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@ -10,84 +10,71 @@ Introduction
Sometimes code contains equal functions, or functions that does exactly the same
thing even though they are non-equal on the IR level (e.g.: multiplication on 2
and 'shl 1'). It could happen due to several reasons: mainly, the usage of
templates and automatic code generators. Though, sometimes user itself could
templates and automatic code generators. Though, sometimes the user itself could
write the same thing twice :-)
The main purpose of this pass is to recognize such functions and merge them.
Why would I want to read this document?
---------------------------------------
Document is the extension to pass comments and describes the pass logic. It
describes algorithm that is used in order to compare functions, it also
explains how we could combine equal functions correctly, keeping module valid.
This document is the extension to pass comments and describes the pass logic. It
describes the algorithm that is used in order to compare functions and
explains how we could combine equal functions correctly to keep the module
valid.
Material is brought in top-down form, so reader could start learn pass from
ideas and end up with low-level algorithm details, thus preparing him for
reading the sources.
Material is brought in a top-down form, so the reader could start to learn pass
from high level ideas and end with low-level algorithm details, thus preparing
him or her for reading the sources.
So main goal is do describe algorithm and logic here; the concept. This document
is good for you, if you *don't want* to read the source code, but want to
understand pass algorithms. Author tried not to repeat the source-code and
cover only common cases, and thus avoid cases when after minor code changes we
need to update this document.
The main goal is to describe the algorithm and logic here and the concept. If
you *don't want* to read the source code, but want to understand pass
algorithms, this document is good for you. The author tries not to repeat the
source-code and covers only common cases to avoid the cases of needing to
update this document after any minor code changes.
What should I know to be able to follow along with this document?
-----------------------------------------------------------------
Reader should be familiar with common compile-engineering principles and LLVM
code fundamentals. In this article we suppose reader is familiar with
`Single Static Assingment <http://en.wikipedia.org/wiki/Static_single_assignment_form>`_
concepts. Understanding of
`IR structure <http://llvm.org/docs/LangRef.html#high-level-structure>`_ is
also important.
The reader should be familiar with common compile-engineering principles and
LLVM code fundamentals. In this article, we assume the reader is familiar with
`Single Static Assignment
<http://en.wikipedia.org/wiki/Static_single_assignment_form>`_
concept and has an understanding of
`IR structure <http://llvm.org/docs/LangRef.html#high-level-structure>`_.
We will use such terms as
We will use terms such as
"`module <http://llvm.org/docs/LangRef.html#high-level-structure>`_",
"`function <http://llvm.org/docs/ProgrammersManual.html#the-function-class>`_",
"`basic block <http://en.wikipedia.org/wiki/Basic_block>`_",
"`user <http://llvm.org/docs/ProgrammersManual.html#the-user-class>`_",
"`value <http://llvm.org/docs/ProgrammersManual.html#the-value-class>`_",
"`instruction <http://llvm.org/docs/ProgrammersManual.html#the-instruction-class>`_".
"`instruction
<http://llvm.org/docs/ProgrammersManual.html#the-instruction-class>`_".
As a good start point, Kaleidoscope tutorial could be used:
As a good starting point, the Kaleidoscope tutorial can be used:
:doc:`tutorial/index`
Especially it's important to understand chapter 3 of tutorial:
It's especially important to understand chapter 3 of tutorial:
:doc:`tutorial/LangImpl03`
Reader also should know how passes work in LLVM, they could use next article as
a reference and start point here:
The reader should also know how passes work in LLVM. They could use this
article as a reference and start point here:
:doc:`WritingAnLLVMPass`
What else? Well perhaps reader also should have some experience in LLVM pass
What else? Well perhaps the reader should also have some experience in LLVM pass
debugging and bug-fixing.
What I gain by reading this document?
-------------------------------------
Main purpose is to provide reader with comfortable form of algorithms
description, namely the human reading text. Since it could be hard to
understand algorithm straight from the source code: pass uses some principles
that have to be explained first.
Author wishes to everybody to avoid case, when you read code from top to bottom
again and again, and yet you don't understand why we implemented it that way.
We hope that after this article reader could easily debug and improve
MergeFunctions pass and thus help LLVM project.
Narrative structure
-------------------
Article consists of three parts. First part explains pass functionality on the
top-level. Second part describes the comparison procedure itself. The third
part describes the merging process.
The article consists of three parts. The first part explains pass functionality
on the top-level. The second part describes the comparison procedure itself.
The third part describes the merging process.
In every part author also tried to put the contents into the top-down form.
First, the top-level methods will be described, while the terminal ones will be
at the end, in the tail of each part. If reader will see the reference to the
In every part, the author tries to put the contents in the top-down form.
The top-level methods will first be described followed by the terminal ones at
the end, in the tail of each part. If the reader sees the reference to the
method that wasn't described yet, they will find its description a bit below.
Basics
@ -95,46 +82,46 @@ Basics
How to do it?
-------------
Do we need to merge functions? Obvious thing is: yes that's a quite possible
case, since usually we *do* have duplicates. And it would be good to get rid of
them. But how to detect such a duplicates? The idea is next: we split functions
onto small bricks (parts), then we compare "bricks" amount, and if it equal,
compare "bricks" themselves, and then do our conclusions about functions
Do we need to merge functions? The obvious answer is: Yes, that is quite a
possible case. We usually *do* have duplicates and it would be good to get rid
of them. But how do we detect duplicates? This is the idea: we split functions
into smaller bricks or parts and compare the "bricks" amount. If equal,
we compare the "bricks" themselves, and then do our conclusions about functions
themselves.
What the difference it could be? For example, on machine with 64-bit pointers
(let's assume we have only one address space), one function stores 64-bit
integer, while another one stores a pointer. So if the target is a machine
What could the difference be? For example, on a machine with 64-bit pointers
(let's assume we have only one address space), one function stores a 64-bit
integer, while another one stores a pointer. If the target is the machine
mentioned above, and if functions are identical, except the parameter type (we
could consider it as a part of function type), then we can treat ``uint64_t``
and``void*`` as equal.
could consider it as a part of function type), then we can treat a ``uint64_t``
and a ``void*`` as equal.
It was just an example; possible details are described a bit below.
This is just an example; more possible details are described a bit below.
As another example reader may imagine two more functions. First function
performs multiplication on 2, while the second one performs arithmetic right
shift on 1.
As another example, the reader may imagine two more functions. The first
function performs a multiplication on 2, while the second one performs an
arithmetic right shift on 1.
Possible solutions
^^^^^^^^^^^^^^^^^^
Let's briefly consider possible options about how and what we have to implement
in order to create full-featured functions merging, and also what it would
meant for us.
mean for us.
Equal functions detection, obviously supposes "detector" method to be
implemented, latter should answer the question "whether functions are equal".
This "detector" method consists of tiny "sub-detectors", each of them answers
Equal function detection obviously supposes that a "detector" method to be
implemented and latter should answer the question "whether functions are equal".
This "detector" method consists of tiny "sub-detectors", which each answers
exactly the same question, but for function parts.
As the second step, we should merge equal functions. So it should be a "merger"
method. "Merger" accepts two functions *F1* and *F2*, and produces *F1F2*
function, the result of merging.
Having such a routines in our hands, we can process whole module, and merge all
Having such routines in our hands, we can process a whole module, and merge all
equal functions.
In this case, we have to compare every function with every another function. As
reader could notice, this way seems to be quite expensive. Of course we could
the reader may notice, this way seems to be quite expensive. Of course we could
introduce hashing and other helpers, but it is still just an optimization, and
thus the level of O(N*N) complexity.
@ -143,44 +130,45 @@ access lookup? The answer is: "yes".
Random-access
"""""""""""""
How it could be done? Just convert each function to number, and gather all of
them in special hash-table. Functions with equal hash are equal. Good hashing
means, that every function part must be taken into account. That means we have
to convert every function part into some number, and then add it into hash.
Lookup-up time would be small, but such approach adds some delay due to hashing
routine.
How it could this be done? Just convert each function to a number, and gather
all of them in a special hash-table. Functions with equal hashes are equal.
Good hashing means, that every function part must be taken into account. That
means we have to convert every function part into some number, and then add it
into the hash. The lookup-up time would be small, but such a approach adds some
delay due to the hashing routine.
Logarithmical search
""""""""""""""""""""
We could introduce total ordering among the functions set, once we had it we
We could introduce total ordering among the functions set, once ordered we
could then implement a logarithmical search. Lookup time still depends on N,
but adds a little of delay (*log(N)*).
Present state
"""""""""""""
Both of approaches (random-access and logarithmical) has been implemented and
tested. And both of them gave a very good improvement. And what was most
surprising, logarithmical search was faster; sometimes up to 15%. Hashing needs
some extra CPU time, and it is the main reason why it works slower; in most of
cases total "hashing" time was greater than total "logarithmical-search" time.
Both of the approaches (random-access and logarithmical) have been implemented
and tested and both give a very good improvement. What was most
surprising is that logarithmical search was faster; sometimes by up to 15%. The
hashing method needs some extra CPU time, which is the main reason why it works
slower; in most cases, total "hashing" time is greater than total
"logarithmical-search" time.
So, preference has been granted to the "logarithmical search".
Though in the case of need, *logarithmical-search* (read "total-ordering") could
be used as a milestone on our way to the *random-access* implementation.
Every comparison is based either on the numbers or on flags comparison. In
*random-access* approach we could use the same comparison algorithm. During
comparison we exit once we find the difference, but here we might have to scan
whole function body every time (note, it could be slower). Like in
"total-ordering", we will track every numbers and flags, but instead of
comparison, we should get numbers sequence and then create the hash number. So,
once again, *total-ordering* could be considered as a milestone for even faster
(in theory) random-access approach.
Every comparison is based either on the numbers or on the flags comparison. In
the *random-access* approach, we could use the same comparison algorithm.
During comparison, we exit once we find the difference, but here we might have
to scan the whole function body every time (note, it could be slower). Like in
"total-ordering", we will track every number and flag, but instead of
comparison, we should get the numbers sequence and then create the hash number.
So, once again, *total-ordering* could be considered as a milestone for even
faster (in theory) random-access approach.
MergeFunctions, main fields and runOnModule
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
There are two most important fields in class:
There are two main important fields in the class:
``FnTree`` – the set of all unique functions. It keeps items that couldn't be
merged with each other. It is defined as:
@ -192,8 +180,8 @@ implemented “<” operator among the functions set (below we explain how it wo
exactly; this is a key point in fast functions comparison).
``Deferred`` – merging process can affect bodies of functions that are in
``FnTree`` already. Obviously such functions should be rechecked again. In this
case we remove them from ``FnTree``, and mark them as to be rescanned, namely
``FnTree`` already. Obviously, such functions should be rechecked again. In this
case, we remove them from ``FnTree``, and mark them to be rescanned, namely
put them into ``Deferred`` list.
runOnModule
@ -205,28 +193,30 @@ The algorithm is pretty simple:
2. Scan *worklist*'s functions twice: first enumerate only strong functions and
then only weak ones:
2.1. Loop body: take function from *worklist* (call it *FCur*) and try to
2.1. Loop body: take a function from *worklist* (call it *FCur*) and try to
insert it into *FnTree*: check whether *FCur* is equal to one of functions
in *FnTree*. If there *is* equal function in *FnTree* (call it *FExists*):
merge function *FCur* with *FExists*. Otherwise add function from *worklist*
to *FnTree*.
in *FnTree*. If there *is* an equal function in *FnTree*
(call it *FExists*): merge function *FCur* with *FExists*. Otherwise add
the function from the *worklist* to *FnTree*.
3. Once *worklist* scanning and merging operations is complete, check *Deferred*
list. If it is not empty: refill *worklist* contents with *Deferred* list and
do step 2 again, if *Deferred* is empty, then exit from method.
3. Once the *worklist* scanning and merging operations are complete, check the
*Deferred* list. If it is not empty: refill the *worklist* contents with
*Deferred* list and redo step 2, if the *Deferred* list is empty, then exit
from method.
Comparison and logarithmical search
"""""""""""""""""""""""""""""""""""
Let's recall our task: for every function *F* from module *M*, we have to find
equal functions *F`* in shortest time, and merge them into the single function.
equal functions *F`* in the shortest time possible , and merge them into a
single function.
Defining total ordering among the functions set allows to organize functions
into the binary tree. The lookup procedure complexity would be estimated as
O(log(N)) in this case. But how to define *total-ordering*?
Defining total ordering among the functions set allows us to organize
functions into a binary tree. The lookup procedure complexity would be
estimated as O(log(N)) in this case. But how do we define *total-ordering*?
We have to introduce a single rule applicable to every pair of functions, and
following this rule then evaluate which of them is greater. What kind of rule
it could be? Let's declare it as "compare" method, that returns one of 3
following this rule, then evaluate which of them is greater. What kind of rule
could it be? Let's declare it as the "compare" method that returns one of 3
possible values:
-1, left is *less* than right,
@ -243,52 +233,52 @@ Of course it means, that we have to maintain
* transitivity (``a <= b`` and ``b <= c``, then ``a <= c``)
* asymmetry (if ``a < b``, then ``a > b`` or ``a == b``).
As it was mentioned before, comparison routine consists of
"sub-comparison-routines", each of them also consists
"sub-comparison-routines", and so on, finally it ends up with a primitives
As mentioned before, the comparison routine consists of
"sub-comparison-routines", with each of them also consisting of
"sub-comparison-routines", and so on. Finally, it ends up with primitive
comparison.
Below, we will use the next operations:
Below, we will use the following operations:
#. ``cmpNumbers(number1, number2)`` is method that returns -1 if left is less
#. ``cmpNumbers(number1, number2)`` is a method that returns -1 if left is less
than right; 0, if left and right are equal; and 1 otherwise.
#. ``cmpFlags(flag1, flag2)`` is hypothetical method that compares two flags.
#. ``cmpFlags(flag1, flag2)`` is a hypothetical method that compares two flags.
The logic is the same as in ``cmpNumbers``, where ``true`` is 1, and
``false`` is 0.
The rest of article is based on *MergeFunctions.cpp* source code
(*<llvm_dir>/lib/Transforms/IPO/MergeFunctions.cpp*). We would like to ask
reader to keep this file open nearby, so we could use it as a reference for
further explanations.
The rest of the article is based on *MergeFunctions.cpp* source code
(found in *<llvm_dir>/lib/Transforms/IPO/MergeFunctions.cpp*). We would like
to ask reader to keep this file open, so we could use it as a reference
for further explanations.
Now we're ready to proceed to the next chapter and see how it works.
Now, we're ready to proceed to the next chapter and see how it works.
Functions comparison
====================
At first, let's define how exactly we compare complex objects.
Complex objects comparison (function, basic-block, etc) is mostly based on its
sub-objects comparison results. So it is similar to the next "tree" objects
Complex object comparison (function, basic-block, etc) is mostly based on its
sub-object comparison results. It is similar to the next "tree" objects
comparison:
#. For two trees *T1* and *T2* we perform *depth-first-traversal* and have
two sequences as a product: "*T1Items*" and "*T2Items*".
#. Then compare chains "*T1Items*" and "*T2Items*" in
most-significant-item-first order. Result of items comparison would be the
result of *T1* and *T2* comparison itself.
#. We then compare chains "*T1Items*" and "*T2Items*" in
the most-significant-item-first order. The result of items comparison
would be the result of *T1* and *T2* comparison itself.
FunctionComparator::compare(void)
---------------------------------
Brief look at the source code tells us, that comparison starts in
A brief look at the source code tells us that the comparison starts in the
“``int FunctionComparator::compare(void)``” method.
1. First parts to be compared are function's attributes and some properties that
outsides “attributes” term, but still could make function different without
changing its body. This part of comparison is usually done within simple
*cmpNumbers* or *cmpFlags* operations (e.g.
``cmpFlags(F1->hasGC(), F2->hasGC())``). Below is full list of function's
1. The first parts to be compared are the function's attributes and some
properties that is outside the “attributes” term, but still could make the
function different without changing its body. This part of the comparison is
usually done within simple *cmpNumbers* or *cmpFlags* operations (e.g.
``cmpFlags(F1->hasGC(), F2->hasGC())``). Below is a full list of function's
properties to be compared on this stage:
* *Attributes* (those are returned by ``Function::getAttributes()``
@ -333,7 +323,7 @@ arguments (see ``cmpValues`` method below).
FunctionComparator::cmpType
---------------------------
Consider how types comparison works.
Consider how type comparison works.
1. Coerce pointer to integer. If left type is a pointer, try to coerce it to the
integer type. It could be done if its address space is 0, or if address spaces
@ -343,7 +333,7 @@ are ignored at all. Do the same thing for the right type.
preference to one of them. So proceed to the next step.
3. If types are of different kind (different type IDs). Return result of type
IDs comparison, treating them as a numbers (use ``cmpNumbers`` operation).
IDs comparison, treating them as numbers (use ``cmpNumbers`` operation).
4. If types are vectors or integers, return result of their pointers comparison,
comparing them as numbers.
@ -378,21 +368,21 @@ technique (see the very first paragraph of this chapter). Both *left* and
way. If we get -1 or 1 on some stage, return it. Otherwise return 0.
8. Steps 1-6 describe all the possible cases, if we passed steps 1-6 and didn't
get any conclusions, then invoke ``llvm_unreachable``, since it's quite
get any conclusions, then invoke ``llvm_unreachable``, since it's quite an
unexpectable case.
cmpValues(const Value*, const Value*)
-------------------------------------
Method that compares local values.
This method gives us an answer on a very curious quesion: whether we could treat
local values as equal, and which value is greater otherwise. It's better to
start from example:
This method gives us an answer to a very curious question: whether we could
treat local values as equal, and which value is greater otherwise. It's
better to start from example:
Consider situation when we're looking at the same place in left function "*FL*"
and in right function "*FR*". And every part of *left* place is equal to the
corresponding part of *right* place, and (!) both parts use *Value* instances,
for example:
Consider the situation when we're looking at the same place in left
function "*FL*" and in right function "*FR*". Every part of *left* place is
equal to the corresponding part of *right* place, and (!) both parts use
*Value* instances, for example:
.. code-block:: text
@ -401,13 +391,13 @@ for example:
So, now our conclusion depends on *Value* instances comparison.
Main purpose of this method is to determine relation between such values.
The main purpose of this method is to determine relation between such values.
What we expect from equal functions? At the same place, in functions "*FL*" and
"*FR*" we expect to see *equal* values, or values *defined* at the same place
in "*FL*" and "*FR*".
What can we expect from equal functions? At the same place, in functions
"*FL*" and "*FR*" we expect to see *equal* values, or values *defined* at
the same place in "*FL*" and "*FR*".
Consider small example here:
Consider a small example here:
.. code-block:: text
@ -421,20 +411,20 @@ Consider small example here:
instr0 i32 %pg0 instr1 i32 %pg0 instr2 i32 123
}
In this example, *pf0* is associated with *pg0*, *pf1* is associated with *pg1*,
and we also declare that *pf0* < *pf1*, and thus *pg0* < *pf1*.
In this example, *pf0* is associated with *pg0*, *pf1* is associated with
*pg1*, and we also declare that *pf0* < *pf1*, and thus *pg0* < *pf1*.
Instructions with opcode "*instr0*" would be *equal*, since their types and
opcodes are equal, and values are *associated*.
Instruction with opcode "*instr1*" from *f* is *greater* than instruction with
opcode "*instr1*" from *g*; here we have equal types and opcodes, but "*pf1* is
greater than "*pg0*".
Instructions with opcode "*instr1*" from *f* is *greater* than instructions
with opcode "*instr1*" from *g*; here we have equal types and opcodes, but
"*pf1* is greater than "*pg0*".
And instructions with opcode "*instr2*" are equal, because their opcodes and
Instructions with opcode "*instr2*" are equal, because their opcodes and
types are equal, and the same constant is used as a value.
What we assiciate in cmpValues?
What we associate in cmpValues?
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
* Function arguments. *i*-th argument from left function associated with
*i*-th argument from right function.
@ -444,23 +434,22 @@ What we assiciate in cmpValues?
* Instructions.
* Instruction operands. Note, we can meet *Value* here we have never seen
before. In this case it is not a function argument, nor *BasicBlock*, nor
*Instruction*. It is global value. It is constant, since its the only
supposed global here. Method also compares:
* Constants that are of the same type.
* If right constant could be losslessly bit-casted to the left one, then we
also compare them.
*Instruction*. It is a global value. It is a constant, since it's the only
supposed global here. The method also compares: Constants that are of the
same type and if right constant can be losslessly bit-casted to the left
one, then we also compare them.
How to implement cmpValues?
^^^^^^^^^^^^^^^^^^^^^^^^^^^
*Association* is a case of equality for us. We just treat such values as equal.
But, in general, we need to implement antisymmetric relation. As it was
mentioned above, to understand what is *less*, we can use order in which we
meet values. If both of values has the same order in function (met at the same
time), then treat values as *associated*. Otherwise – it depends on who was
*Association* is a case of equality for us. We just treat such values as equal,
but, in general, we need to implement antisymmetric relation. As mentioned
above, to understand what is *less*, we can use order in which we
meet values. If both values have the same order in a function (met at the same
time), we then treat values as *associated*. Otherwise – it depends on who was
first.
Every time we run top-level compare method, we initialize two identical maps
(one for the left side, another one for the right side):
Every time we run the top-level compare method, we initialize two identical
maps (one for the left side, another one for the right side):
``map<Value, int> sn_mapL, sn_mapR;``
@ -471,11 +460,11 @@ To add value *V* we need to perform the next procedure:
``sn_map.insert(std::make_pair(V, sn_map.size()));``
For the first *Value*, map will return *0*, for second *Value* map will return
*1*, and so on.
For the first *Value*, map will return *0*, for the second *Value* map will
return *1*, and so on.
Then we can check whether left and right values met at the same time with simple
comparison:
We can then check whether left and right values met at the same time with
a simple comparison:
``cmpNumbers(sn_mapL[Left], sn_mapR[Right]);``
@ -490,7 +479,7 @@ Of course, we can combine insertion and comparison:
Let's look, how whole method could be implemented.
1. we have to start from the bad news. Consider function self and
1. We have to start with the bad news. Consider function self and
cross-referencing cases:
.. code-block:: c++
@ -507,7 +496,7 @@ cross-referencing cases:
This comparison has been implemented in initial *MergeFunctions* pass
version. But, unfortunately, it is not transitive. And this is the only case
we can't convert to less-equal-greater comparison. It is a seldom case, 4-5
functions of 10000 (checked on test-suite), and, we hope, reader would
functions of 10000 (checked in test-suite), and, we hope, the reader would
forgive us for such a sacrifice in order to get the O(log(N)) pass time.
2. If left/right *Value* is a constant, we have to compare them. Return 0 if it
@ -518,8 +507,8 @@ comparison.
4. Explicit association of *L* (left value) and *R* (right value). We need to
find out whether values met at the same time, and thus are *associated*. Or we
need to put the rule: when we treat *L* < *R*. Now it is easy: just return
result of numbers comparison:
need to put the rule: when we treat *L* < *R*. Now it is easy: we just return
the result of numbers comparison:
.. code-block:: c++
@ -530,16 +519,16 @@ result of numbers comparison:
if (LeftRes.first->second < RightRes.first->second) return -1;
return 1;
Now when *cmpValues* returns 0, we can proceed comparison procedure. Otherwise,
if we get (-1 or 1), we need to pass this result to the top level, and finish
comparison procedure.
Now when *cmpValues* returns 0, we can proceed the comparison procedure.
Otherwise, if we get (-1 or 1), we need to pass this result to the top level,
and finish comparison procedure.
cmpConstants
------------
Performs constants comparison as follows:
1. Compare constant types using ``cmpType`` method. If result is -1 or 1, goto
step 2, otherwise proceed to step 3.
1. Compare constant types using ``cmpType`` method. If the result is -1 or 1,
goto step 2, otherwise proceed to step 3.
2. If types are different, we still can check whether constants could be
losslessly bitcasted to each other. The further explanation is modification of
@ -581,10 +570,10 @@ bitcastable:
if (int Res = cmpNumbers(L->getValueID(), R->getValueID()))
return Res;
5. Compare the contents of constants. The comparison depends on kind of
5. Compare the contents of constants. The comparison depends on the kind of
constants, but on this stage it is just a lexicographical comparison. Just see
how it was described in the beginning of "*Functions comparison*" paragraph.
Mathematically it is equal to the next case: we encode left constant and right
Mathematically, it is equal to the next case: we encode left constant and right
constant (with similar way *bitcode-writer* does). Then compare left code
sequence and right code sequence.
@ -598,7 +587,7 @@ It enumerates instructions from left *BB* and right *BB*.
``cmpValues`` method.
2. If one of left or right is *GEP* (``GetElementPtr``), then treat *GEP* as
greater than other instructions, if both instructions are *GEPs* use ``cmpGEP``
greater than other instructions. If both instructions are *GEPs* use ``cmpGEP``
method for comparison. If result is -1 or 1, pass it to the top-level
comparison (return it).
@ -618,11 +607,11 @@ comparison (return it).
4. We can finish instruction enumeration in 3 cases:
4.1. We reached the end of both left and right basic-blocks. We didn't
exit on steps 1-3, so contents is equal, return 0.
exit on steps 1-3, so contents are equal, return 0.
4.2. We have reached the end of the left basic-block. Return -1.
4.3. Return 1 (the end of the right basic block).
4.3. Return 1 (we reached the end of the right basic block).
cmpGEP
------
@ -652,8 +641,8 @@ method, and compare it like a numbers.
5. Compare operand types.
6. For some particular instructions check equivalence (relation in our case) of
some significant attributes. For example we have to compare alignment for
6. For some particular instructions, check equivalence (relation in our case) of
some significant attributes. For example, we have to compare alignment for
``load`` instructions.
O(log(N))
@ -692,7 +681,7 @@ call wrapper around *F* and replace *G* with that call.
change the callers: call *F* instead of *G*. That's what
``replaceDirectCallers`` does.
Below is detailed body description.
Below is a detailed body description.
If “F” may be overridden
------------------------
@ -736,17 +725,17 @@ also have alias to *F*.
No global aliases, replaceDirectCallers
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If global aliases are not supported. We call ``replaceDirectCallers`` then. Just
If global aliases are not supported. We call ``replaceDirectCallers``. Just
go through all calls of *G* and replace it with calls of *F*. If you look into
method you will see that it scans all uses of *G* too, and if use is callee (if
user is call instruction and *G* is used as what to be called), we replace it
with use of *F*.
the method you will see that it scans all uses of *G* too, and if use is callee
(if user is call instruction and *G* is used as what to be called), we replace
it with use of *F*.
If “F” could not be overridden, fix it!
"""""""""""""""""""""""""""""""""""""""
We call ``writeThunkOrAlias(Function *F, Function *G)``. Here we try to replace
*G* with alias to *F* first. Next conditions are essential:
*G* with alias to *F* first. The next conditions are essential:
* target should support global aliases,
* the address itself of *G* should be not significant, not named and not
@ -761,7 +750,7 @@ so *G* could be replaced with this wrapper.
As follows from *llvm* reference:
“Aliases act as *second name* for the aliasee value”. So we just want to create
second name for *F* and use it instead of *G*:
a second name for *F* and use it instead of *G*:
1. create global alias itself (*GA*),
@ -793,10 +782,4 @@ it instead of *G*.
3. Get rid of *G*.
That's it.
==========
We have described how to detect equal functions, and how to merge them, and in
first chapter we have described how it works all-together. Author hopes, reader
have some picture from now, and it helps him improve and debug ­this pass.
Reader is welcomed to send us any questions and proposals ;-)