llvm dev - Mar 2020 - [GSOC] "Project: Improve inter-procedural analyses and optimisations"

Hi Fahad,

> > Improve dynamic memory related capabilities of Attributor. For example
> Improve HeapToStackConversions. Maybe such deductions can help safety
> (dis)provers. For example, can we improve the use-after-free bug detection
> using some attributes?
> Stefan should know more about H2S. Regarding the use-after-free, I
don't
> think there's currently any plans for it directly, but they can be I
assume.

You are somewhat right. However, H2S is not about 'use-after-free' bug
detection, but rather its prevention. We already do this, see example
<https://godbolt.org/z/HgrC7H>.

In the rest of this post I'll try to help you familiarize yourself with
the
> Attributor and maybe answer your questions.
> Johannes can then give you specific things to do to get started.

In the meantime you could look at some TODOs in the Attributor itself and
try those you see fit.

If you have any questions, don't hesitate to ask.

-stefan

On Fri, Mar 13, 2020 at 10:14 PM Stefanos Baziotis <
stefanos.baziotis at gmail.com> wrote:
> Hi Fahad,
>
> We're all happy to see you being interested in LLVM! More so in the
> Attributor! I'm a relatively new contributor so I
> think I can help. Please note that the Attributor, apart from Johannes
> (who CC'd), has at least another 2 great
> contributors, Hideto and Stefan (who I also CC'd). They were among the
> initial creators.
>
> In the rest of this post I'll try to help you familiarize yourself with
> the Attributor and maybe answer your questions.
> Johannes can then give you specific things to do to get started.
>
> Starting off, understanding the theory of data-flow analysis can help.
I'd
> say don't get too hang up on it, you just
> have to understand the idea of fix-point analyses.
>
> I don't how much you know about the Attributor, so I'll defer a too
long
> (or too beginner) description because you might already know
> a lot of things. You can of course any specific questions you want:
> A summary is:
> The Attributor tries to deduce attributes in different points of an LLVM
> IR program (you can see that in the video).
> The deduction of these attributes is inter-connected, which is the whole
> point of the Attributor. The attributes
> "ask" one another for information. For example, one attribute
tries to see
> if a load loads from null pointer.
> But the pointer operand might be non-constant (like %v in LLVM IR). Well,
> another attribute, whose job is to do value simplification
> (i.e. constant folding / propagation etc.) might have folded that (%v)
> into the constant null. So, the former can ask him.
> These connections give the power and the complexity.
>
> The attributes have a state, that changes. When the state stops changing,
> it has reached a fixpoint, at which point
> the deduction of it stops. From the initialization of the attribute until
> a fixpoint is reached, the state changes
> in updates (called updateImpl() in the source code). This is where
> attributes try to deduce new things, ask one another
> and eventually try to reach a fixpoint.
>
> Finally, a fixpoint can be enforced. Because if we for some reason never
> stop changing, it would run forever.
> Note however that attributes should be programmed in a way that fixpoint
> should be able to be reached
> (This is where theory might help a little).
>
> I'd suggest that you try to run the Attributor and follow a specific
> attribute's updates and see what it tries to deduce.
> That is, see its updateImpl(). With a couple of prints you can get a good
> idea of what it does and what info it
> gets from other attributes (and when it stops). You can of course ask us
> if you're interested in a specific one, if
> there's something you don't understand etc.
>
> Now, to (try to) answer your questions and hopefully other people can help.
> > How Attributor can help for standard inter-procedural and
> intra-procedural analysis passes of LLVm. I’ve seen the tutorial [4]. I
> would like to discuss ways of improving other optimization passes similarly
> (or some examples which have already been implemented).
>
> The Attributor AFAIK is self-contained. It's not in
"production" yet and
> so it's not connected with other passes. At this point, LLVM is focused
on
> heavy inlining, which while very useful, you'll lose a lot of the
> interprocedural information.
> Note that there are other transforms that do Inter-Procedural Optimization
> (https://github.com/llvm/llvm-project/tree/master/llvm/lib/Transforms/IPO)
> but they don't follow the idea of the Attributor.
> But they might follow a fix-point analysis.
>
> > Improve dynamic memory related capabilities of Attributor. For example
> Improve HeapToStackConversions. Maybe such deductions can help safety
> (dis)provers. For example, can we improve the use-after-free bug detection
> using some attributes?
> Stefan should know more about H2S. Regarding the use-after-free, I
don't
> think there's currently any plans for it directly, but they can be I
assume.
>
> > Improve Liveness related capabilities of Attributor. Again I want to
> consider whether some attribute deduction can help liveness (dis)provers.
> For example NoReturn, WillReturn can be improved. I am sure these 2
> attributes do not cover all the cases as it is an undecidable problem. But
> I was wondering whether there is room for improvement in their deduction
> mechanism. Liveness is certainly something that we're currently trying
to
> improve and I don't think we'll ever stop. Most of the attributes
interact
> with the deadness attribute (AAIsDead) both for asking it info and
> providing it info (i.e. the undefined-behavior attribute hopefully will at
> some point be able to tell AAIsDead that a block is dead because it
> contains UB). > Is there any attribute that tells whether a function has
> side-effects (does it always gives the same output for the same input? Or
> does it affect some global variable directly or indirectly?)? No AFAIK,
> although you might be interested in this:
> https://reviews.llvm.org/D74691#1887983
>
> I hope this was helpful! Don't hesitate to ask any questions.
>
> Kind regards,
> Stefanos Baziotis
>
> Στις Παρ, 13 Μαρ 2020 στις 10:25 μ.μ., ο/η Fahad Nayyar via llvm-dev <
> llvm-dev at lists.llvm.org> έγραψε:
>
>> Hi all,
>>
>> My name is Fahad Nayyar. I am an undergraduate student from India.
>>
>> I am interested to participate in GSOC under the project “Improve
>> inter-procedural analyses and optimizations”.
>>
>> I have been using LLVM for the past 8 months. I have written various
>> intra-procedural analysis in LLVM as FunctionPass for my course
projects
>> and research projects. But I’ve not contributed to the LLVM community
yet.
>> I am very excited to contribute to LLVM!
>>
>> I am not too familiar with the inter-procedural analysis infrastructure
>> of LLVM. I have written small toy inter-procedural dataflow analysis
(like
>> taint analysis, reaching definitions, etc) for JAVA programs using SOOT
>> tool *[5].* I am familiar with the theory of inter-procedural analysis
>> (I’ve read some chapters of  [1],  [2] and [3] for this).
>>
>> I am trying to understand the LLVM’s Attributor framework. I am
>> interested in these 3 aspects:
>>
>>    1.
>>
>>    How Attributor can help for standard inter-procedural and
>>    intra-procedural analysis passes of LLVm. I’ve seen the tutorial
[4].
>>    I would like to discuss ways of improving other optimization passes
>>    similarly (or some examples which have already been implemented).
>>    2.
>>
>>    Improve dynamic memory related capabilities of Attributor. For
>>    example Improve HeapToStackConversions. Maybe such deductions can
>>    help safety (dis)provers. For example, can we improve the
use-after-free
>>    bug detection using some attributes?
>>    3.
>>
>>    Improve Liveness related capabilities of Attributor. Again I want to
>>    consider whether some attribute deduction can help liveness
(dis)provers.
>>    For example NoReturn, WillReturn can be improved. I am sure these 2
>>    attributes do not cover all the cases as it is an undecidable
problem. But
>>    I was wondering whether there is room for improvement in their
deduction
>>    mechanism.
>>    4.
>>
>>    Can we optimize the attribute deduction algorithm to reduce compile
>>    time?
>>    5.
>>
>>    Is there any attribute that tells whether a function has
side-effects
>>    (does it always gives the same output for the same input? Or does it
affect
>>    some global variable directly or indirectly?)?
>>
>>
>> It would be great if Johannes can provide me some TODOs before
submitting
>> my proposal. Also please tell some specific IPO improvement goals which
you
>> have in mind for this project. I would be most interested in
memory-related
>> attributes, liveness deductions from attributes and measurable better
IPO
>> using attribute deduction.
>>
>> Thanks and Regards.
>>
>> References:
>>
>> [1] Principles of Program Analysis.
>> <https://www.springer.com/gp/book/9783540654100>
>>
>> [2] Data Flow Analysis: Theory and Practice.
>> <https://dl.acm.org/doi/book/10.5555/1592955>
>>
>> [3] Static Program Analysis.
<https://cs.au.dk/~amoeller/spa/spa.pdf>
>>
>> [4] 2019 LLVM Developers’ Meeting: J. Doerfert “The Attributor: A
>> Versatile Inter-procedural Fixpoint.."
>> <https://www.youtube.com/watch?v=HVvvCSSLiTw>
>> [5] Soot - A Java optimization framework
<https://github.com/Sable/soot>
>>
>>
>>
>> _______________________________________________
>> LLVM Developers mailing list
>> llvm-dev at lists.llvm.org
>> https://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>>
>
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Dear Stefan and Stefanos,

Thanks for your suggestions!
> I'd suggest that you try to run the Attributor and follow a specific
attribute's updates and see what it tries to deduce. That is, see its
updateImpl(). With a couple of prints you can get a good idea of what it
does and what info it gets from other attributes (and when it stops).

I tried to do this for the NoUnwind attribute. I printed getState(), i
sAssumedNoUnwind(), isKnownNoUnwind() in updateImpl method of classes
AANoUnwind and AANoUnwindCallSite. I run the tests in nounwind.ll
(/llvm/test/Transforms/Attributor/nounwind.ll).
I used this command to run the test: “opt -attributor
-attributor-disable=false nounwind.ll -S &> nounwind_out.ll”. But After
seeing the output I was not able to understand how the attribute is
changing for the tests. Its status was almost constant every time updateimp was
called. Please tell me what other things should I try to print to better
observe how the NoUnwind attribute is changing over the iterations of fix
point analysis. Also please verify whether I am using the correct command
to run the tests.
> Also, probably this will be a very interesting panel discussion for you:
https://www.youtube.com/watch?v=cC2cspQgSxM

Thanks for suggesting this! I watched the video and now I understand the
pros and cons of inlining. But I still think that It would take me a while
before I can come up with a very good example demonstrating the use of of
of the Attribues in some IPO pass. I know how in [1] Johaanes explained the
use of MaxObjSize and Dereferenceable in the AliasAnalysis. But I would be
happy if I could come up with some even better example.
> You are somewhat right. However, H2S is not about 'use-after-free'
bug
detection, but rather its prevention. We already do this, see example.
<https://godbolt.org/z/HgrC7H>

Thanks for sharing the example. Just for clarification, was this example
demonstrating the point that we can automatically correct use-after-free
bugs using attributes? If yes, then I didn’t understand how and which
attribute helped in this correction? Also is it not wrong to change the IR
as in this example? Replacing %1 = tail call noalias i8* @malloc(i64 4) ;
tail call void @no_sync_func(i8* %1) with  %1 = alloca i8, i64 4 solved the
use-after-free bug, but doesn’t it also change the semantic of the program?
> In the meantime you could look at some TODOs in the Attributor itself and
try those you see fit.

I looked up some of the TODOs. I found AAReachability a very interesting
attribute. I can start with TODO at line no. 2605  // TODO: Return the
number of reachable queries. I can work towards this TODO. But I first want
your advice on whether it looks doable for me. I can see that
implementation of AAReachability attribute is not complete yet. I can try
to learn more about it from D70233 <https://reviews.llvm.org/D70233>and
D71617 <https://reviews.llvm.org/D71617>.

I am trying to get more familiar with Attributor’s code. Since the code is
very large right now, I thought to refer to some of the very initial
patches of attributor (D59918, <https://reviews.llvm.org/D59918> D60012
<https://reviews.llvm.org/D60012>, D63379
<https://reviews.llvm.org/D63379>).
I believe that by looking at these three I can get a better idea of the
framework as a whole. Please suggest if this is a good idea or not. Also
please suggest any other way by which I can improve my understanding of the
code.

I can see that Johanned have put up some issues for GSOC aspirants. I think
that [2] <https://github.com/llvm/llvm-project/issues/179> ([Attributor]
Cleanup and upstream `Attribute::MaxObjectSize`) will be a very good issue
for me, It seems doable and I can get familiar with the whole process of
writing a patch for an issue. How should I indicate to the community that I
have started working towards this issue (should I comment on the issue page
on github?)? I can try to work on AAReachability TODO after solving this
issue.

Thanks and Regards


References

[1] https://youtu.be/HVvvCSSLiTw
[2] https://github.com/llvm/llvm-project/issues/179




On Sat, Mar 14, 2020 at 4:12 PM Stefan Stipanovic <stefomeister at
gmail.com>
wrote:
> Hi Fahad,
>
>
>> > Improve dynamic memory related capabilities of Attributor. For
example
>> Improve HeapToStackConversions. Maybe such deductions can help safety
>> (dis)provers. For example, can we improve the use-after-free bug
>> detection using some attributes?
>> Stefan should know more about H2S. Regarding the use-after-free, I
don't
>> think there's currently any plans for it directly, but they can be
I assume.
>
>
> You are somewhat right. However, H2S is not about 'use-after-free'
bug
> detection, but rather its prevention. We already do this, see example
> <https://godbolt.org/z/HgrC7H>.
>
> In the rest of this post I'll try to help you familiarize yourself with
>> the Attributor and maybe answer your questions.
>> Johannes can then give you specific things to do to get started.
>
>
> In the meantime you could look at some TODOs in the Attributor itself and
> try those you see fit.
>
> If you have any questions, don't hesitate to ask.
>
> -stefan
>
> On Fri, Mar 13, 2020 at 10:14 PM Stefanos Baziotis <
> stefanos.baziotis at gmail.com> wrote:
>
>> Hi Fahad,
>>
>> We're all happy to see you being interested in LLVM! More so in the
>> Attributor! I'm a relatively new contributor so I
>> think I can help. Please note that the Attributor, apart from Johannes
>> (who CC'd), has at least another 2 great
>> contributors, Hideto and Stefan (who I also CC'd). They were among
the
>> initial creators.
>>
>> In the rest of this post I'll try to help you familiarize yourself
with
>> the Attributor and maybe answer your questions.
>> Johannes can then give you specific things to do to get started.
>>
>> Starting off, understanding the theory of data-flow analysis can help.
>> I'd say don't get too hang up on it, you just
>> have to understand the idea of fix-point analyses.
>>
>> I don't how much you know about the Attributor, so I'll defer a
too long
>> (or too beginner) description because you might already know
>> a lot of things. You can of course any specific questions you want:
>> A summary is:
>> The Attributor tries to deduce attributes in different points of an
LLVM
>> IR program (you can see that in the video).
>> The deduction of these attributes is inter-connected, which is the
whole
>> point of the Attributor. The attributes
>> "ask" one another for information. For example, one attribute
tries to
>> see if a load loads from null pointer.
>> But the pointer operand might be non-constant (like %v in LLVM IR).
Well,
>> another attribute, whose job is to do value simplification
>> (i.e. constant folding / propagation etc.) might have folded that (%v)
>> into the constant null. So, the former can ask him.
>> These connections give the power and the complexity.
>>
>> The attributes have a state, that changes. When the state stops
changing,
>> it has reached a fixpoint, at which point
>> the deduction of it stops. From the initialization of the attribute
until
>> a fixpoint is reached, the state changes
>> in updates (called updateImpl() in the source code). This is where
>> attributes try to deduce new things, ask one another
>> and eventually try to reach a fixpoint.
>>
>> Finally, a fixpoint can be enforced. Because if we for some reason
never
>> stop changing, it would run forever.
>> Note however that attributes should be programmed in a way that
fixpoint
>> should be able to be reached
>> (This is where theory might help a little).
>>
>> I'd suggest that you try to run the Attributor and follow a
specific
>> attribute's updates and see what it tries to deduce.
>> That is, see its updateImpl(). With a couple of prints you can get a
good
>> idea of what it does and what info it
>> gets from other attributes (and when it stops). You can of course ask
us
>> if you're interested in a specific one, if
>> there's something you don't understand etc.
>>
>> Now, to (try to) answer your questions and hopefully other people can
>> help.
>> > How Attributor can help for standard inter-procedural and
>> intra-procedural analysis passes of LLVm. I’ve seen the tutorial [4]. I
>> would like to discuss ways of improving other optimization passes
similarly
>> (or some examples which have already been implemented).
>>
>> The Attributor AFAIK is self-contained. It's not in
"production" yet and
>> so it's not connected with other passes. At this point, LLVM is
focused on
>> heavy inlining, which while very useful, you'll lose a lot of the
>> interprocedural information.
>> Note that there are other transforms that do Inter-Procedural
>> Optimization (
>>
https://github.com/llvm/llvm-project/tree/master/llvm/lib/Transforms/IPO)
>> but they don't follow the idea of the Attributor.
>> But they might follow a fix-point analysis.
>>
>> > Improve dynamic memory related capabilities of Attributor. For
example
>> Improve HeapToStackConversions. Maybe such deductions can help safety
>> (dis)provers. For example, can we improve the use-after-free bug
>> detection using some attributes?
>> Stefan should know more about H2S. Regarding the use-after-free, I
don't
>> think there's currently any plans for it directly, but they can be
I assume.
>>
>> > Improve Liveness related capabilities of Attributor. Again I want
to
>> consider whether some attribute deduction can help liveness
(dis)provers.
>> For example NoReturn, WillReturn can be improved. I am sure these 2
>> attributes do not cover all the cases as it is an undecidable problem.
But
>> I was wondering whether there is room for improvement in their
deduction
>> mechanism. Liveness is certainly something that we're currently
trying to
>> improve and I don't think we'll ever stop. Most of the
attributes interact
>> with the deadness attribute (AAIsDead) both for asking it info and
>> providing it info (i.e. the undefined-behavior attribute hopefully will
at
>> some point be able to tell AAIsDead that a block is dead because it
>> contains UB). > Is there any attribute that tells whether a function
has
>> side-effects (does it always gives the same output for the same input?
>> Or does it affect some global variable directly or indirectly?)? No
AFAIK,
>> although you might be interested in this:
>> https://reviews.llvm.org/D74691#1887983
>>
>> I hope this was helpful! Don't hesitate to ask any questions.
>>
>> Kind regards,
>> Stefanos Baziotis
>>
>> Στις Παρ, 13 Μαρ 2020 στις 10:25 μ.μ., ο/η Fahad Nayyar via llvm-dev
<
>> llvm-dev at lists.llvm.org> έγραψε:
>>
>>> Hi all,
>>>
>>> My name is Fahad Nayyar. I am an undergraduate student from India.
>>>
>>> I am interested to participate in GSOC under the project “Improve
>>> inter-procedural analyses and optimizations”.
>>>
>>> I have been using LLVM for the past 8 months. I have written
various
>>> intra-procedural analysis in LLVM as FunctionPass for my course
projects
>>> and research projects. But I’ve not contributed to the LLVM
community yet.
>>> I am very excited to contribute to LLVM!
>>>
>>> I am not too familiar with the inter-procedural analysis
infrastructure
>>> of LLVM. I have written small toy inter-procedural dataflow
analysis (like
>>> taint analysis, reaching definitions, etc) for JAVA programs using
SOOT
>>> tool *[5].* I am familiar with the theory of inter-procedural
analysis
>>> (I’ve read some chapters of  [1],  [2] and [3] for this).
>>>
>>> I am trying to understand the LLVM’s Attributor framework. I am
>>> interested in these 3 aspects:
>>>
>>>    1.
>>>
>>>    How Attributor can help for standard inter-procedural and
>>>    intra-procedural analysis passes of LLVm. I’ve seen the tutorial
[4].
>>>    I would like to discuss ways of improving other optimization
passes
>>>    similarly (or some examples which have already been
implemented).
>>>    2.
>>>
>>>    Improve dynamic memory related capabilities of Attributor. For
>>>    example Improve HeapToStackConversions. Maybe such deductions
can
>>>    help safety (dis)provers. For example, can we improve the
use-after-free
>>>    bug detection using some attributes?
>>>    3.
>>>
>>>    Improve Liveness related capabilities of Attributor. Again I
want to
>>>    consider whether some attribute deduction can help liveness
(dis)provers.
>>>    For example NoReturn, WillReturn can be improved. I am sure
these 2
>>>    attributes do not cover all the cases as it is an undecidable
problem. But
>>>    I was wondering whether there is room for improvement in their
deduction
>>>    mechanism.
>>>    4.
>>>
>>>    Can we optimize the attribute deduction algorithm to reduce
compile
>>>    time?
>>>    5.
>>>
>>>    Is there any attribute that tells whether a function has
side-effects
>>>    (does it always gives the same output for the same input? Or
does it affect
>>>    some global variable directly or indirectly?)?
>>>
>>>
>>> It would be great if Johannes can provide me some TODOs before
>>> submitting my proposal. Also please tell some specific IPO
improvement
>>> goals which you have in mind for this project. I would be most
interested
>>> in memory-related attributes, liveness deductions from attributes
and
>>> measurable better IPO using attribute deduction.
>>>
>>> Thanks and Regards.
>>>
>>> References:
>>>
>>> [1] Principles of Program Analysis.
>>> <https://www.springer.com/gp/book/9783540654100>
>>>
>>> [2] Data Flow Analysis: Theory and Practice.
>>> <https://dl.acm.org/doi/book/10.5555/1592955>
>>>
>>> [3] Static Program Analysis.
<https://cs.au.dk/~amoeller/spa/spa.pdf>
>>>
>>> [4] 2019 LLVM Developers’ Meeting: J. Doerfert “The Attributor: A
>>> Versatile Inter-procedural Fixpoint.."
>>> <https://www.youtube.com/watch?v=HVvvCSSLiTw>
>>> [5] Soot - A Java optimization framework
<https://github.com/Sable/soot>
>>>
>>>
>>>
>>> _______________________________________________
>>> LLVM Developers mailing list
>>> llvm-dev at lists.llvm.org
>>> https://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>>>
>>
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Hi Farad,
> I tried to do this for the NoUnwind attribute Hmm, I don't have
experience with this attribute but it seems like a good starting point
since it doesn't do much. First of all, be sure that you run with: opt
-passes=attributor -attributor-disable=false This uses the new pass manager
which is another discussion. Now, to the point: If you open nounwind.ll, it
has a bunch of test cases and I don't think it's a good idea to run
Attributor in all of them at first. So, break it into individual tests.
First of all, note that the Attributor follows an optimistic path to
attribute deduction. That is, you always start assuming that an attribute
is valid until you have info that it isn't. Seeing TEST 1 should be
relatively obvious that it doesn't have something that breaks the initial
assumption, that's why you see no change in state between calls to
updateImpl(). But now we have to dig deeper: What can break our initial
assumption (which is that a function does not throw) in the case of
NoUnwind? You see in the topmost updateImpl() that they're a bunch Opcodes.
Those are instructions (inside our function) that can potentially break our
initial assumption (e.g. call to a function that either we know it throws
or at least it is not guaranteed that it doesn't). In the updateImpl(),
using checkForAllInstructions, we loop through all those instructions and
call for each one the predicate CheckForNoUnwind. Note a couple of things:
- TEST 1 has no such instructions whatsoever so if you put a print inside
the predicate, you'll see nothing. - You can see that the predicate returns
a boolean value. If it's true, we continue to the next instruction,
otherwise we stop. If we make it through all of them,
checkForAllInstructions() returns true. Otherwise false. The predicate
checks if any instruction breaks our assumption (we'll see shortly how). If
it does, we immediately indicate pessimistic fixpoint. What about TEST 2
and 3 ? Those 2 functions have a call inside but if you put a print inside
the predicate, you'll see again nothing. The reason for that brings us to
an important part of the Attributor and that is that "deadness" (and
the
relative attribute) is very important. checkForAllInstructions() will only
go through instructions that are considered live. The 2 calls are not
considered because another part of the Attributor (which is out of topic
right now) has (somewhat) deduced that they go in an endless recursion. If
you run the Attributor with these 2 functions you'll see another important
point. Specifically that the function bodies have only an `unreachable`
instruction inside. That is, the attributor not only deduces (and provides)
info through attributes but it also transforms code. In this case it
changed the function bodies to unreachable. Finally, I think it's
interesting to see TEST 4: You see that it calls a function that we don't
know it doesn't throw. This should break our assumption. And it does.
Inside the topmost updateImpl() and inside the predicate, if you put a
print, you'll see the call (e.g. dbgs() << I << "\n").
We ask I.mayThrow().
Note that mayThrow() will return false in the case that we're somehow sure
that the instruction does not throw. In this case the instruction is a
call, so it will return true if we're sure that the called function does
not throw. But we're not, so we move forward. What then happens is a little
bit weird but it basically AANoUnwind asks AANoUnwindCallSite for info
because this instruction is a call site. Attributes ask one another and
this is very important in the Attributor because one's information is
useful in another. We do it with getAAFor. Without getting into too much
info, the other attribute says that it's not assumed unwind so we indicate
pessimistic fixpoint (the reality is that the order of calls between the
attributes is reverse, but again, out of topic). I hope that gave you a
better understanding! > I know how in [1] Johaanes explained the use of
MaxObjSize and Dereferenceable in the AliasAnalysis. But I would be happy
if I could come up with some even better example. As you said, that'll
probably take some time but that's ok There are opportunities everywhere.
For example, consider this: https://godbolt.org/z/HFWo_J It's a for loop
that does a load inside from %p. The load seems to be invariant, we could
move it out of the loop. -licm in the cmd arguments means it invokes the
Loop-Invariant Code Motion pass, which does such things. But it doesn't
move the load out. The reason for that is that consider the case where %n
== 0 and %p == null. In the initial code, we would never get into the loop
and we would not have a trap. While, with this transformation, we will have
and thus, we just changed the initial behavior. So, the transformation is
not done. However, if you put dereferenceable(4) attribute in %p, it will
be done. Because now you now you can certainly dereference. So, attribute
info is useful in ways we may not consider :) > I can start with TODO at
line no. 2605  // TODO: Return the number of reachable queries. I'm not
familiar with it. Currently it doesn't seem to do anything but I may miss
something. I suppose what it asks is to track how many queries to this
attribute have been done by outside users which should be easy. > Since the
code is very large right now, I thought to refer to some of the very
initial patches of attributor Maybe, I don't know. But I assume things will
have changed from then and you may get lost. I'd start by doing diagrams
about how different parts of the code interact with each other (e.g. where
does the Attributor start? what does it call then? how are attributes
created? etc.) When starting out, these things might not be important to
tackle. But they helped me. > How should I indicate to the community that I
have started working towards this issue (should I comment on the issue page
on github?)? I can try to work on AAReachability TODO after solving this
issue.
You can write it in the Github comments. I don't think you can / need to do
something else. Kind regards, Stefanos Baziotis

Στις Δευ, 16 Μαρ 2020 στις 12:12 π.μ., ο/η Fahad Nayyar <
fahad17049 at iiitd.ac.in> έγραψε:
> Dear Stefan and Stefanos,
>
> Thanks for your suggestions!
>
> > I'd suggest that you try to run the Attributor and follow a
specific
> attribute's updates and see what it tries to deduce. That is, see its
> updateImpl(). With a couple of prints you can get a good idea of what it
> does and what info it gets from other attributes (and when it stops).
>
> I tried to do this for the NoUnwind attribute. I printed getState(), i
> sAssumedNoUnwind(), isKnownNoUnwind() in updateImpl method of classes
> AANoUnwind and AANoUnwindCallSite. I run the tests in nounwind.ll
(/llvm/test/Transforms/Attributor/nounwind.ll).
> I used this command to run the test: “opt -attributor
> -attributor-disable=false nounwind.ll -S &> nounwind_out.ll”. But
After
> seeing the output I was not able to understand how the attribute is
> changing for the tests. Its status was almost constant every time updateimp
> was called. Please tell me what other things should I try to print to
> better observe how the NoUnwind attribute is changing over the iterations
> of fix point analysis. Also please verify whether I am using the correct
> command to run the tests.
>
> > Also, probably this will be a very interesting panel discussion for
you:
> https://www.youtube.com/watch?v=cC2cspQgSxM
>
> Thanks for suggesting this! I watched the video and now I understand the
> pros and cons of inlining. But I still think that It would take me a while
> before I can come up with a very good example demonstrating the use of of
> of the Attribues in some IPO pass. I know how in [1] Johaanes explained
> the use of MaxObjSize and Dereferenceable in the AliasAnalysis. But I
> would be happy if I could come up with some even better example.
>
> > You are somewhat right. However, H2S is not about
'use-after-free' bug
> detection, but rather its prevention. We already do this, see example.
> <https://godbolt.org/z/HgrC7H>
>
> Thanks for sharing the example. Just for clarification, was this example
> demonstrating the point that we can automatically correct use-after-free
> bugs using attributes? If yes, then I didn’t understand how and which
> attribute helped in this correction? Also is it not wrong to change the IR
> as in this example? Replacing %1 = tail call noalias i8* @malloc(i64 4)
> ;  tail call void @no_sync_func(i8* %1) with  %1 = alloca i8, i64 4 solved
> the use-after-free bug, but doesn’t it also change the semantic of the
> program?
>
> > In the meantime you could look at some TODOs in the Attributor itself
> and try those you see fit.
>
> I looked up some of the TODOs. I found AAReachability a very interesting
> attribute. I can start with TODO at line no. 2605  // TODO: Return the
> number of reachable queries. I can work towards this TODO. But I first
> want your advice on whether it looks doable for me. I can see that
> implementation of AAReachability attribute is not complete yet. I can try
> to learn more about it from D70233
<https://reviews.llvm.org/D70233>and
> D71617 <https://reviews.llvm.org/D71617>.
>
> I am trying to get more familiar with Attributor’s code. Since the code is
> very large right now, I thought to refer to some of the very initial
> patches of attributor (D59918, <https://reviews.llvm.org/D59918>
D60012
> <https://reviews.llvm.org/D60012>, D63379
> <https://reviews.llvm.org/D63379>). I believe that by looking at
these
> three I can get a better idea of the framework as a whole. Please suggest
> if this is a good idea or not. Also please suggest any other way by which I
> can improve my understanding of the code.
>
> I can see that Johanned have put up some issues for GSOC aspirants. I
> think that [2] <https://github.com/llvm/llvm-project/issues/179>
([Attributor]
> Cleanup and upstream `Attribute::MaxObjectSize`) will be a very good
> issue for me, It seems doable and I can get familiar with the whole process
> of writing a patch for an issue. How should I indicate to the community
> that I have started working towards this issue (should I comment on the
> issue page on github?)? I can try to work on AAReachability TODO after
> solving this issue.
>
> Thanks and Regards
>
>
> References
>
> [1] https://youtu.be/HVvvCSSLiTw
> [2] https://github.com/llvm/llvm-project/issues/179
>
>
>
>
> On Sat, Mar 14, 2020 at 4:12 PM Stefan Stipanovic <stefomeister at
gmail.com>
> wrote:
>
>> Hi Fahad,
>>
>>
>>> > Improve dynamic memory related capabilities of Attributor. For
example
>>> Improve HeapToStackConversions. Maybe such deductions can help
safety
>>> (dis)provers. For example, can we improve the use-after-free bug
>>> detection using some attributes?
>>> Stefan should know more about H2S. Regarding the use-after-free, I
don't
>>> think there's currently any plans for it directly, but they can
be I assume.
>>
>>
>> You are somewhat right. However, H2S is not about
'use-after-free' bug
>> detection, but rather its prevention. We already do this, see example
>> <https://godbolt.org/z/HgrC7H>.
>>
>> In the rest of this post I'll try to help you familiarize yourself
with
>>> the Attributor and maybe answer your questions.
>>> Johannes can then give you specific things to do to get started.
>>
>>
>> In the meantime you could look at some TODOs in the Attributor itself
and
>> try those you see fit.
>>
>> If you have any questions, don't hesitate to ask.
>>
>> -stefan
>>
>> On Fri, Mar 13, 2020 at 10:14 PM Stefanos Baziotis <
>> stefanos.baziotis at gmail.com> wrote:
>>
>>> Hi Fahad,
>>>
>>> We're all happy to see you being interested in LLVM! More so in
the
>>> Attributor! I'm a relatively new contributor so I
>>> think I can help. Please note that the Attributor, apart from
Johannes
>>> (who CC'd), has at least another 2 great
>>> contributors, Hideto and Stefan (who I also CC'd). They were
among the
>>> initial creators.
>>>
>>> In the rest of this post I'll try to help you familiarize
yourself with
>>> the Attributor and maybe answer your questions.
>>> Johannes can then give you specific things to do to get started.
>>>
>>> Starting off, understanding the theory of data-flow analysis can
help.
>>> I'd say don't get too hang up on it, you just
>>> have to understand the idea of fix-point analyses.
>>>
>>> I don't how much you know about the Attributor, so I'll
defer a too long
>>> (or too beginner) description because you might already know
>>> a lot of things. You can of course any specific questions you want:
>>> A summary is:
>>> The Attributor tries to deduce attributes in different points of an
LLVM
>>> IR program (you can see that in the video).
>>> The deduction of these attributes is inter-connected, which is the
whole
>>> point of the Attributor. The attributes
>>> "ask" one another for information. For example, one
attribute tries to
>>> see if a load loads from null pointer.
>>> But the pointer operand might be non-constant (like %v in LLVM IR).
>>> Well, another attribute, whose job is to do value simplification
>>> (i.e. constant folding / propagation etc.) might have folded that
(%v)
>>> into the constant null. So, the former can ask him.
>>> These connections give the power and the complexity.
>>>
>>> The attributes have a state, that changes. When the state stops
>>> changing, it has reached a fixpoint, at which point
>>> the deduction of it stops. From the initialization of the attribute
>>> until a fixpoint is reached, the state changes
>>> in updates (called updateImpl() in the source code). This is where
>>> attributes try to deduce new things, ask one another
>>> and eventually try to reach a fixpoint.
>>>
>>> Finally, a fixpoint can be enforced. Because if we for some reason
never
>>> stop changing, it would run forever.
>>> Note however that attributes should be programmed in a way that
fixpoint
>>> should be able to be reached
>>> (This is where theory might help a little).
>>>
>>> I'd suggest that you try to run the Attributor and follow a
specific
>>> attribute's updates and see what it tries to deduce.
>>> That is, see its updateImpl(). With a couple of prints you can get
a
>>> good idea of what it does and what info it
>>> gets from other attributes (and when it stops). You can of course
ask us
>>> if you're interested in a specific one, if
>>> there's something you don't understand etc.
>>>
>>> Now, to (try to) answer your questions and hopefully other people
can
>>> help.
>>> > How Attributor can help for standard inter-procedural and
>>> intra-procedural analysis passes of LLVm. I’ve seen the tutorial
[4]. I
>>> would like to discuss ways of improving other optimization passes
similarly
>>> (or some examples which have already been implemented).
>>>
>>> The Attributor AFAIK is self-contained. It's not in
"production" yet and
>>> so it's not connected with other passes. At this point, LLVM is
focused on
>>> heavy inlining, which while very useful, you'll lose a lot of
the
>>> interprocedural information.
>>> Note that there are other transforms that do Inter-Procedural
>>> Optimization (
>>>
https://github.com/llvm/llvm-project/tree/master/llvm/lib/Transforms/IPO)
>>> but they don't follow the idea of the Attributor.
>>> But they might follow a fix-point analysis.
>>>
>>> > Improve dynamic memory related capabilities of Attributor. For
example
>>> Improve HeapToStackConversions. Maybe such deductions can help
safety
>>> (dis)provers. For example, can we improve the use-after-free bug
>>> detection using some attributes?
>>> Stefan should know more about H2S. Regarding the use-after-free, I
don't
>>> think there's currently any plans for it directly, but they can
be I assume.
>>>
>>> > Improve Liveness related capabilities of Attributor. Again I
want to
>>> consider whether some attribute deduction can help liveness
(dis)provers.
>>> For example NoReturn, WillReturn can be improved. I am sure these 2
>>> attributes do not cover all the cases as it is an undecidable
problem. But
>>> I was wondering whether there is room for improvement in their
deduction
>>> mechanism. Liveness is certainly something that we're currently
trying to
>>> improve and I don't think we'll ever stop. Most of the
attributes interact
>>> with the deadness attribute (AAIsDead) both for asking it info and
>>> providing it info (i.e. the undefined-behavior attribute hopefully
will at
>>> some point be able to tell AAIsDead that a block is dead because it
>>> contains UB). > Is there any attribute that tells whether a
function
>>> has side-effects (does it always gives the same output for the same
>>> input? Or does it affect some global variable directly or
indirectly?)? No
>>> AFAIK, although you might be interested in this:
>>> https://reviews.llvm.org/D74691#1887983
>>>
>>> I hope this was helpful! Don't hesitate to ask any questions.
>>>
>>> Kind regards,
>>> Stefanos Baziotis
>>>
>>> Στις Παρ, 13 Μαρ 2020 στις 10:25 μ.μ., ο/η Fahad Nayyar via
llvm-dev <
>>> llvm-dev at lists.llvm.org> έγραψε:
>>>
>>>> Hi all,
>>>>
>>>> My name is Fahad Nayyar. I am an undergraduate student from
India.
>>>>
>>>> I am interested to participate in GSOC under the project
“Improve
>>>> inter-procedural analyses and optimizations”.
>>>>
>>>> I have been using LLVM for the past 8 months. I have written
various
>>>> intra-procedural analysis in LLVM as FunctionPass for my course
projects
>>>> and research projects. But I’ve not contributed to the LLVM
community yet.
>>>> I am very excited to contribute to LLVM!
>>>>
>>>> I am not too familiar with the inter-procedural analysis
infrastructure
>>>> of LLVM. I have written small toy inter-procedural dataflow
analysis (like
>>>> taint analysis, reaching definitions, etc) for JAVA programs
using SOOT
>>>> tool *[5].* I am familiar with the theory of inter-procedural
analysis
>>>> (I’ve read some chapters of  [1],  [2] and [3] for this).
>>>>
>>>> I am trying to understand the LLVM’s Attributor framework. I am
>>>> interested in these 3 aspects:
>>>>
>>>>    1.
>>>>
>>>>    How Attributor can help for standard inter-procedural and
>>>>    intra-procedural analysis passes of LLVm. I’ve seen the
tutorial [4].
>>>>    I would like to discuss ways of improving other optimization
passes
>>>>    similarly (or some examples which have already been
implemented).
>>>>    2.
>>>>
>>>>    Improve dynamic memory related capabilities of Attributor.
For
>>>>    example Improve HeapToStackConversions. Maybe such
deductions can
>>>>    help safety (dis)provers. For example, can we improve the
use-after-free
>>>>    bug detection using some attributes?
>>>>    3.
>>>>
>>>>    Improve Liveness related capabilities of Attributor. Again I
want
>>>>    to consider whether some attribute deduction can help
liveness
>>>>    (dis)provers. For example NoReturn, WillReturn can be
improved. I
>>>>    am sure these 2 attributes do not cover all the cases as it
is an
>>>>    undecidable problem. But I was wondering whether there is
room for
>>>>    improvement in their deduction mechanism.
>>>>    4.
>>>>
>>>>    Can we optimize the attribute deduction algorithm to reduce
compile
>>>>    time?
>>>>    5.
>>>>
>>>>    Is there any attribute that tells whether a function has
>>>>    side-effects (does it always gives the same output for the
same
>>>>    input? Or does it affect some global variable directly or
indirectly?)?
>>>>
>>>>
>>>> It would be great if Johannes can provide me some TODOs before
>>>> submitting my proposal. Also please tell some specific IPO
improvement
>>>> goals which you have in mind for this project. I would be most
interested
>>>> in memory-related attributes, liveness deductions from
attributes and
>>>> measurable better IPO using attribute deduction.
>>>>
>>>> Thanks and Regards.
>>>>
>>>> References:
>>>>
>>>> [1] Principles of Program Analysis.
>>>> <https://www.springer.com/gp/book/9783540654100>
>>>>
>>>> [2] Data Flow Analysis: Theory and Practice.
>>>> <https://dl.acm.org/doi/book/10.5555/1592955>
>>>>
>>>> [3] Static Program Analysis.
<https://cs.au.dk/~amoeller/spa/spa.pdf>
>>>>
>>>> [4] 2019 LLVM Developers’ Meeting: J. Doerfert “The Attributor:
A
>>>> Versatile Inter-procedural Fixpoint.."
>>>> <https://www.youtube.com/watch?v=HVvvCSSLiTw>
>>>> [5] Soot - A Java optimization framework
>>>> <https://github.com/Sable/soot>
>>>>
>>>>
>>>>
>>>> _______________________________________________
>>>> LLVM Developers mailing list
>>>> llvm-dev at lists.llvm.org
>>>> https://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>>>>
>>>
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On 03/16, Fahad Nayyar wrote:
> I can see that Johanned have put up some issues for GSOC aspirants. I think
> that [2] <https://github.com/llvm/llvm-project/issues/179>
([Attributor]
> Cleanup and upstream `Attribute::MaxObjectSize`) will be a very good issue
> for me, It seems doable and I can get familiar with the whole process of
> writing a patch for an issue. How should I indicate to the community that I
> have started working towards this issue (should I comment on the issue page
> on github?)? I can try to work on AAReachability TODO after solving this
> issue.
I think the AAReachability TODO is being worked on but #179 not, as far
as I know. Would you be interested in taking this one? If so, make sure
to split it in multiple smaller patches, starting with one for the
LangRef.doc and the Attributor.

FIWI, I think we want the attribute to mean 1) below. I note this
because 2) is "the opposite" of dereferenceable.
  1) the underlying object is at most this large, where the pointer
     points to doesn't matter.
  2) the underlying object has at most X more dereferenceable bytes from
     this point forward.
I think we want 1) and later the opposite of 1) as well.

Does this make sense?

Cheers,
  Johannes
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