Quentin Colombet via llvm-dev
2016-Aug-26 23:54 UTC
[llvm-dev] [RFC] Interprocedural MIR-level outlining pass
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
<mailto:code.kchoi at gmail.com>>
> To: "Hal Finkel" <hfinkel at anl.gov <mailto:hfinkel at
anl.gov>>
> Cc: "llvm-dev" <llvm-dev at lists.llvm.org <mailto: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 <mailto: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 <mailto:llvm-dev at lists.llvm.org>>
> > To: llvm-dev at lists.llvm.org <mailto: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/MachineOutliner.h
<https://github.com/ornata/llvm/blob/master/lib/CodeGen/MachineOutliner.h>
> >
> > * Suffix tree:
> >
https://github.com/ornata/llvm/blob/master/include/llvm/ADT/SuffixTree.h
<https://github.com/ornata/llvm/blob/master/include/llvm/ADT/SuffixTree.h>
> >
> > * TerminatedString and TerminatedStringList:
> >
https://github.com/ornata/llvm/blob/master/include/llvm/ADT/TerminatedString.h
<https://github.com/ornata/llvm/blob/master/include/llvm/ADT/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
<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
<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
<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
<https://www.cs.helsinki.fi/u/ukkonen/SuffixT1withFigs.pdf>
> > [2] Suffix Trees and Suffix Arrays:
> > http://web.cs.iastate.edu/~cs548/suffix.pdf
<http://web.cs.iastate.edu/%7Ecs548/suffix.pdf>
> > [3] Extended Application of Suffix Trees to Data Compression:
> > http://www.larsson.dogma.net/dccpaper.pdf
<http://www.larsson.dogma.net/dccpaper.pdf>
> >
> >
> > Thanks for reading,
> > Jessica
> >
> > _______________________________________________
> > LLVM Developers mailing list
> > llvm-dev at lists.llvm.org <mailto:llvm-dev at lists.llvm.org>
> > http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
<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 <mailto:llvm-dev at lists.llvm.org>
> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
<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 <mailto:llvm-dev at lists.llvm.org>
> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
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Daniel Berlin via llvm-dev
2016-Aug-27 04:06 UTC
[llvm-dev] [RFC] Interprocedural MIR-level outlining pass
FWIW: I'm with quentin. Without a good value numbering analysis, this is a hard problem. 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/ >> MachineOutliner.h >> > >> > * Suffix tree: >> > https://github.com/ornata/llvm/blob/master/include/llvm/ >> ADT/SuffixTree.h >> > >> > * TerminatedString and TerminatedStringList: >> > https://github.com/ornata/llvm/blob/master/include/llvm/ >> ADT/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 > >-------------- next part -------------- An HTML attachment was scrubbed... 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Hal Finkel via llvm-dev
2016-Aug-27 04:44 UTC
[llvm-dev] [RFC] Interprocedural MIR-level outlining pass
----- Original Message -----> 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. 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. -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/MachineOutliner.h > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > * Suffix tree: > > > > > > > > > > > > > > > > https://github.com/ornata/llvm/blob/master/include/llvm/ADT/SuffixTree.h > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > * TerminatedString and TerminatedStringList: > > > > > > > > > > > > > > > > https://github.com/ornata/llvm/blob/master/include/llvm/ADT/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 -------------- next part -------------- An HTML attachment was scrubbed... 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