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Kaleidoscope: Compiling to Object Code

Chapter 8 Introduction

Welcome to Chapter 8 of the "Implementing a language with LLVM" tutorial. This chapter describes how to compile our language down to object files.

Choosing a target

LLVM has native support for cross-compilation. You can compile to the architecture of your current machine, or just as easily compile for other architectures. In this tutorial, we'll target the current machine.

To specify the architecture that you want to target, we use a string called a "target triple". This takes the form <arch><sub>-<vendor>-<sys>-<abi> (see the cross compilation docs).

As an example, we can see what clang thinks is our current target triple:

$ clang --version | grep Target
Target: x86_64-unknown-linux-gnu

Running this command may show something different on your machine as you might be using a different architecture or operating system to me.

Fortunately, we don't need to hard-code a target triple to target the current machine. LLVM provides sys::getDefaultTargetTriple, which returns the target triple of the current machine.

auto TargetTriple = sys::getDefaultTargetTriple();

LLVM doesn't require us to link in all the target functionality. For example, if we're just using the JIT, we don't need the assembly printers. Similarly, if we're only targeting certain architectures, we can only link in the functionality for those architectures.

For this example, we'll initialize all the targets for emitting object code.


We can now use our target triple to get a Target:

std::string Error;
auto Target = TargetRegistry::lookupTarget(TargetTriple, Error);

// Print an error and exit if we couldn't find the requested target.
// This generally occurs if we've forgotten to initialise the
// TargetRegistry or we have a bogus target triple.
if (!Target) {
  errs() << Error;
  return 1;

Target Machine

We will also need a TargetMachine. This class provides a complete machine description of the machine we're targeting. If we want to target a specific feature (such as SSE) or a specific CPU (such as Intel's Sandylake), we do so now.

To see which features and CPUs that LLVM knows about, we can use llc. For example, let's look at x86:

$ llvm-as < /dev/null | llc -march=x86 -mattr=help
Available CPUs for this target:

  amdfam10      - Select the amdfam10 processor.
  athlon        - Select the athlon processor.
  athlon-4      - Select the athlon-4 processor.

Available features for this target:

  16bit-mode            - 16-bit mode (i8086).
  32bit-mode            - 32-bit mode (80386).
  3dnow                 - Enable 3DNow! instructions.
  3dnowa                - Enable 3DNow! Athlon instructions.

For our example, we'll use the generic CPU without any additional features, options or relocation model.

auto CPU = "generic";
auto Features = "";

TargetOptions opt;
auto RM = Optional<Reloc::Model>();
auto TargetMachine = Target->createTargetMachine(TargetTriple, CPU, Features, opt, RM);

Configuring the Module

We're now ready to configure our module, to specify the target and data layout. This isn't strictly necessary, but the frontend performance guide recommends this. Optimizations benefit from knowing about the target and data layout.


Emit Object Code

We're ready to emit object code! Let's define where we want to write our file to:

auto Filename = "output.o";
std::error_code EC;
raw_fd_ostream dest(Filename, EC, sys::fs::F_None);

if (EC) {
  errs() << "Could not open file: " << EC.message();
  return 1;

Finally, we define a pass that emits object code, then we run that pass:

legacy::PassManager pass;
auto FileType = TargetMachine::CGFT_ObjectFile;

if (TargetMachine->addPassesToEmitFile(pass, dest, nullptr, FileType)) {
  errs() << "TargetMachine can't emit a file of this type";
  return 1;


Putting It All Together

Does it work? Let's give it a try. We need to compile our code, but note that the arguments to llvm-config are different to the previous chapters.

$ clang++ -g -O3 toy.cpp `llvm-config --cxxflags --ldflags --system-libs --libs all` -o toy

Let's run it, and define a simple average function. Press Ctrl-D when you're done.

$ ./toy
ready> def average(x y) (x + y) * 0.5;
Wrote output.o

We have an object file! To test it, let's write a simple program and link it with our output. Here's the source code:

#include <iostream>

extern "C" {
    double average(double, double);

int main() {
    std::cout << "average of 3.0 and 4.0: " << average(3.0, 4.0) << std::endl;

We link our program to output.o and check the result is what we expected:

$ clang++ main.cpp output.o -o main
$ ./main
average of 3.0 and 4.0: 3.5