[llvm-dev] [RFC] Interprocedural MIR-level outlining pass

Andrey Bokhanko via llvm-dev
Mon, 29 Aug 2016 19:35:04 -0000

Daniel,

I wonder what the NewGVN would generate for the following C code:

int a, b;

int foo() {
  return a + b;
}

int bar() {
  return a + b;
}

?

Obviously, the expressions would be the same ("value1 + value2"), but
a
single operator is not worthy to be outlined. What classes of congruency
would be assigned to operands? The same for both reads of "a" and
"b"? If
yes, it would be incorrect, as obviously, these two additions are not
guaranteed to be semantically equivalent (a's and b's values can be
changed
in-between).

Also note that one should be able to compare VN's results from different
functions. Looks like an inter-procedural VN is required.

Yours,
Andrey


On Sat, Aug 27, 2016 at 9:28 AM, Daniel Berlin via llvm-dev <
llvm-dev at lists.llvm.org> wrote:

>
>
> On Fri, Aug 26, 2016 at 9:44 PM, Hal Finkel <hfinkel at anl.gov>
wrote:
>
>>
>> ------------------------------
>>
>> *From: *"Daniel Berlin" <dberlin at dberlin.org>
>> *To: *"Quentin Colombet" <qcolombet at apple.com>
>> *Cc: *"Hal Finkel" <hfinkel at anl.gov>,
"llvm-dev" <llvm-dev at lists.llvm.org
>> >
>> *Sent: *Friday, August 26, 2016 11:06:56 PM
>> *Subject: *Re: [llvm-dev] [RFC] Interprocedural MIR-level outlining
pass
>>
>> FWIW: I'm with quentin. Without a good value numbering analysis,
this is
>> a hard problem.
>>
>> How exactly does value numbering help here? This problem seems to be
>> about finding structurally-similar parts of the computations of
different
>> values, not identical values.
>>
> Note, first, the optimization we are talking about is not outlining, at
> least, as far as i've ever heard it.
>
> function outlining/etc is about removing cold regions of functions to
> separate functions to make the hot portions smaller, more inlinable, etc.
>
> What is being talked about here is a variant of  identical code folding,
> e.g., http://research.google.com/pubs/pub36912.html and it's variants.
>
> Where identical varies (and is based on semantic equivalence).  Variants
> where you extract portions partially to merge functions are pretty much the
>  same optimization :)
>
> Here, value numbering helps because it gives you value expressions.
>
> It tells you:
>
> This operation is "add V1, V2".
> It does not matter what V1 and V2 are, they just "are abstract
things". We
> know if these abstract things are equivalent or not.
>
> More relevantly, these expressions form a value number dag.
>
> That is, they represent the computations being computed only in terms of
> operators, abstract variables, and other parts of the VNDAG
>
> The *actual values* of those computations, numbers, etc, do not matter (IE
> the abstract value numbers have some set of things *in the program* that
> are in the set of things equivalent to that value number).
>
> It is "are these semantically the same operations in the same
order",
> regardless of the value of those operations.
> See, for example, the DAGS generated by:
>
> https://www.researchgate.net/publication/221323142_An_
> Efficient_SSA-Based_Algorithm_for_Complete_Global_Value_Numbering
>
> Again, this is not something current GVN does, but NewGVN (and other
GVN's
> do) can give you.
>
> The question of what portions of a function you can merge are variants of
> common subgraph and graph isomorphism problems on a VNDAG.
>
> (because in the end, it doesn't matter where the computations are, it
> matters what they abstractly compute, and what they depend on)
>
>
>
>> It seems much closer to the analysis necessary for SLP vectorization
than
>> value numbering, as such.
>>
>
>
>> I think we might be able to use value numbering to help with subset of
>> SLP vectorization, but only because we can define some kind of
equivalence
>> relation on consecutive memory accesses (and similar). What you need
for
>> this outlining seems more akin to the general SLP-vectorization case.
This
>> might just be the maximal common subgraph problem.
>>
>
> If i have an add in a loop, and it's VN equivalent to an add outside a
> loop in some other function, i can still merge the functions :)
>
> It's how the value is generated and used that matters, not the
structure
> of the program.
>
> So you can't just do it on a regular CFG or anything like that if you
want
> good results.
>
>>
>>  -Hal
>>
>>
>> GVN as it exists now doesn't really provide what you want, and in
fact,
>> doesn't value number a lot of instruction types (including, for
example,
>> loads, stores, calls, phis, etc).  It also relies on ordering, and more
>> importantly, it relies on *not* being a strong analysis. If you were to
>> stop it from eliminating as it went, it would catch maybe 10% of the
>> redundancies it does now.  So what you want is "i want to know
what
>> globally is the same", it doesn't really answer that well.
>>
>> Doing the analysis Quentin wants is pretty trivial in NewGVN (analysis
>> and elimination are split, everything is broken into congruence classes
>> explicitly, each congruence class has an id, you could sub in that id
as
>> the value for the terminated string), but i'd agree that GVN as it
exists
>> now will not do what they want, and would be pretty hard to make work
well.
>>
>> (FWIW: Davide Italiano has started breaking up newgvn into submittable
>> pieces, and is pretty far along to having a first patch set I believe)
>>
>>
>> On Fri, Aug 26, 2016 at 4:54 PM, Quentin Colombet via llvm-dev <
>> llvm-dev at lists.llvm.org> wrote:
>>
>>> Hi,
>>>
>>> I let Jessica give more details but here are some insights.
>>>
>>> MIR offers a straight forward way to model benefits, because we
know
>>> which instructions we remove and which one we add and there are no
overhead
>>> of setting up parameters. Indeed, since the coloring will be the
same
>>> between the different outlining candidates, the call is just a jump
>>> somewhere else. We do not have to worry about the impact of
parameter
>>> passing and ABI.
>>>
>>> So basically, better cost model. That's one part of the story.
>>>
>>> The other part is at the LLVM IR level or before register
allocation
>>> identifying similar code sequence is much harder, at least with a
suffix
>>> tree like algorithm. Basically the problem is how do we name our
>>> instructions such that we can match them.
>>> Let me take an example.
>>> foo() {
>>> /* bunch of code */
>>> a = add b, c;
>>> d = add e, f;
>>> }
>>>
>>> bar() {
>>> d = add e, g;
>>> f = add c, w;
>>> }
>>>
>>> With proper renaming, we can outline both adds in one function. The
>>> difficulty is to recognize that they are semantically equivalent to
give
>>> them the same identifier in the suffix tree. I won’t get into the
details
>>> but it gets tricky quickly. We were thinking of reusing GVN to have
such
>>> identifier if we wanted to do the outlining at IR level but solving
this
>>> problem is hard.
>>>
>>> By running after regalloc, we basically have a heuristic that does
this
>>> naming for us.
>>>
>>> Cheers,
>>> -Quentin
>>>
>>>
>>> On Aug 26, 2016, at 3:01 PM, Hal Finkel via llvm-dev <
>>> llvm-dev at lists.llvm.org> wrote:
>>>
>>>
>>> ------------------------------
>>>
>>> *From: *"Kevin Choi" <code.kchoi at gmail.com>
>>> *To: *"Hal Finkel" <hfinkel at anl.gov>
>>> *Cc: *"llvm-dev" <llvm-dev at lists.llvm.org>
>>> *Sent: *Friday, August 26, 2016 4:55:29 PM
>>> *Subject: *Re: [llvm-dev] [RFC] Interprocedural MIR-level outlining
pass
>>>
>>> I think the "Motivation" section explained that.
>>>
>>> I don't think it explained it.
>>>
>>> I too first thought about "why not at IR?" but the reason
looks like
>>> MIR, post-RA has the most accurate heuristics (best way to know
looks like
>>> actually getting there).
>>>
>>> But also, potentially, the fewest opportunities. That's why
I'm curious
>>> about the motivation - the trade offs are not obvious to me.
>>>
>>>  -Hal
>>>
>>>
>>>
>>> Do you know if there is any experimental pass that relies on
deriving
>>> heuristics by a feedback loop after letting, ie. a duplicate
>>> module/function/block continue past?
>>>
>>> Regards,
>>> Kevin
>>>
>>> On 26 August 2016 at 14:36, Hal Finkel via llvm-dev <
>>> llvm-dev at lists.llvm.org> wrote:
>>>
>>>> Hi Jessica,
>>>>
>>>> This is quite interesting.
>>>>
>>>> Can you comment on why you started by doing this at the MI
level, as
>>>> opposed to the IR level. And at the MI level, why after RA
instead of
>>>> before RA?
>>>>
>>>> Perhaps the first question is another way of asking about how
>>>> accurately we can model call-site code size at the IR level?
>>>>
>>>> Thanks in advance,
>>>> Hal
>>>>
>>>> ------------------------------
>>>>
>>>> > From: "Jessica Paquette via llvm-dev"
<llvm-dev at lists.llvm.org>
>>>> > To: llvm-dev at lists.llvm.org
>>>> > Sent: Friday, August 26, 2016 4:26:09 PM
>>>> > Subject: [llvm-dev] [RFC] Interprocedural MIR-level
outlining pass
>>>> >
>>>> > Hi everyone,
>>>> >
>>>> > Since I haven't said anything on the mailing list
before, a quick
>>>> > introduction. I'm an intern at Apple, and over the
summer I
>>>> > implemented a
>>>> > prototype for an outlining pass for code size in LLVM. Now
I'm
>>>> > seeking to
>>>> > eventually upstream it. I have the preliminary code on
GitHub right
>>>> > now,
>>>> > but it's still very prototypical (see the code
section).
>>>> >
>>>> > ===============================>>>> >
Motivation
>>>> > ===============================>>>> > The
goal of the internship was to create an interprocedural pass that
>>>> > would reduce code size as much as possible, perhaps at the
cost of
>>>> > some
>>>> > performance. This would be useful to, say, embedded
programmers who
>>>> > only
>>>> > have a few kilobytes to work with and a substantial amount
of code to
>>>> > fit
>>>> > in that space.
>>>> >
>>>> >
>>>> > ===============================>>>> >
Approach and Initial Results
>>>> > ===============================>>>> > To do
this, we chose to implement an outliner. Outliners find
>>>> > sequences of
>>>> > instructions which would be better off as a function call,
by some
>>>> > measure
>>>> > of "better". In this case, the measure of
"better" is "makes code
>>>> > smaller".
>>>> >
>>>> >
>>>> > ===============================>>>> >
Results
>>>> > ===============================>>>> > These
results are from a fairly recent 64-bit Intel processor, using
>>>> > a
>>>> > version of Clang equipped with the outliner prototype
versus an
>>>> > equivalent
>>>> > version of Clang without the outliner.
>>>> >
>>>> > CODE SIZE REDUCTION
>>>> > For tests >=4 Kb in non-outlined size, the outliner
currently
>>>> > provides an
>>>> > average of 12.94% code size reduction on the LLVM test
suite in
>>>> > comparison
>>>> > to a default Clang, up to 51.4% code size reduction. In
comparison to
>>>> > a
>>>> > Clang with -Oz, the outliner provides an average of a
1.29% code size
>>>> > reduction, up to a 37% code size reduction. I believe that
the -Oz
>>>> > numbers
>>>> > can be further improved by better tuning the outlining
cost model.
>>>> >
>>>> > EXECUTION TIME IMPACT
>>>> > On average, the outliner increases execution time by 2% on
the LLVM
>>>> > test
>>>> > suite, but has been also shown to improve exection time by
up to 16%.
>>>> > These results were from a fairly recent Intel processor,
so the
>>>> > results
>>>> > may vary. Recent Intel processors have very low latency
for function
>>>> > calls, which may impact these results. Execution time
improvements
>>>> > are
>>>> > likely dependent on the latency of function calls,
instruction
>>>> > caching
>>>> > behaviour, and the execution frequency of the code being
outlined. In
>>>> > partucular, using a processor with heavy function call
latency will
>>>> > likely
>>>> > increase execution time overhead.
>>>> >
>>>> >
>>>> > ===============================>>>> >
Implementation
>>>> > ===============================>>>> > The
outliner, in its current state, is a MachineModulePass. It finds
>>>> > *identical* sequences of MIR, after register allocation,
and pulls
>>>> > them
>>>> > out into their own functions. Thus, it's effectively
assembly-level.
>>>> > Ultimately, the algorithm used is general, so it can sit
anywhere,
>>>> > but MIR
>>>> > was very convenient for the time being.
>>>> >
>>>> > It requires two data structures.
>>>> >
>>>> > 1. A generalized suffix tree
>>>> > 2. A "terminated string"
>>>> >
>>>> > 1: The generalized suffix tree is constructed using
Ukkonen's linear
>>>> > time
>>>> > construction algorithm [1]. They require linear space and
support
>>>> > linear-time substring queries. In practice, the
construction time for
>>>> > the
>>>> > suffix tree is the most time consuming part, but I
haven't noticed a
>>>> > difference in compilation time on, say, 12 MB .ll files.
>>>> >
>>>> > 2: To support the suffix tree, we need a "terminated
string." This is
>>>> > a
>>>> > generalized string with an unique terminator character
appended to
>>>> > the
>>>> > end. TerminatedStrings can be built from any type.
>>>> >
>>>> > The algorithm is then roughly as follows.
>>>> >
>>>> > 1. For each MachineBasicBlock in the program, build a
>>>> > TerminatedString for
>>>> > that block.
>>>> > 2. Build a suffix tree for that collection of strings.
>>>> > 3. Query the suffix tree for the longest repeated
substring and place
>>>> > that
>>>> > string in a candidate list. Repeat until none are found.
>>>> > 4. Create functions for each candidate.
>>>> > 5. Replace each candidate with a call to its respective
function.
>>>> >
>>>> > Currently, the program itself isn't stored in the
suffix tree, but
>>>> > rather
>>>> > a "proxy string" of integers. This isn't
necessary at the MIR level,
>>>> > but
>>>> > may be for an IR level extension of the algorithm.
>>>> >
>>>> >
>>>> > ===============================>>>> >
Challenges
>>>> > ===============================>>>> > 1)
MEMORY CONSUMPTION
>>>> > Given a string of length n, a naive suffix tree
implementation can
>>>> > take up
>>>> > to 40n bytes of memory. However, this number can be
reduced to 20n
>>>> > with a
>>>> > bit of work [2]. Currently, the suffix tree stores the
entire
>>>> > program,
>>>> > including instructions which really ought not to be
outlined, such as
>>>> > returns. These instructions should not be included in the
final
>>>> > implementation, but should rather act as terminators for
the strings.
>>>> > This
>>>> > will likely curb memory consumption. Suffix trees have
been used in
>>>> > the
>>>> > past in sliding-window-based compression schemes, which
may serve as
>>>> > a
>>>> > source of inspiration for reducing memory overhead.[3]
>>>> >
>>>> > Nonetheless, the outliner probably shouldn't be run
unless it really
>>>> > has
>>>> > to be run. It will likely be used mostly in embedded
spaces, where
>>>> > the
>>>> > programs have to fit into small devices anyway. Thus,
memory overhead
>>>> > for
>>>> > the compiler likely won't be a problem. The outliner
should only be
>>>> > used
>>>> > in -Oz compilations, and possibly should have its own
flag.
>>>> >
>>>> >
>>>> > 2) EXECUTION TIME
>>>> > Currently, the outliner isn't tuned for preventing
execution time
>>>> > increases. There is an average of a 2% execution time hit
on the
>>>> > tests in
>>>> > the LLVM test suite, with a few outliers of up to 30%. The
outliers
>>>> > are
>>>> > tests which contain hot loops. The outliner really ought
to be able
>>>> > to use
>>>> > profiling information and not outline from hot areas.
Another
>>>> > suggestion
>>>> > people have given me is to add a "never outline"
directive which
>>>> > would
>>>> > allow the user to say something along the lines of
"this is a hot
>>>> > loop,
>>>> > please never outline from it".
>>>> >
>>>> > It's also important to note that these numbers are
coming from a
>>>> > fairly
>>>> > recent Intel processor.
>>>> >
>>>> >
>>>> > 3) CONSTRAINTS ON INSTRUCTIONS
>>>> > The outliner currently won't pull anything out of
functions which use
>>>> > a
>>>> > red zone. It also won't pull anything out that uses
the stack,
>>>> > instruction
>>>> > pointer, uses constant pool indices, CFI indices, jump
table indices,
>>>> > or
>>>> > frame indices. This removes many opportunities for
outlining which
>>>> > would
>>>> > likely be available at a higher level (such as IR). Thus,
there's a
>>>> > case
>>>> > for moving this up to a higher level.
>>>> >
>>>> >
>>>> > ===============================>>>> >
Additional Applications
>>>> > ===============================>>>> > The
suffix tree itself could be used as a tool for finding
>>>> > opportunities
>>>> > to refactor code. For example, it could recognize places
where the
>>>> > user
>>>> > likely copied and pasted some code. This could be run on
codebases to
>>>> > find
>>>> > areas where people could manually outline things at the
source level.
>>>> >
>>>> > Using the terminated string class, it would also be
possible to
>>>> > implement
>>>> > other string algorithms on code. This may open the door to
new ways
>>>> > to
>>>> > analyze existing codebases.
>>>> >
>>>> >
>>>> > ===============================>>>> >
Roadmap
>>>> > ===============================>>>> > The
current outliner is *very* prototypical. The version I would want
>>>> > to
>>>> > upstream would be a new implementation. Here's what
I'd like to
>>>> > address
>>>> > and accomplish.
>>>> >
>>>> > 1. Ask "what does the LLVM community want from an
outliner" and use
>>>> > that
>>>> > to drive development of the algorithm.
>>>> > 2. Reimplement the outliner, perhaps using a less
memory-intensve
>>>> > data
>>>> > structure like a suffix array.
>>>> > 3. Begin adding features to the algorithm, for example:
>>>> >     i.   Teaching the algorithm about hot/cold blocks of
code and
>>>> >     taking
>>>> > that into account.
>>>> >     ii.  Simple parameter passing.
>>>> >     iii. Similar function outlining-- eg, noticing that
two outlining
>>>> > candidates are similar and can be merged into one function
with some
>>>> > control flow.
>>>> >
>>>> >
>>>> > ===============================>>>> > Code
>>>> > ===============================>>>> > Note:
This code requires MachineModulePasses
>>>> >
>>>> > * Main pass:
>>>> > https://github.com/ornata/llvm/blob/master/lib/CodeGen/Mac
>>>> hineOutliner.h
>>>> >
>>>> > * Suffix tree:
>>>> > https://github.com/ornata/llvm/blob/master/include/llvm/AD
>>>> T/SuffixTree.h
>>>> >
>>>> > * TerminatedString and TerminatedStringList:
>>>> > https://github.com/ornata/llvm/blob/master/include/llvm/AD
>>>> T/TerminatedString.h
>>>> >
>>>> > Here are a couple unit tests for the data structures.
>>>> >
>>>> > * Suffix tree unit tests:
>>>> > https://github.com/ornata/llvm/blob/master/unittests/ADT/
>>>> SuffixTreeTest.cpp
>>>> >
>>>> > * TerminatedString unit tests:
>>>> > https://github.com/ornata/llvm/blob/master/unittests/ADT/
>>>> TerminatedStringTest.cpp
>>>> >
>>>> > * TerminatedStringList unit tests:
>>>> > https://github.com/ornata/llvm/blob/master/unittests/ADT/
>>>> TerminatedStringListTest.cpp
>>>> >
>>>> >
>>>> > ===============================>>>> >
References
>>>> > ===============================>>>> > [1]
Ukkonen's Algorithm:
>>>> > https://www.cs.helsinki.fi/u/ukkonen/SuffixT1withFigs.pdf
>>>> > [2] Suffix Trees and Suffix Arrays:
>>>> > http://web.cs.iastate.edu/~cs548/suffix.pdf
>>>> > [3] Extended Application of Suffix Trees to Data
Compression:
>>>> > http://www.larsson.dogma.net/dccpaper.pdf
>>>> >
>>>> >
>>>> > Thanks for reading,
>>>> > Jessica
>>>> >
>>>> > _______________________________________________
>>>> > LLVM Developers mailing list
>>>> > llvm-dev at lists.llvm.org
>>>> > http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>>>> >
>>>>
>>>> --
>>>> Hal Finkel
>>>> Assistant Computational Scientist
>>>> Leadership Computing Facility
>>>> Argonne National Laboratory
>>>> _______________________________________________
>>>> LLVM Developers mailing list
>>>> llvm-dev at lists.llvm.org
>>>> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>>>>
>>>
>>>
>>>
>>>
>>> --
>>> Hal Finkel
>>> Assistant Computational Scientist
>>> Leadership Computing Facility
>>> Argonne National Laboratory
>>> _______________________________________________
>>> LLVM Developers mailing list
>>> llvm-dev at lists.llvm.org
>>> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>>>
>>>
>>>
>>> _______________________________________________
>>> LLVM Developers mailing list
>>> llvm-dev at lists.llvm.org
>>> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>>>
>>>
>>
>>
>>
>> --
>> Hal Finkel
>> Assistant Computational Scientist
>> Leadership Computing Facility
>> Argonne National Laboratory
>>
>
>
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org
> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
<http://lists.llvm.org/pipermail/llvm-dev/attachments/20160829/8e7aafcf/attachment-0001.html>