Writing an LLVM Pass (legacy PM version) — LLVM 21.0.0git documentation (original) (raw)
- Introduction — What is a pass?
- Pass classes and requirements
- The ImmutablePass class
- The ModulePass class
* The runOnModule method - The CallGraphSCCPass class
* The doInitialization(CallGraph &) method
* The runOnSCC method
* The doFinalization(CallGraph &) method - The FunctionPass class
* The doInitialization(Module &) method
* The runOnFunction method
* The doFinalization(Module &) method - The LoopPass class
* The doInitialization(Loop *, LPPassManager &) method
* The runOnLoop method
* The doFinalization() method - The RegionPass class
* The doInitialization(Region *, RGPassManager &) method
* The runOnRegion method
* The doFinalization() method - The MachineFunctionPass class
* The runOnMachineFunction(MachineFunction &MF) method - Pass registration
* The print method - Specifying interactions between passes
* The getAnalysisUsage method
* The AnalysisUsage::addRequired<> and AnalysisUsage::addRequiredTransitive<> methods
* The AnalysisUsage::addPreserved<> method
* Example implementations of getAnalysisUsage
* The getAnalysis<> and getAnalysisIfAvailable<> methods
- Pass Statistics
- Registering dynamically loaded passes
Introduction — What is a pass?¶
Warning
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 Writing an LLVM Pass andUsing the New Pass Manager.
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 , CallGraphSCCPass, FunctionPass , or LoopPass, or RegionPass 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¶
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.
ImmutablePass
es never invalidate other transformations, are never invalidated, and are never “run”.
The ModulePass class¶
The ModulePass class is the most general of all superclasses that you can use. Deriving fromModulePass
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 thegetAnalysis
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 andfalse
otherwise.
The CallGraphSCCPass class¶
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 CallGraphSCCPass
es. If your pass meets the requirements outlined below, and doesn’t meet the requirements of aFunctionPass, you should derive fromCallGraphSCCPass
.
TODO
: explain briefly what SCC, Tarjan’s algo, and B-U mean.
To be explicit, CallGraphSCCPass subclasses are:
- … not allowed to inspect or modify any
Function
s other than those in the current SCC and the direct callers and direct callees of the SCC. - … required to preserve the current
CallGraph
object, updating it to reflect any changes made to the program. - … not allowed to add or remove SCC’s from the current Module, though they may change the contents of an SCC.
- … allowed to add or remove global variables from the current Module.
- … allowed to maintain state across invocations of runOnSCC (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, orfalse
if they didn’t.
The doInitialization(CallGraph &) method¶
virtual bool doInitialization(CallGraph &CG);
The doInitialization
method is allowed to do most of the things thatCallGraphSCCPass
es 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¶
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 for every SCC in the program being compiled.
The FunctionPass class¶
In contrast to ModulePass
subclasses, FunctionPass subclasses do have a predictable, local behavior that can be expected by the system. AllFunctionPass
execute on each function in the program independent of all of the other functions in the program. FunctionPass
es do not require that they are executed in a particular order, and FunctionPass
es do not modify external functions.
To be explicit, FunctionPass
subclasses are not allowed to:
- Inspect or modify a
Function
other than the one currently being processed. - Add or remove
Function
s from the currentModule
. - Add or remove global variables from the current
Module
. - Maintain state across invocations of runOnFunction (including global data).
Implementing a FunctionPass
is usually straightforward. FunctionPass
es 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¶
virtual bool doInitialization(Module &M);
The doInitialization
method is allowed to do most of the things thatFunctionPass
es 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 dependentmalloc()
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¶
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¶
virtual bool doFinalization(Module &M);
The doFinalization
method is an infrequently used method that is called when the pass framework has finished calling runOnFunction for every function in the program being compiled.
The LoopPass class¶
All LoopPass
execute on each loop 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.LoopPass
es 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. ThedoInitialization
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¶
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 for every loop in the program being compiled.
The RegionPass class¶
RegionPass
is similar to LoopPass, 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 theRGPassManager
interface. You may override three virtual methods ofRegionPass
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. ThedoInitialization
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¶
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 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 byTargetMachine::addPassesToEmitFile
and similar routines, so they cannot generally be run from the opt or bugpoint commands.
A MachineFunctionPass
is also a FunctionPass
, so all the restrictions that apply to a FunctionPass
also apply to it. MachineFunctionPass
es also have additional restrictions. In particular, MachineFunctionPass
es are not allowed to do any of the following:
- Modify or create any LLVM IR
Instruction
s,BasicBlock
s,Argument
s,Function
s,GlobalVariable
s,GlobalAlias
es, orModule
s. - Modify a
MachineFunction
other than the one currently being processed. - Maintain state across invocations of runOnMachineFunction (including global data).
The runOnMachineFunction(MachineFunction &MF) method¶
virtual bool runOnMachineFunction(MachineFunction &MF) = 0;
runOnMachineFunction
can be considered the main entry point of aMachineFunctionPass
; that is, you should override this method to do the work of your MachineFunctionPass
.
The runOnMachineFunction
method is called on every MachineFunction
in aModule
, 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, useMachineFunction
’s getFunction()
accessor method — but remember, you may not modify the LLVM Function
or its contents from aMachineFunctionPass
.
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 output of programs, as well as for debug output generated by the –debug-pass 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¶
One of the main responsibilities of the PassManager
is to make sure that passes interact with each other correctly. Because PassManager
tries tooptimize the execution of passes 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 method, it defaults to not having any prerequisite passes, and invalidating all other passes.
The getAnalysisUsage method¶
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
. RequiringBreakCriticalEdges
, 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, anAliasAnalysis implementation is required to chain 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, thesetPreservesAll
method can be called to indicate that the pass does not modify the LLVM program at all (which is true for analyses), and thesetPreservesCFG
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 likeBreakCriticalEdges
. 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(); }
The getAnalysis<> and getAnalysisIfAvailable<> methods¶
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 getAnalysisUsagemethod. 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().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 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(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 thegetAnalysisIfAvailable
method, which returns a pointer to the analysis if it is active. For example:
if (DominatorSet *DS = getAnalysisIfAvailable()) { // 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 -statscommand line option is enabled on the command line. See the Statistics section in the Programmer’s Manual for details.
What PassManager does¶
The PassManager class takes a list of passes, ensures their prerequisitesare 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:
- 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 thePassManager
tracks the exact lifetime of all analysis results, allowing it to free memory allocated to holding analysis results as soon as they are no longer needed. - 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, it will execute all of the FunctionPass on the first function, then all of theFunctionPasses 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 getAnalysisUsagemethod. 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 fp 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¶
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. ThereleaseMemory
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 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 theMachinePassRegistry
class and subclasses of MachinePassRegistryNode
.
An instance of MachinePassRegistry
is used to maintain a list ofMachinePassRegistryNode
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 ofRegisterRegAlloc::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 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 theRegisterScheduler
class. Note that theRegisterScheduler::FunctionPassCtor
is significantly different fromRegisterRegAlloc::FunctionPassCtor
.
To force the load/linking of your register allocator into thellc/lli tools, add your creator function’s global declaration to Passes.h
and add a “pseudo” call line tollvm/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 isRegisterMyPasses
then define:
MachinePassRegistryRegisterMyPasses::FunctionPassCtor RegisterMyPasses::Registry;
And finally, declare the command line option for your passes. Example:
cl::opt<RegisterMyPasses::FunctionPassCtor, false, RegisterPassParser > 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, 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 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 inPassManager::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 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 inPassManager::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.