This document serves as a high level summary of the optimization features that LLVM provides. Optimizations are implemented as Passes that traverse some portion of a program to either collect information or transform the program. The table below divides the passes that LLVM provides into three categories. Analysis passes compute information that other passes can use or for debugging or program visualization purposes. Transform passes can use (or invalidate) the analysis passes. Transform passes all mutate the program in some way. Utility passes provides some utility but don’t otherwise fit categorization. For example passes to extract functions to bitcode or write a module to bitcode are neither analysis nor transform passes. The table of contents above provides a quick summary of each pass and links to the more complete pass description later in the document.
This section describes the LLVM Analysis Passes.
This is a simple N^2 alias analysis accuracy evaluator. Basically, for each function in the program, it simply queries to see how the alias analysis implementation answers alias queries between each pair of pointers in the function.
This is inspired and adapted from code by: Naveen Neelakantam, Francesco Spadini, and Wojciech Stryjewski.
A basic alias analysis pass that implements identities (two different globals cannot alias, etc), but does no stateful analysis.
Yet to be written.
A pass which can be used to count how many alias queries are being made and how the alias analysis implementation being used responds.
Dependence analysis framework, which is used to detect dependences in memory accesses.
This simple pass checks alias analysis users to ensure that if they create a new value, they do not query AA without informing it of the value. It acts as a shim over any other AA pass you want.
Yes keeping track of every value in the program is expensive, but this is a debugging pass.
This pass is a simple dominator construction algorithm for finding forward dominator frontiers.
This pass is a simple dominator construction algorithm for finding forward dominators.
This pass, only available in opt, prints the call graph into a .dot graph. This graph can then be processed with the “dot” tool to convert it to postscript or some other suitable format.
This pass, only available in opt, prints the control flow graph into a .dot graph. This graph can then be processed with the dot tool to convert it to postscript or some other suitable format.
This pass, only available in opt, prints the control flow graph into a .dot graph, omitting the function bodies. This graph can then be processed with the dot tool to convert it to postscript or some other suitable format.
This pass, only available in opt, prints the dominator tree into a .dot graph. This graph can then be processed with the dot tool to convert it to postscript or some other suitable format.
This pass, only available in opt, prints the dominator tree into a .dot graph, omitting the function bodies. This graph can then be processed with the dot tool to convert it to postscript or some other suitable format.
This pass, only available in opt, prints the post dominator tree into a .dot graph. This graph can then be processed with the dot tool to convert it to postscript or some other suitable format.
This pass, only available in opt, prints the post dominator tree into a .dot graph, omitting the function bodies. This graph can then be processed with the dot tool to convert it to postscript or some other suitable format.
This simple pass provides alias and mod/ref information for global values that do not have their address taken, and keeps track of whether functions read or write memory (are “pure”). For this simple (but very common) case, we can provide pretty accurate and useful information.
This pass collects the count of all instructions and reports them.
This analysis calculates and represents the interval partition of a function, or a preexisting interval partition.
In this way, the interval partition may be used to reduce a flow graph down to its degenerate single node interval partition (unless it is irreducible).
Bookkeeping for “interesting” users of expressions computed from induction variables.
Interface for lazy computation of value constraint information.
LibCall Alias Analysis.
This pass statically checks for common and easily-identified constructs which produce undefined or likely unintended behavior in LLVM IR.
It is not a guarantee of correctness, in two ways. First, it isn’t comprehensive. There are checks which could be done statically which are not yet implemented. Some of these are indicated by TODO comments, but those aren’t comprehensive either. Second, many conditions cannot be checked statically. This pass does no dynamic instrumentation, so it can’t check for all possible problems.
Another limitation is that it assumes all code will be executed. A store through a null pointer in a basic block which is never reached is harmless, but this pass will warn about it anyway.
Optimization passes may make conditions that this pass checks for more or less obvious. If an optimization pass appears to be introducing a warning, it may be that the optimization pass is merely exposing an existing condition in the code.
This code may be run before instcombine. In many cases, instcombine checks for the same kinds of things and turns instructions with undefined behavior into unreachable (or equivalent). Because of this, this pass makes some effort to look through bitcasts and so on.
This analysis is used to identify natural loops and determine the loop depth of various nodes of the CFG. Note that the loops identified may actually be several natural loops that share the same header node... not just a single natural loop.
An analysis that determines, for a given memory operation, what preceding memory operations it depends on. It builds on alias analysis information, and tries to provide a lazy, caching interface to a common kind of alias information query.
This pass decodes the debug info metadata in a module and prints in a (sufficiently-prepared-) human-readable form.
For example, run this pass from opt along with the -analyze option, and it’ll print to standard output.
This pass is a simple post-dominator construction algorithm for finding post-dominator frontiers.
This pass is a simple post-dominator construction algorithm for finding post-dominators.
Yet to be written.
This pass, only available in opt, prints the call graph to standard error in a human-readable form.
This pass, only available in opt, prints the SCCs of the call graph to standard error in a human-readable form.
This pass, only available in opt, printsthe SCCs of each function CFG to standard error in a human-readable fom.
Dominator Info Printer.
This pass, only available in opt, prints out call sites to external functions that are called with constant arguments. This can be useful when looking for standard library functions we should constant fold or handle in alias analyses.
The PrintFunctionPass class is designed to be pipelined with other FunctionPasses, and prints out the functions of the module as they are processed.
This pass simply prints out the entire module when it is executed.
This pass is used to seek out all of the types in use by the program. Note that this analysis explicitly does not include types only used by the symbol table.
The RegionInfo pass detects single entry single exit regions in a function, where a region is defined as any subgraph that is connected to the remaining graph at only two spots. Furthermore, an hierarchical region tree is built.
The ScalarEvolution analysis can be used to analyze and catagorize scalar expressions in loops. It specializes in recognizing general induction variables, representing them with the abstract and opaque SCEV class. Given this analysis, trip counts of loops and other important properties can be obtained.
This analysis is primarily useful for induction variable substitution and strength reduction.
Simple alias analysis implemented in terms of ScalarEvolution queries.
This differs from traditional loop dependence analysis in that it tests for dependencies within a single iteration of a loop, rather than dependencies between different iterations.
ScalarEvolution has a more complete understanding of pointer arithmetic than BasicAliasAnalysis‘ collection of ad-hoc analyses.
Provides other passes access to information on how the size and alignment required by the target ABI for various data types.
This section describes the LLVM Transform Passes.
ADCE aggressively tries to eliminate code. This pass is similar to DCE but it assumes that values are dead until proven otherwise. This is similar to SCCP, except applied to the liveness of values.
A custom inliner that handles only functions that are marked as “always inline”.
This pass promotes “by reference” arguments to be “by value” arguments. In practice, this means looking for internal functions that have pointer arguments. If it can prove, through the use of alias analysis, that an argument is only loaded, then it can pass the value into the function instead of the address of the value. This can cause recursive simplification of code and lead to the elimination of allocas (especially in C++ template code like the STL).
This pass also handles aggregate arguments that are passed into a function, scalarizing them if the elements of the aggregate are only loaded. Note that it refuses to scalarize aggregates which would require passing in more than three operands to the function, because passing thousands of operands for a large array or structure is unprofitable!
Note that this transformation could also be done for arguments that are only stored to (returning the value instead), but does not currently. This case would be best handled when and if LLVM starts supporting multiple return values from functions.
This pass combines instructions inside basic blocks to form vector instructions. It iterates over each basic block, attempting to pair compatible instructions, repeating this process until no additional pairs are selected for vectorization. When the outputs of some pair of compatible instructions are used as inputs by some other pair of compatible instructions, those pairs are part of a potential vectorization chain. Instruction pairs are only fused into vector instructions when they are part of a chain longer than some threshold length. Moreover, the pass attempts to find the best possible chain for each pair of compatible instructions. These heuristics are intended to prevent vectorization in cases where it would not yield a performance increase of the resulting code.
This pass is a very simple profile guided basic block placement algorithm. The idea is to put frequently executed blocks together at the start of the function and hopefully increase the number of fall-through conditional branches. If there is no profile information for a particular function, this pass basically orders blocks in depth-first order.
Break all of the critical edges in the CFG by inserting a dummy basic block. It may be “required” by passes that cannot deal with critical edges. This transformation obviously invalidates the CFG, but can update forward dominator (set, immediate dominators, tree, and frontier) information.
This pass munges the code in the input function to better prepare it for SelectionDAG-based code generation. This works around limitations in its basic-block-at-a-time approach. It should eventually be removed.
Merges duplicate global constants together into a single constant that is shared. This is useful because some passes (i.e., TraceValues) insert a lot of string constants into the program, regardless of whether or not an existing string is available.
This pass implements constant propagation and merging. It looks for instructions involving only constant operands and replaces them with a constant value instead of an instruction. For example:
add i32 1, 2
becomes
i32 3
NOTE: this pass has a habit of making definitions be dead. It is a good idea to run a Dead Instruction Elimination pass sometime after running this pass.
Dead code elimination is similar to dead instruction elimination, but it rechecks instructions that were used by removed instructions to see if they are newly dead.
This pass deletes dead arguments from internal functions. Dead argument elimination removes arguments which are directly dead, as well as arguments only passed into function calls as dead arguments of other functions. This pass also deletes dead arguments in a similar way.
This pass is often useful as a cleanup pass to run after aggressive interprocedural passes, which add possibly-dead arguments.
This pass is used to cleanup the output of GCC. It eliminate names for types that are unused in the entire translation unit, using the find used types pass.
Dead instruction elimination performs a single pass over the function, removing instructions that are obviously dead.
A trivial dead store elimination that only considers basic-block local redundant stores.
A simple interprocedural pass which walks the call-graph, looking for functions which do not access or only read non-local memory, and marking them readnone/readonly. In addition, it marks function arguments (of pointer type) “nocapture” if a call to the function does not create any copies of the pointer value that outlive the call. This more or less means that the pointer is only dereferenced, and not returned from the function or stored in a global. This pass is implemented as a bottom-up traversal of the call-graph.
This transform is designed to eliminate unreachable internal globals from the program. It uses an aggressive algorithm, searching out globals that are known to be alive. After it finds all of the globals which are needed, it deletes whatever is left over. This allows it to delete recursive chunks of the program which are unreachable.
This pass transforms simple global variables that never have their address taken. If obviously true, it marks read/write globals as constant, deletes variables only stored to, etc.
This pass performs global value numbering to eliminate fully and partially redundant instructions. It also performs redundant load elimination.
This transformation analyzes and transforms the induction variables (and computations derived from them) into simpler forms suitable for subsequent analysis and transformation.
This transformation makes the following changes to each loop with an identifiable induction variable:
If the trip count of a loop is computable, this pass also makes the following changes:
The exit condition for the loop is canonicalized to compare the induction value against the exit value. This turns loops like:
for (i = 7; i*i < 1000; ++i)
into
for (i = 0; i != 25; ++i)
Any use outside of the loop of an expression derived from the indvar is changed to compute the derived value outside of the loop, eliminating the dependence on the exit value of the induction variable. If the only purpose of the loop is to compute the exit value of some derived expression, this transformation will make the loop dead.
This transformation should be followed by strength reduction after all of the desired loop transformations have been performed. Additionally, on targets where it is profitable, the loop could be transformed to count down to zero (the “do loop” optimization).
Bottom-up inlining of functions into callees.
Combine instructions to form fewer, simple instructions. This pass does not modify the CFG. This pass is where algebraic simplification happens.
This pass combines things like:
%Y = add i32 %X, 1
%Z = add i32 %Y, 1
into:
%Z = add i32 %X, 2
This is a simple worklist driven algorithm.
This pass guarantees that the following canonicalizations are performed on the program:
This pass can also simplify calls to specific well-known function calls (e.g. runtime library functions). For example, a call exit(3) that occurs within the main() function can be transformed into simply return 3. Whether or not library calls are simplified is controlled by the -functionattrs pass and LLVM’s knowledge of library calls on different targets.
This pass loops over all of the functions in the input module, looking for a main function. If a main function is found, all other functions and all global variables with initializers are marked as internal.
This pass implements an extremely simple interprocedural constant propagation pass. It could certainly be improved in many different ways, like using a worklist. This pass makes arguments dead, but does not remove them. The existing dead argument elimination pass should be run after this to clean up the mess.
An interprocedural variant of Sparse Conditional Constant Propagation.
Jump threading tries to find distinct threads of control flow running through a basic block. This pass looks at blocks that have multiple predecessors and multiple successors. If one or more of the predecessors of the block can be proven to always cause a jump to one of the successors, we forward the edge from the predecessor to the successor by duplicating the contents of this block.
An example of when this can occur is code like this:
if () { ...
X = 4;
}
if (X < 3) {
In this case, the unconditional branch at the end of the first if can be revectored to the false side of the second if.
This pass transforms loops by placing phi nodes at the end of the loops for all values that are live across the loop boundary. For example, it turns the left into the right code:
for (...) for (...)
if (c) if (c)
X1 = ... X1 = ...
else else
X2 = ... X2 = ...
X3 = phi(X1, X2) X3 = phi(X1, X2)
... = X3 + 4 X4 = phi(X3)
... = X4 + 4
This is still valid LLVM; the extra phi nodes are purely redundant, and will be trivially eliminated by InstCombine. The major benefit of this transformation is that it makes many other loop optimizations, such as LoopUnswitching, simpler.
This pass performs loop invariant code motion, attempting to remove as much code from the body of a loop as possible. It does this by either hoisting code into the preheader block, or by sinking code to the exit blocks if it is safe. This pass also promotes must-aliased memory locations in the loop to live in registers, thus hoisting and sinking “invariant” loads and stores.
This pass uses alias analysis for two purposes:
Moving loop invariant loads and calls out of loops. If we can determine that a load or call inside of a loop never aliases anything stored to, we can hoist it or sink it like any other instruction.
Scalar Promotion of Memory. If there is a store instruction inside of the loop, we try to move the store to happen AFTER the loop instead of inside of the loop. This can only happen if a few conditions are true:
If these conditions are true, we can promote the loads and stores in the loop of the pointer to use a temporary alloca’d variable. We then use the mem2reg functionality to construct the appropriate SSA form for the variable.
This file implements the Dead Loop Deletion Pass. This pass is responsible for eliminating loops with non-infinite computable trip counts that have no side effects or volatile instructions, and do not contribute to the computation of the function’s return value.
A pass wrapper around the ExtractLoop() scalar transformation to extract each top-level loop into its own new function. If the loop is the only loop in a given function, it is not touched. This is a pass most useful for debugging via bugpoint.
Similar to Extract loops into new functions, this pass extracts one natural loop from the program into a function if it can. This is used by bugpoint.
This pass performs a strength reduction on array references inside loops that have as one or more of their components the loop induction variable. This is accomplished by creating a new value to hold the initial value of the array access for the first iteration, and then creating a new GEP instruction in the loop to increment the value by the appropriate amount.
A simple loop rotation transformation.
This pass performs several transformations to transform natural loops into a simpler form, which makes subsequent analyses and transformations simpler and more effective.
Loop pre-header insertion guarantees that there is a single, non-critical entry edge from outside of the loop to the loop header. This simplifies a number of analyses and transformations, such as LICM.
Loop exit-block insertion guarantees that all exit blocks from the loop (blocks which are outside of the loop that have predecessors inside of the loop) only have predecessors from inside of the loop (and are thus dominated by the loop header). This simplifies transformations such as store-sinking that are built into LICM.
This pass also guarantees that loops will have exactly one backedge.
Note that the simplifycfg pass will clean up blocks which are split out but end up being unnecessary, so usage of this pass should not pessimize generated code.
This pass obviously modifies the CFG, but updates loop information and dominator information.
This pass implements a simple loop unroller. It works best when loops have been canonicalized by the indvars pass, allowing it to determine the trip counts of loops easily.
This pass transforms loops that contain branches on loop-invariant conditions to have multiple loops. For example, it turns the left into the right code:
for (...) if (lic)
A for (...)
if (lic) A; B; C
B else
C for (...)
A; C
This can increase the size of the code exponentially (doubling it every time a loop is unswitched) so we only unswitch if the resultant code will be smaller than a threshold.
This pass expects LICM to be run before it to hoist invariant conditions out of the loop, to make the unswitching opportunity obvious.
This pass lowers atomic intrinsics to non-atomic form for use in a known non-preemptible environment.
The pass does not verify that the environment is non-preemptible (in general this would require knowledge of the entire call graph of the program including any libraries which may not be available in bitcode form); it simply lowers every atomic intrinsic.
This transformation is designed for use by code generators which do not yet support stack unwinding. This pass converts invoke instructions to call instructions, so that any exception-handling landingpad blocks become dead code (which can be removed by running the -simplifycfg pass afterwards).
Rewrites switch instructions with a sequence of branches, which allows targets to get away with not implementing the switch instruction until it is convenient.
This file promotes memory references to be register references. It promotes alloca instructions which only have loads and stores as uses. An alloca is transformed by using dominator frontiers to place phi nodes, then traversing the function in depth-first order to rewrite loads and stores as appropriate. This is just the standard SSA construction algorithm to construct “pruned” SSA form.
This pass performs various transformations related to eliminating memcpy calls, or transforming sets of stores into memsets.
This pass looks for equivalent functions that are mergable and folds them.
Total-ordering is introduced among the functions set: we define comparison that answers for every two functions which of them is greater. It allows to arrange functions into the binary tree.
For every new function we check for equivalent in tree.
If equivalent exists we fold such functions. If both functions are overridable, we move the functionality into a new internal function and leave two overridable thunks to it.
If there is no equivalent, then we add this function to tree.
Lookup routine has O(log(n)) complexity, while whole merging process has complexity of O(n*log(n)).
Read this article for more details.
Ensure that functions have at most one ret instruction in them. Additionally, it keeps track of which node is the new exit node of the CFG.
This pass performs partial inlining, typically by inlining an if statement that surrounds the body of the function.
This file implements a simple interprocedural pass which walks the call-graph, turning invoke instructions into call instructions if and only if the callee cannot throw an exception. It implements this as a bottom-up traversal of the call-graph.
This pass reassociates commutative expressions in an order that is designed to promote better constant propagation, GCSE, LICM, PRE, etc.
For example: 4 + (x + 5) ⇒ x + (4 + 5)
In the implementation of this algorithm, constants are assigned rank = 0, function arguments are rank = 1, and other values are assigned ranks corresponding to the reverse post order traversal of current function (starting at 2), which effectively gives values in deep loops higher rank than values not in loops.
This file demotes all registers to memory references. It is intended to be the inverse of mem2reg. By converting to load instructions, the only values live across basic blocks are alloca instructions and load instructions before phi nodes. It is intended that this should make CFG hacking much easier. To make later hacking easier, the entry block is split into two, such that all introduced alloca instructions (and nothing else) are in the entry block.
The well-known scalar replacement of aggregates transformation. This transform breaks up alloca instructions of aggregate type (structure or array) into individual alloca instructions for each member if possible. Then, if possible, it transforms the individual alloca instructions into nice clean scalar SSA form.
Sparse conditional constant propagation and merging, which can be summarized as:
Note that this pass has a habit of making definitions be dead. It is a good idea to run a DCE pass sometime after running this pass.
Performs dead code elimination and basic block merging. Specifically:
This pass moves instructions into successor blocks, when possible, so that they aren’t executed on paths where their results aren’t needed.
Performs code stripping. This transformation can delete:
Note that this transformation makes code much less readable, so it should only be used in situations where the strip utility would be used, such as reducing code size or making it harder to reverse engineer code.
performs code stripping. this transformation can delete:
note that this transformation makes code much less readable, so it should only be used in situations where the strip utility would be used, such as reducing code size or making it harder to reverse engineer code.
This pass loops over all of the functions in the input module, looking for dead declarations and removes them. Dead declarations are declarations of functions for which no implementation is available (i.e., declarations for unused library functions).
This pass implements code stripping. Specifically, it can delete:
Note that this transformation makes code much less readable, so it should only be used in situations where the ‘strip’ utility would be used, such as reducing code size or making it harder to reverse engineer code.
This pass implements code stripping. Specifically, it can delete:
Note that this transformation makes code much less readable, so it should only be used in situations where the ‘strip’ utility would be used, such as reducing code size or making it harder to reverse engineer code.
This file transforms calls of the current function (self recursion) followed by a return instruction with a branch to the entry of the function, creating a loop. This pass also implements the following extensions to the basic algorithm:
This section describes the LLVM Utility Passes.
Same as dead argument elimination, but deletes arguments to functions which are external. This is only for use by bugpoint.
This pass is used by bugpoint to extract all blocks from the module into their own functions.
This is a little utility pass that gives instructions names, this is mostly useful when diffing the effect of an optimization because deleting an unnamed instruction can change all other instruction numbering, making the diff very noisy.
Verifies an LLVM IR code. This is useful to run after an optimization which is undergoing testing. Note that llvm-as verifies its input before emitting bitcode, and also that malformed bitcode is likely to make LLVM crash. All language front-ends are therefore encouraged to verify their output before performing optimizing transformations.
Note that this does not provide full security verification (like Java), but instead just tries to ensure that code is well-formed.
Displays the control flow graph using the GraphViz tool.
Displays the control flow graph using the GraphViz tool, but omitting function bodies.
Displays the dominator tree using the GraphViz tool.
Displays the dominator tree using the GraphViz tool, but omitting function bodies.
Displays the post dominator tree using the GraphViz tool.
Displays the post dominator tree using the GraphViz tool, but omitting function bodies.