctionAST::Codegen() {
|
|
NamedValues.clear();
|
|
|
|
Function *TheFunction = Proto->Codegen();
|
|
if (TheFunction == 0)
|
|
return 0;
|
|
|
|
// Create a new basic block to start insertion into.
|
|
BasicBlock *BB = BasicBlock::Create(getGlobalContext(), "entry", TheFunction);
|
|
Builder.SetInsertPoint(BB);
|
|
|
|
if (Value *RetVal = Body->Codegen()) {
|
|
// Finish off the function.
|
|
Builder.CreateRet(RetVal);
|
|
|
|
// Validate the generated code, checking for consistency.
|
|
verifyFunction(*TheFunction);
|
|
|
|
// Optimize the function.
|
|
TheFPM->run(*TheFunction);
|
|
|
|
return TheFunction;
|
|
}
|
|
|
|
// Error reading body, remove function.
|
|
TheFunction->eraseFromParent();
|
|
return 0;
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Top-Level parsing and JIT Driver
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
static ExecutionEngine *TheExecutionEngine;
|
|
|
|
static void HandleDefinition() {
|
|
if (FunctionAST *F = ParseDefinition()) {
|
|
if (Function *LF = F->Codegen()) {
|
|
fprintf(stderr, "Read function definition:");
|
|
LF->dump();
|
|
}
|
|
} else {
|
|
// Skip token for error recovery.
|
|
getNextToken();
|
|
}
|
|
}
|
|
|
|
static void HandleExtern() {
|
|
if (PrototypeAST *P = ParseExtern()) {
|
|
if (Function *F = P->Codegen()) {
|
|
fprintf(stderr, "Read extern: ");
|
|
F->dump();
|
|
}
|
|
} else {
|
|
// Skip token for error recovery.
|
|
getNextToken();
|
|
}
|
|
}
|
|
|
|
static void HandleTopLevelExpression() {
|
|
// Evaluate a top-level expression into an anonymous function.
|
|
if (FunctionAST *F = ParseTopLevelExpr()) {
|
|
if (Function *LF = F->Codegen()) {
|
|
fprintf(stderr, "Read top-level expression:");
|
|
LF->dump();
|
|
|
|
// JIT the function, returning a function pointer.
|
|
void *FPtr = TheExecutionEngine->getPointerToFunction(LF);
|
|
|
|
// Cast it to the right type (takes no arguments, returns a double) so we
|
|
// can call it as a native function.
|
|
double (*FP)() = (double (*)())(intptr_t)FPtr;
|
|
fprintf(stderr, "Evaluated to %f\n", FP());
|
|
}
|
|
} else {
|
|
// Skip token for error recovery.
|
|
getNextToken();
|
|
}
|
|
}
|
|
|
|
/// top ::= definition | external | expression | ';'
|
|
static void MainLoop() {
|
|
while (1) {
|
|
fprintf(stderr, "ready> ");
|
|
switch (CurTok) {
|
|
case tok_eof: return;
|
|
case ';': getNextToken(); break; // ignore top-level semicolons.
|
|
case tok_def: HandleDefinition(); break;
|
|
case tok_extern: HandleExtern(); break;
|
|
default: HandleTopLevelExpression(); break;
|
|
}
|
|
}
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// "Library" functions that can be "extern'd" from user code.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
/// putchard - putchar that takes a double and returns 0.
|
|
extern "C"
|
|
double putchard(double X) {
|
|
putchar((char)X);
|
|
return 0;
|
|
}
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Main driver code.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
int main() {
|
|
InitializeNativeTarget();
|
|
LLVMContext &Context = getGlobalContext();
|
|
|
|
// Install standard binary operators.
|
|
// 1 is lowest precedence.
|
|
BinopPrecedence['<'] = 10;
|
|
BinopPrecedence['+'] = 20;
|
|
BinopPrecedence['-'] = 20;
|
|
BinopPrecedence['*'] = 40; // highest.
|
|
|
|
// Prime the first token.
|
|
fprintf(stderr, "ready> ");
|
|
getNextToken();
|
|
|
|
// Make the module, which holds all the code.
|
|
TheModule = new Module("my cool jit", Context);
|
|
|
|
// Create the JIT. This takes ownership of the module.
|
|
std::string ErrStr;
|
|
TheExecutionEngine = EngineBuilder(TheModule).setErrorStr(&ErrStr).create();
|
|
if (!TheExecutionEngine) {
|
|
fprintf(stderr, "Could not create ExecutionEngine: %s\n", ErrStr.c_str());
|
|
exit(1);
|
|
}
|
|
|
|
FunctionPassManager OurFPM(TheModule);
|
|
|
|
// Set up the optimizer pipeline. Start with registering info about how the
|
|
// target lays out data structures.
|
|
OurFPM.add(new TargetData(*TheExecutionEngine->getTargetData()));
|
|
// Provide basic AliasAnalysis support for GVN.
|
|
OurFPM.add(createBasicAliasAnalysisPass());
|
|
// Do simple "peephole" optimizations and bit-twiddling optzns.
|
|
OurFPM.add(createInstructionCombiningPass());
|
|
// Reassociate expressions.
|
|
OurFPM.add(createReassociatePass());
|
|
// Eliminate Common SubExpressions.
|
|
OurFPM.add(createGVNPass());
|
|
// Simplify the control flow graph (deleting unreachable blocks, etc).
|
|
OurFPM.add(createCFGSimplificationPass());
|
|
|
|
OurFPM.doInitialization();
|
|
|
|
// Set the global so the code gen can use this.
|
|
TheFPM = &OurFPM;
|
|
|
|
// Run the main "interpreter loop" now.
|
|
MainLoop();
|
|
|
|
TheFPM = 0;
|
|
|
|
// Print out all of the generated code.
|
|
TheModule->dump();
|
|
|
|
return 0;
|
|
}
|
|
</pre>
|
|
</div>
|
|
|
|
<a href="LangImpl5.html">Next: Extending the language: control flow</a>
|
|
</div>
|
|
|
|
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<a href="mailto:sabre@nondot.org">Chris Lattner</a><br>
|
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<a href="http://llvm.org/">The LLVM Compiler Infrastructure</a><br>
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Last modified: $Date$
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</address>
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