Writing an LLVM Pass (legacy PM version)

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Introduction --- What is a pass?

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This document deals with the legacy pass manager. LLVM uses the new pass manager for the optimization pipeline (the codegen pipeline still uses the legacy pass manager), which has its own way of defining passes. For more details, see WritingAnLLVMNewPMPass{.interpreted-text role=“doc”} and NewPassManager{.interpreted-text role=“doc”}. ::::

The LLVM Pass Framework is an important part of the LLVM system, because LLVM passes are where most of the interesting parts of the compiler exist. Passes perform the transformations and optimizations that make up the compiler, they build the analysis results that are used by these transformations, and they are, above all, a structuring technique for compiler code.

All LLVM passes are subclasses of the Pass class, which implement functionality by overriding virtual methods inherited from Pass. Depending on how your pass works, you should inherit from the ModulePass <writing-an-llvm-pass-ModulePass>{.interpreted-text role=“ref”} , CallGraphSCCPass <writing-an-llvm-pass-CallGraphSCCPass>{.interpreted-text role=“ref”}, FunctionPass <writing-an-llvm-pass-FunctionPass>{.interpreted-text role=“ref”} , or LoopPass <writing-an-llvm-pass-LoopPass>{.interpreted-text role=“ref”}, or RegionPass <writing-an-llvm-pass-RegionPass>{.interpreted-text role=“ref”} classes, which gives the system more information about what your pass does, and how it can be combined with other passes. One of the main features of the LLVM Pass Framework is that it schedules passes to run in an efficient way based on the constraints that your pass meets (which are indicated by which class they derive from).

Pass classes and requirements {#writing-an-llvm-pass-pass-classes}

One of the first things that you should do when designing a new pass is to decide what class you should subclass for your pass. Here we talk about the classes available, from the most general to the most specific.

When choosing a superclass for your Pass, you should choose the most specific class possible, while still being able to meet the requirements listed. This gives the LLVM Pass Infrastructure information necessary to optimize how passes are run, so that the resultant compiler isn’t unnecessarily slow.

The ImmutablePass class

The most plain and boring type of pass is the “ImmutablePass” class. This pass type is used for passes that do not have to be run, do not change state, and never need to be updated. This is not a normal type of transformation or analysis, but can provide information about the current compiler configuration.

Although this pass class is very infrequently used, it is important for providing information about the current target machine being compiled for, and other static information that can affect the various transformations.

ImmutablePasses never invalidate other transformations, are never invalidated, and are never “run”.

The ModulePass class {#writing-an-llvm-pass-ModulePass}

The ModulePass class is the most general of all superclasses that you can use. Deriving from ModulePass indicates that your pass uses the entire program as a unit, referring to function bodies in no predictable order, or adding and removing functions. Because nothing is known about the behavior of ModulePass subclasses, no optimization can be done for their execution.

A module pass can use function level passes (e.g. dominators) using the getAnalysis interface getAnalysis<DominatorTree>(llvm::Function *) to provide the function to retrieve analysis result for, if the function pass does not require any module or immutable passes. Note that this can only be done for functions for which the analysis ran, e.g. in the case of dominators you should only ask for the DominatorTree for function definitions, not declarations.

To write a correct ModulePass subclass, derive from ModulePass and override the runOnModule method with the following signature:

The runOnModule method

virtual bool runOnModule(Module &M) = 0;

The runOnModule method performs the interesting work of the pass. It should return true if the module was modified by the transformation and false otherwise.

The CallGraphSCCPass class {#writing-an-llvm-pass-CallGraphSCCPass}

The CallGraphSCCPass is used by passes that need to traverse the program bottom-up on the call graph (callees before callers). Deriving from CallGraphSCCPass provides some mechanics for building and traversing the CallGraph, but also allows the system to optimize execution of CallGraphSCCPasses. If your pass meets the requirements outlined below, and doesn’t meet the requirements of a FunctionPass <writing-an-llvm-pass-FunctionPass>{.interpreted-text role=“ref”}, you should derive from CallGraphSCCPass.

TODO: explain briefly what SCC, Tarjan’s algo, and B-U mean.

To be explicit, CallGraphSCCPass subclasses are:

1. … not allowed to inspect or modify any Functions other than those in the current SCC and the direct callers and direct callees of the SCC.
2. … required to preserve the current CallGraph object, updating it to reflect any changes made to the program.
3. … not allowed to add or remove SCC’s from the current Module, though they may change the contents of an SCC.
4. … allowed to add or remove global variables from the current Module.
5. … allowed to maintain state across invocations of runOnSCC <writing-an-llvm-pass-runOnSCC>{.interpreted-text role=“ref”} (including global data).

Implementing a CallGraphSCCPass is slightly tricky in some cases because it has to handle SCCs with more than one node in it. All of the virtual methods described below should return true if they modified the program, or false if they didn’t.

The doInitialization(CallGraph &) method

virtual bool doInitialization(CallGraph &CG);

The doInitialization method is allowed to do most of the things that CallGraphSCCPasses are not allowed to do. They can add and remove functions, get pointers to functions, etc. The doInitialization method is designed to do simple initialization type of stuff that does not depend on the SCCs being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast).

The runOnSCC method {#writing-an-llvm-pass-runOnSCC}

virtual bool runOnSCC(CallGraphSCC &SCC) = 0;

The runOnSCC method performs the interesting work of the pass, and should return true if the module was modified by the transformation, false otherwise.

The doFinalization(CallGraph &) method

virtual bool doFinalization(CallGraph &CG);

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnSCC <writing-an-llvm-pass-runOnSCC>{.interpreted-text role=“ref”} for every SCC in the program being compiled.

The FunctionPass class {#writing-an-llvm-pass-FunctionPass}

In contrast to ModulePass subclasses, FunctionPass subclasses do have a predictable, local behavior that can be expected by the system. All FunctionPass execute on each function in the program independent of all of the other functions in the program. FunctionPasses do not require that they are executed in a particular order, and FunctionPasses do not modify external functions.

To be explicit, FunctionPass subclasses are not allowed to:

1. Inspect or modify a Function other than the one currently being processed.
2. Add or remove Functions from the current Module.
3. Add or remove global variables from the current Module.
4. Maintain state across invocations of runOnFunction <writing-an-llvm-pass-runOnFunction>{.interpreted-text role=“ref”} (including global data).

Implementing a FunctionPass is usually straightforward. FunctionPasses may override three virtual methods to do their work. All of these methods should return true if they modified the program, or false if they didn’t.

The doInitialization(Module &) method {#writing-an-llvm-pass-doInitialization-mod}

virtual bool doInitialization(Module &M);

The doInitialization method is allowed to do most of the things that FunctionPasses are not allowed to do. They can add and remove functions, get pointers to functions, etc. The doInitialization method is designed to do simple initialization type of stuff that does not depend on the functions being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast).

A good example of how this method should be used is the LowerAllocations pass. This pass converts malloc and free instructions into platform dependent malloc() and free() function calls. It uses the doInitialization method to get a reference to the malloc and free functions that it needs, adding prototypes to the module if necessary.

The runOnFunction method {#writing-an-llvm-pass-runOnFunction}

virtual bool runOnFunction(Function &F) = 0;

The runOnFunction method must be implemented by your subclass to do the transformation or analysis work of your pass. As usual, a true value should be returned if the function is modified.

The doFinalization(Module &) method {#writing-an-llvm-pass-doFinalization-mod}

virtual bool doFinalization(Module &M);

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnFunction <writing-an-llvm-pass-runOnFunction>{.interpreted-text role=“ref”} for every function in the program being compiled.

The LoopPass class {#writing-an-llvm-pass-LoopPass}

All LoopPass execute on each loop <loop-terminology>{.interpreted-text role=“ref”} in the function independent of all of the other loops in the function. LoopPass processes loops in loop nest order such that outer most loop is processed last.

LoopPass subclasses are allowed to update loop nest using LPPassManager interface. Implementing a loop pass is usually straightforward. LoopPasses may override three virtual methods to do their work. All these methods should return true if they modified the program, or false if they didn’t.

A LoopPass subclass which is intended to run as part of the main loop pass pipeline needs to preserve all of the same function analyses that the other loop passes in its pipeline require. To make that easier, a getLoopAnalysisUsage function is provided by LoopUtils.h. It can be called within the subclass’s getAnalysisUsage override to get consistent and correct behavior. Analogously, INITIALIZE_PASS_DEPENDENCY(LoopPass) will initialize this set of function analyses.

The doInitialization(Loop *, LPPassManager &) method

virtual bool doInitialization(Loop *, LPPassManager &LPM);

The doInitialization method is designed to do simple initialization type of stuff that does not depend on the functions being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast). LPPassManager interface should be used to access Function or Module level analysis information.

The runOnLoop method {#writing-an-llvm-pass-runOnLoop}

virtual bool runOnLoop(Loop *, LPPassManager &LPM) = 0;

The runOnLoop method must be implemented by your subclass to do the transformation or analysis work of your pass. As usual, a true value should be returned if the function is modified. LPPassManager interface should be used to update loop nest.

The doFinalization() method

virtual bool doFinalization();

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnLoop <writing-an-llvm-pass-runOnLoop>{.interpreted-text role=“ref”} for every loop in the program being compiled.

The RegionPass class {#writing-an-llvm-pass-RegionPass}

RegionPass is similar to LoopPass <writing-an-llvm-pass-LoopPass>{.interpreted-text role=“ref”}, but executes on each single entry single exit region in the function. RegionPass processes regions in nested order such that the outer most region is processed last.

RegionPass subclasses are allowed to update the region tree by using the RGPassManager interface. You may override three virtual methods of RegionPass to implement your own region pass. All these methods should return true if they modified the program, or false if they did not.

The doInitialization(Region *, RGPassManager &) method

virtual bool doInitialization(Region *, RGPassManager &RGM);

The doInitialization method is designed to do simple initialization type of stuff that does not depend on the functions being processed. The doInitialization method call is not scheduled to overlap with any other pass executions (thus it should be very fast). RPPassManager interface should be used to access Function or Module level analysis information.

The runOnRegion method {#writing-an-llvm-pass-runOnRegion}

virtual bool runOnRegion(Region *, RGPassManager &RGM) = 0;

The runOnRegion method must be implemented by your subclass to do the transformation or analysis work of your pass. As usual, a true value should be returned if the region is modified. RGPassManager interface should be used to update region tree.

The doFinalization() method

virtual bool doFinalization();

The doFinalization method is an infrequently used method that is called when the pass framework has finished calling runOnRegion <writing-an-llvm-pass-runOnRegion>{.interpreted-text role=“ref”} for every region in the program being compiled.

The MachineFunctionPass class

A MachineFunctionPass is a part of the LLVM code generator that executes on the machine-dependent representation of each LLVM function in the program.

Code generator passes are registered and initialized specially by TargetMachine::addPassesToEmitFile and similar routines, so they cannot generally be run from the opt{.interpreted-text role=“program”} or bugpoint{.interpreted-text role=“program”} commands.

A MachineFunctionPass is also a FunctionPass, so all the restrictions that apply to a FunctionPass also apply to it. MachineFunctionPasses also have additional restrictions. In particular, MachineFunctionPasses are not allowed to do any of the following:

1. Modify or create any LLVM IR Instructions, BasicBlocks, Arguments, Functions, GlobalVariables, GlobalAliases, or Modules.
2. Modify a MachineFunction other than the one currently being processed.
3. Maintain state across invocations of runOnMachineFunction <writing-an-llvm-pass-runOnMachineFunction>{.interpreted-text role=“ref”} (including global data).

The runOnMachineFunction(MachineFunction &MF) method {#writing-an-llvm-pass-runOnMachineFunction}

virtual bool runOnMachineFunction(MachineFunction &MF) = 0;

runOnMachineFunction can be considered the main entry point of a MachineFunctionPass; that is, you should override this method to do the work of your MachineFunctionPass.

The runOnMachineFunction method is called on every MachineFunction in a Module, so that the MachineFunctionPass may perform optimizations on the machine-dependent representation of the function. If you want to get at the LLVM Function for the MachineFunction you’re working on, use MachineFunction’s getFunction() accessor method --- but remember, you may not modify the LLVM Function or its contents from a MachineFunctionPass.

Pass registration {#writing-an-llvm-pass-registration}

Passes are registered with the RegisterPass template. The template parameter is the name of the pass that is to be used on the command line to specify that the pass should be added to a program. The first argument is the name of the pass, which is to be used for the -help{.interpreted-text role=“option”} output of programs, as well as for debug output generated by the [—debug-pass]{.title-ref} option.

If you want your pass to be easily dumpable, you should implement the virtual print method:

The print method

virtual void print(llvm::raw_ostream &O, const Module *M) const;

The print method must be implemented by “analyses” in order to print a human readable version of the analysis results. This is useful for debugging an analysis itself, as well as for other people to figure out how an analysis works. Use the opt -analyze argument to invoke this method.

The llvm::raw_ostream parameter specifies the stream to write the results on, and the Module parameter gives a pointer to the top level module of the program that has been analyzed. Note however that this pointer may be NULL in certain circumstances (such as calling the Pass::dump() from a debugger), so it should only be used to enhance debug output, it should not be depended on.

Specifying interactions between passes {#writing-an-llvm-pass-interaction}

One of the main responsibilities of the PassManager is to make sure that passes interact with each other correctly. Because PassManager tries to optimize the execution of passes <writing-an-llvm-pass-passmanager>{.interpreted-text role=“ref”} it must know how the passes interact with each other and what dependencies exist between the various passes. To track this, each pass can declare the set of passes that are required to be executed before the current pass, and the passes which are invalidated by the current pass.

Typically this functionality is used to require that analysis results are computed before your pass is run. Running arbitrary transformation passes can invalidate the computed analysis results, which is what the invalidation set specifies. If a pass does not implement the getAnalysisUsage <writing-an-llvm-pass-getAnalysisUsage>{.interpreted-text role=“ref”} method, it defaults to not having any prerequisite passes, and invalidating all other passes.

The getAnalysisUsage method {#writing-an-llvm-pass-getAnalysisUsage}

virtual void getAnalysisUsage(AnalysisUsage &Info) const;

By implementing the getAnalysisUsage method, the required and invalidated sets may be specified for your transformation. The implementation should fill in the AnalysisUsage object with information about which passes are required and not invalidated. To do this, a pass may call any of the following methods on the AnalysisUsage object:

The AnalysisUsage::addRequired<> and AnalysisUsage::addRequiredTransitive<> methods

If your pass requires a previous pass to be executed (an analysis for example), it can use one of these methods to arrange for it to be run before your pass. LLVM has many different types of analyses and passes that can be required, spanning the range from DominatorSet to BreakCriticalEdges. Requiring BreakCriticalEdges, for example, guarantees that there will be no critical edges in the CFG when your pass has been run.

Some analyses chain to other analyses to do their job. For example, an [AliasAnalysis <AliasAnalysis>]{.title-ref} implementation is required to chain <aliasanalysis-chaining>{.interpreted-text role=“ref”} to other alias analysis passes. In cases where analyses chain, the addRequiredTransitive method should be used instead of the addRequired method. This informs the PassManager that the transitively required pass should be alive as long as the requiring pass is.

The AnalysisUsage::addPreserved<> method

One of the jobs of the PassManager is to optimize how and when analyses are run. In particular, it attempts to avoid recomputing data unless it needs to. For this reason, passes are allowed to declare that they preserve (i.e., they don’t invalidate) an existing analysis if it’s available. For example, a simple constant folding pass would not modify the CFG, so it can’t possibly affect the results of dominator analysis. By default, all passes are assumed to invalidate all others.

The AnalysisUsage class provides several methods which are useful in certain circumstances that are related to addPreserved. In particular, the setPreservesAll method can be called to indicate that the pass does not modify the LLVM program at all (which is true for analyses), and the setPreservesCFG method can be used by transformations that change instructions in the program but do not modify the CFG or terminator instructions.

addPreserved is particularly useful for transformations like BreakCriticalEdges. This pass knows how to update a small set of loop and dominator related analyses if they exist, so it can preserve them, despite the fact that it hacks on the CFG.

Example implementations of getAnalysisUsage

// This example modifies the program, but does not modify the CFG
void LICM::getAnalysisUsage(AnalysisUsage &AU) const {
  AU.setPreservesCFG();
  AU.addRequired<LoopInfoWrapperPass>();
}

The getAnalysis<> and getAnalysisIfAvailable<> methods {#writing-an-llvm-pass-getAnalysis}

The Pass::getAnalysis<> method is automatically inherited by your class, providing you with access to the passes that you declared that you required with the getAnalysisUsage <writing-an-llvm-pass-getAnalysisUsage>{.interpreted-text role=“ref”} method. It takes a single template argument that specifies which pass class you want, and returns a reference to that pass. For example:

bool LICM::runOnFunction(Function &F) {
  LoopInfo &LI = getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
  //...
}

This method call returns a reference to the pass desired. You may get a runtime assertion failure if you attempt to get an analysis that you did not declare as required in your getAnalysisUsage <writing-an-llvm-pass-getAnalysisUsage>{.interpreted-text role=“ref”} implementation. This method can be called by your run* method implementation, or by any other local method invoked by your run* method.

A module level pass can use function level analysis info using this interface. For example:

bool ModuleLevelPass::runOnModule(Module &M) {
  //...
  DominatorTree &DT = getAnalysis<DominatorTree>(Func);
  //...
}

In above example, runOnFunction for DominatorTree is called by pass manager before returning a reference to the desired pass.

If your pass is capable of updating analyses if they exist (e.g., BreakCriticalEdges, as described above), you can use the getAnalysisIfAvailable method, which returns a pointer to the analysis if it is active. For example:

if (DominatorSet *DS = getAnalysisIfAvailable<DominatorSet>()) {
  // A DominatorSet is active.  This code will update it.
}

Pass Statistics

The Statistic class is designed to be an easy way to expose various success metrics from passes. These statistics are printed at the end of a run, when the -stats{.interpreted-text role=“option”} command line option is enabled on the command line. See the Statistics section <Statistic>{.interpreted-text role=“ref”} in the Programmer’s Manual for details.

What PassManager does {#writing-an-llvm-pass-passmanager}

The PassManager class takes a list of passes, ensures their prerequisites <writing-an-llvm-pass-interaction>{.interpreted-text role=“ref”} are set up correctly, and then schedules passes to run efficiently. All of the LLVM tools that run passes use the PassManager for execution of these passes.

The PassManager does two main things to try to reduce the execution time of a series of passes:

1. Share analysis results. The PassManager attempts to avoid recomputing analysis results as much as possible. This means keeping track of which analyses are available already, which analyses get invalidated, and which analyses are needed to be run for a pass. An important part of work is that the PassManager tracks the exact lifetime of all analysis results, allowing it to free memory <writing-an-llvm-pass-releaseMemory>{.interpreted-text role=“ref”} allocated to holding analysis results as soon as they are no longer needed.

2. Pipeline the execution of passes on the program. The PassManager attempts to get better cache and memory usage behavior out of a series of passes by pipelining the passes together. This means that, given a series of consecutive FunctionPass <writing-an-llvm-pass-FunctionPass>{.interpreted-text role=“ref”}, it will execute all of the FunctionPass <writing-an-llvm-pass-FunctionPass>{.interpreted-text role=“ref”} on the first function, then all of the FunctionPasses <writing-an-llvm-pass-FunctionPass>{.interpreted-text role=“ref”} on the second function, etc… until the entire program has been run through the passes.

   This improves the cache behavior of the compiler, because it is only touching the LLVM program representation for a single function at a time, instead of traversing the entire program. It reduces the memory consumption of compiler, because, for example, only one DominatorSet needs to be calculated at a time.

The effectiveness of the PassManager is influenced directly by how much information it has about the behaviors of the passes it is scheduling. For example, the “preserved” set is intentionally conservative in the face of an unimplemented getAnalysisUsage <writing-an-llvm-pass-getAnalysisUsage>{.interpreted-text role=“ref”} method. Not implementing when it should be implemented will have the effect of not allowing any analysis results to live across the execution of your pass.

The PassManager class exposes a --debug-pass command line options that is useful for debugging pass execution, seeing how things work, and diagnosing when you should be preserving more analyses than you currently are. (To get information about all of the variants of the --debug-pass option, just type “llc -help-hidden”).

By using the —debug-pass=Structure option, for example, we can see inspect the default optimization pipelines, e.g. (the output has been trimmed):

$ llc -mtriple=arm64-- -O3 -debug-pass=Structure file.ll > /dev/null
(...)
ModulePass Manager
Pre-ISel Intrinsic Lowering
FunctionPass Manager
  Expand large div/rem
  Expand large fp convert
  Expand Atomic instructions
SVE intrinsics optimizations
  FunctionPass Manager
    Dominator Tree Construction
FunctionPass Manager
  Simplify the CFG
  Dominator Tree Construction
  Natural Loop Information
  Canonicalize natural loops
(...)

The releaseMemory method {#writing-an-llvm-pass-releaseMemory}

virtual void releaseMemory();

The PassManager automatically determines when to compute analysis results, and how long to keep them around for. Because the lifetime of the pass object itself is effectively the entire duration of the compilation process, we need some way to free analysis results when they are no longer useful. The releaseMemory virtual method is the way to do this.

If you are writing an analysis or any other pass that retains a significant amount of state (for use by another pass which “requires” your pass and uses the getAnalysis <writing-an-llvm-pass-getAnalysis>{.interpreted-text role=“ref”} method) you should implement releaseMemory to, well, release the memory allocated to maintain this internal state. This method is called after the run* method for the class, before the next call of run* in your pass.

Registering dynamically loaded passes

Size matters when constructing production quality tools using LLVM, both for the purposes of distribution, and for regulating the resident code size when running on the target system. Therefore, it becomes desirable to selectively use some passes, while omitting others and maintain the flexibility to change configurations later on. You want to be able to do all this, and, provide feedback to the user. This is where pass registration comes into play.

The fundamental mechanisms for pass registration are the MachinePassRegistry class and subclasses of MachinePassRegistryNode.

An instance of MachinePassRegistry is used to maintain a list of MachinePassRegistryNode objects. This instance maintains the list and communicates additions and deletions to the command line interface.

An instance of MachinePassRegistryNode subclass is used to maintain information provided about a particular pass. This information includes the command line name, the command help string and the address of the function used to create an instance of the pass. A global static constructor of one of these instances registers with a corresponding MachinePassRegistry, the static destructor unregisters. Thus a pass that is statically linked in the tool will be registered at start up. A dynamically loaded pass will register on load and unregister at unload.

Using existing registries

There are predefined registries to track instruction scheduling (RegisterScheduler) and register allocation (RegisterRegAlloc) machine passes. Here we will describe how to register a register allocator machine pass.

Implement your register allocator machine pass. In your register allocator .cpp file add the following include:

#include "llvm/CodeGen/RegAllocRegistry.h"

Also in your register allocator .cpp file, define a creator function in the form:

FunctionPass *createMyRegisterAllocator() {
  return new MyRegisterAllocator();
}

Note that the signature of this function should match the type of RegisterRegAlloc::FunctionPassCtor. In the same file add the “installing” declaration, in the form:

static RegisterRegAlloc myRegAlloc("myregalloc",
                                   "my register allocator help string",
                                   createMyRegisterAllocator);

Note the two spaces prior to the help string produces a tidy result on the -help{.interpreted-text role=“option”} query.

$ llc -help
  ...
  -regalloc                    - Register allocator to use (default=linearscan)
    =linearscan                -   linear scan register allocator
    =local                     -   local register allocator
    =simple                    -   simple register allocator
    =myregalloc                -   my register allocator help string
  ...

And that’s it. The user is now free to use -regalloc=myregalloc as an option. Registering instruction schedulers is similar except use the RegisterScheduler class. Note that the RegisterScheduler::FunctionPassCtor is significantly different from RegisterRegAlloc::FunctionPassCtor.

To force the load/linking of your register allocator into the llc{.interpreted-text role=“program”}/lli{.interpreted-text role=“program”} tools, add your creator function’s global declaration to Passes.h and add a “pseudo” call line to llvm/Codegen/LinkAllCodegenComponents.h.

Creating new registries

The easiest way to get started is to clone one of the existing registries; we recommend llvm/CodeGen/RegAllocRegistry.h. The key things to modify are the class name and the FunctionPassCtor type.

Then you need to declare the registry. Example: if your pass registry is RegisterMyPasses then define:

MachinePassRegistry<RegisterMyPasses::FunctionPassCtor> RegisterMyPasses::Registry;

And finally, declare the command line option for your passes. Example:

cl::opt<RegisterMyPasses::FunctionPassCtor, false,
        RegisterPassParser<RegisterMyPasses> >
MyPassOpt("mypass",
          cl::init(&createDefaultMyPass),
          cl::desc("my pass option help"));

Here the command option is “mypass”, with createDefaultMyPass as the default creator.

Using GDB with dynamically loaded passes

Unfortunately, using GDB with dynamically loaded passes is not as easy as it should be. First of all, you can’t set a breakpoint in a shared object that has not been loaded yet, and second of all there are problems with inlined functions in shared objects. Here are some suggestions to debugging your pass with GDB.

For sake of discussion, I’m going to assume that you are debugging a transformation invoked by opt{.interpreted-text role=“program”}, although nothing described here depends on that.

Setting a breakpoint in your pass

First thing you do is start gdb on the opt process:

$ gdb opt
GNU gdb 5.0
Copyright 2000 Free Software Foundation, Inc.
GDB is free software, covered by the GNU General Public License, and you are
welcome to change it and/or distribute copies of it under certain conditions.
Type "show copying" to see the conditions.
There is absolutely no warranty for GDB.  Type "show warranty" for details.
This GDB was configured as "sparc-sun-solaris2.6"...
(gdb)

Note that opt{.interpreted-text role=“program”} has a lot of debugging information in it, so it takes time to load. Be patient. Since we cannot set a breakpoint in our pass yet (the shared object isn’t loaded until runtime), we must execute the process, and have it stop before it invokes our pass, but after it has loaded the shared object. The most foolproof way of doing this is to set a breakpoint in PassManager::run and then run the process with the arguments you want:

$ (gdb) break llvm::PassManager::run
Breakpoint 1 at 0x2413bc: file Pass.cpp, line 70.
(gdb) run test.bc -load $(LLVMTOP)/llvm/Debug+Asserts/lib/[libname].so -[passoption]
Starting program: opt test.bc -load $(LLVMTOP)/llvm/Debug+Asserts/lib/[libname].so -[passoption]
Breakpoint 1, PassManager::run (this=0xffbef174, M=@0x70b298) at Pass.cpp:70
70      bool PassManager::run(Module &M) { return PM->run(M); }
(gdb)

Once the opt{.interpreted-text role=“program”} stops in the PassManager::run method you are now free to set breakpoints in your pass so that you can trace through execution or do other standard debugging stuff.

Miscellaneous Problems

Once you have the basics down, there are a couple of problems that GDB has, some with solutions, some without.

• Inline functions have bogus stack information. In general, GDB does a pretty good job getting stack traces and stepping through inline functions. When a pass is dynamically loaded however, it somehow completely loses this capability. The only solution I know of is to de-inline a function (move it from the body of a class to a .cpp file).
• Restarting the program breaks breakpoints. After following the information above, you have succeeded in getting some breakpoints planted in your pass. Next thing you know, you restart the program (i.e., you type “run” again), and you start getting errors about breakpoints being unsettable. The only way I have found to “fix” this problem is to delete the breakpoints that are already set in your pass, run the program, and re-set the breakpoints once execution stops in PassManager::run.

Hopefully these tips will help with common case debugging situations. If you’d like to contribute some tips of your own, just contact Chris.