[flang-dev] [llvm-dev] About OpenMP dialect in MLIR
Vinay Madhusudan via flang-dev
flang-dev at lists.llvm.org
Sat Feb 15 08:22:01 PST 2020
Reply to Kiran Chandramohan:
> You are welcome to participate, provide feedback and criticism to change
the design as well as to contribute to the implementation.
Thank you Kiran.
> But the latest is what is there in the RFC in discourse.
I have used this as reference for the response.
> We did a study of a few constructs and clauses which was shared as mails
to flang-dev and the RFC. As we make progress and before implementation, we
will share further details.
> “ Yes, parallel and flush would be the next two constructs that we will
do.” -- from a comment in latest RFC
For the above mentioned reasons, I will try to restrict my reply to how the
“parallel (do)” construct would be lowered.
> If it is OK we can have further discussions in discourse as River points
out.
Given that the multiple components of the LLVM project, namely clang,
flang, MLIR and LLVM are involved, llvm-dev is probably a better place,
with a much wider audience, until it is clear how different components must
interact.
> It is the review for translation to LLVM IR that is in progress.
> “If we decide that the OpenMP construct (for e.g. collapse) can be
handled fully in MLIR and that is the best place to do it (based on
experiments) then we will not use the OpenMP IRBuilder for these constructs.”
-- latest RFC in discourse
If it is not finalized that the OpenMPIRBuilder will be used for all the
constructs, wouldn’t it be better to delay the submission of “translation
to LLVM IR” patch in MLIR? Lowering code will become inconsistent if the
OpenMPIRBuilder is used only for a few constructs and not for others.
Also, the patch does OpenMP dialect lowering *alongside* LLVM Dialect to
LLVM IR. This is different from most dialects which get directly lowered to
LLVM Dialect. I think lowering to LLVM Dialect would be a cleaner way if
OpenMPIRBuilder is not being considered for all constructs.
Mehdi also seems to have the same suggestion: “I agree that having dialect
lowering would be cleaner” in https://reviews.llvm.org/D72962
> Yes, the design has mildly changed over time to incorporate feedback.
But the latest is what is there in the RFC in discourse.
RFC fails to discuss the following (I have also mentioned some of them in
my reply to Johannes):
> The proposed plan involves a) lowering F18 AST with OpenMP directly to a
mix of OpenMP and FIR dialects. b) converting this finally to a mix of
OpenMP and LLVM dialects.
It is unclear in the RFC what other dialects are considered as supported
for OpenMP dialect (std, affine, vector, loop, etc) and how it would be
transformed, used and lowered from FIR to LLVM.
It becomes important to list down the various dialects / operations / types
supported for OpenMP (which is mainly defined for C, C++ and Fortran
programs. MLIR has a much wider scope.
It wouldn’t add much value for the proposed OpenMP dialect to be in the
MLIR tree if it cannot support at least the relevant standard dialect types
/ operations.
> We would like to take advantage of the transformations in cases that are
possible. FIR loops will be converted to affine/loop dialect. So the loop
inside an omp.do can be in these dialects as clarified in the discussion in
discourse and also shown in slide 20 of the fosdem presentation (links to
both below).
https://llvm.discourse.group/t/rfc-openmp-dialect-in-mlir/397/7?u=kiranchandramohan
https://fosdem.org/2020/schedule/event/llvm_flang/attachments/slides/3839/export/events/attachments/llvm_flang/slides/3839/flang_llvm_frontend.pdf
Although it is mentioned that the affine/ loop.for is used, following
things are unclear:
I am assuming that there will be lowering / conversion code in f18 repo
dialect from fir.do to loop.for / affine.for. Is it the case? If so, I
think it is worth mentioning it in the “sequential code flow
representation” in the RFC.
This raises the following questions.
1.
Which types are supported? Standard dialect types and FIR types?
For example, what types are used for Fortran arrays used inside OpenMP
regions? Is it std.memref OR Fortran array representation in FIR dialect
(fir.array?) OR both? Note that Fortran has support for column major
arrays. std.memref supports custom memory layouts. What custom layouts are
supported?
How would different non-scalar types in standard dialect be lowered to
LLVM IR and passed to OpenMP runtime calls? Can you please elaborate on
this?
The example provided in slide 20 of the fosdem presentation contains
“loop.for %j = %lb2 to %ub2 : !integer {“
But loop.for accepts “index” type. Not sure what type “!integer” represents
here.
1.
What are the different memory access operations which are supported
inside the OpenMP region and lowered to proper OpenMP runtime calls in LLVM
IR?
The possibilities are:
1.
affine.load / affine.store
2.
std.load / std.store
3.
FIR dialect memory access operations.
> I must also point out that the question of where to do loop
transformations is a topic we have not fully converged on. See the
following thread for discussions.
http://lists.llvm.org/pipermail/flang-dev/2019-September/000042.html
Looks like placement (MLIR / LLVM) of various transformations related to
OpenMP has not been finalized, from what I could infer from Johannes’s
reply and the below text in the latest RFC in discourse:
“So there exist some questions regarding where the optimisations should be
carried out. We will decide on which framework to choose only after some
experimentation.”
> i) we need to keep the loops separately so as to take advantage of
transformations that other dialects like affine/loop would provide.
1) Keeping the loops separate from the OpenMP operations will expose them
to the “regular” transformations passes in MLIR inside the OpenMP region.
Most of them are invalid or in-efficient for OpenMP operations.
Examples:
1.
Constant propagation example mentioned by Johannes in this thread. (omp
task shared(x))
2.
Loop (nest) transformations (permute / split / fuse / tile, etc) will
happen ignoring the surrounding OpenMP operations.
3.
Hoisting and sinking of various memory/ SSA values inside the OpenMP
region. This goes against the likes of “map”, “firstprivate”, shared, etc
clauses and more.
2) Various loop operations (loop.for, affine.for, fir.do) have (or will
have) different transformations/ optimization passes which are different
from one another.
Example:
1.
AffineLoopInvariantCodeMotion.cpp is different from
LoopInvariantCodeMotion.cpp.
2.
Other Loop transformation passes for affine.for
These loops also use different Types and memory access operations in
general for transformations. Example, most Affine dialect transformations
(if not all) work on affine.load and affine.store operations.
Supporting different loop operations means that there would be *OpenMP
specific transformations* for each one of them and also requires a way to
restrict each of them from existing transformations (when nested in OpenMP
constructs).
There would be different lowerings for different loop operations as well.
Example, affine.for and loop.for would have to be lowered to omp.do in
different ways.
>From slide 20 of fosdem presentation you mentioned, the LLVM + OpenMP
dialect representation is as follows:
------------------------------
Mlir.region(…) {
omp.parallel {
%ub3 = …
omp.do %i = 0 to %ub3 : !integer {
…
}
}
}
-------------------------------
Currently, the LLVM Dialect doesn’t contain a high level loop operation. It
is all based on CFG implementation.
Will omp.do follow the same structure (SizedRegion<1>) as loop.for? OR
there would be CFG for LLVM Dialect based loop operation?
Can you please mention how the OpenMP + LLVM dialect will look like for the
below parallel do construct?
integer :: i=1, k=10
integer :: a(10), b(10), c(10)
...
!$omp parallel do
do i = 1, k
if (i .ne. 1) *cycle*
c(i) = a(i) + b(i)
end do
!$omp end parallel do
print *,c
Thanks,
Vinay
On Fri, Feb 14, 2020 at 6:52 AM Kiran Chandramohan via llvm-dev <
llvm-dev at lists.llvm.org> wrote:
> Hello Vinay,
>
> Thanks for your mail about the OpenMP dialect in MLIR. Happy to know that
> you and several other groups are interested in the OpenMP dialect. At the
> outset, I must point out that the design is not set in stone and will
> change as we make progress. You are welcome to participate, provide
> feedback and criticism to change the design as well as to contribute to the
> implementation. I provide some clarifications and replies to your comments
> below. If it is OK we can have further discussions in discourse as River
> points out.
>
> 1. [May 2019] An OpenMPIRBuilder in LLVM was proposed for flang and clang
> frontends. Note that this proposal was before considering MLIR for FIR.
>
> A correction here. The proposal for OpenMPIRBuilder was made when MLIR was
> being considered for FIR.
> (i) Gary Klimowicz's minutes for Flang call in April 2019 mentions
> considering MLIR for FIR.
>
> http://lists.flang-compiler.org/pipermail/flang-dev_lists.flang-compiler.org/2019-April/000194.html
> (ii) My reply to Johaness's proposal in May 2019 mentions MLIR for FIR.
>
> http://lists.flang-compiler.org/pipermail/flang-dev_lists.flang-compiler.org/2019-May/000220.html
>
> b. Review of barrier construct is in progress:
> https://reviews.llvm.org/D72962
>
> Minor correction here. The addition of barrier construct was accepted and
> has landed (https://reviews.llvm.org/D7240
> <https://reviews.llvm.org/D72400>). It is the review for translation to
> LLVM IR that is in progress.
>
> It looks like the design has evolved over time and there is no one place
> which contains the latest design decisions that fits all the different
> pieces of the puzzle. I will try to deduce it from the above mentioned
> references. Please correct me If I am referring to anything which has
> changed.
>
> Yes, the design has mildly changed over time to incorporate feedback. But
> the latest is what is there in the RFC in discourse.
>
> For most OpenMP design discussions, FIR examples are used (as seen in (2)
> and (3)). The MLIR examples mentioned in the design only talks about FIR
> dialect and LLVM dialect.
>
> Our initial concern was how will all these pieces (FIR, LLVM Dialect,
> OpenMPIRBuilder, LLVM IR) fit together. Hence you see the prominence of FIR
> and LLVM dialect and more information about lowering/translation than
> transformations/optimisations.
>
> This completely ignores the likes of standard, affine (where most loop
> transformations are supposed to happen) and loop dialects.
>
> Adding to the reply above. We would like to take advantage of the
> transformations in cases that are possible. FIR loops will be converted to
> affine/loop dialect. So the loop inside an omp.do can be in these dialects
> as clarified in the discussion in discourse and also shown in slide 20 of
> the fosdem presentation (links to both below).
>
> https://llvm.discourse.group/t/rfc-openmp-dialect-in-mlir/397/7?u=kiranchandramohan
>
> https://fosdem.org/2020/schedule/event/llvm_flang/attachments/slides/3839/export/events/attachments/llvm_flang/slides/3839/flang_llvm_frontend.pdf
>
> I must also point out that the question of where to do loop
> transformations is a topic we have not fully converged on. See the
> following thread for discussions.
> http://lists.llvm.org/pipermail/flang-dev/2019-September/000042.html
>
> Is it the same omp.do operation which now contains the bounds and
> induction variables of the loop after the LLVM conversion?
>
> The point here is that i) we need to keep the loops separately so as to
> take advantage of transformations that other dialects like affine/loop
> would provide. ii) We will need the loop information while lowering the
> OpenMP do operation. For implementation, if reusing the same operation (in
> different contexts) is difficult then we can add a new operation.
>
> It is also not mentioned how clauses like firstprivate, shared, private,
> reduce, map, etc are lowered to OpenMP dialect.
>
> Yes, it is not mentioned. We did a study of a few constructs and clauses
> which was shared as mails to flang-dev and the RFC. As we make progress and
> before implementation, we will share further details.
>
> it would be beneficial to have an omp.parallel_do operation which has
> semantics similar to other loop structures (may not be LoopLikeInterface)
> in MLIR.
>
> I am not against adding parallel_do if it can help with transformations or
> reduce the complexity of lowering. Please share the details in discourse as
> a reply to the RFC or a separate thread.
>
> it looks like having OpenMP operations based on standard MLIR types and
> operations (scalars and memrefs mainly) is the right way to go.
>
> This will definitely be the first version that we implement. But I do not
> understand why we should restrict to only the standard types and
> operations. To ease lowering and translation and to avoid adding OpenMP
> operations to other dialects, I believe OpenMP dialect should also be able
> to exist with other dialects like FIR and LLVM.
>
> E. Lowering of target constructs mentioned in ( 2(d) ) specifies direct
> lowering to LLVM IR ignoring all the advantages that MLIR provides.
>
> Also, OpenMP codegen will automatically benefit from the GPU dialect based
> optimizations. For example, it would be way easier to hoist a memory
> reference out of GPU kernel in MLIR than in LLVM IR.
>
> I might not have fully understood you here. But the dialect lives
> independently of the translation to LLVM IR. If there are optimisations
> (like hoisting that you mention here) I believe they can be performed as
> transformation passes on the dialect. It is not ruled out.
>
> --Kiran
> ------------------------------
> *From:* flang-dev <flang-dev-bounces at lists.llvm.org> on behalf of Vinay
> Madhusudan via flang-dev <flang-dev at lists.llvm.org>
> *Sent:* 13 February 2020 16:33
> *To:* llvm-dev at lists.llvm.org <llvm-dev at lists.llvm.org>;
> flang-dev at lists.llvm.org <flang-dev at lists.llvm.org>
> *Subject:* [flang-dev] About OpenMP dialect in MLIR
>
>
> Hi,
>
> I have few questions / concerns regarding the design of OpenMP dialect in
> MLIR that is currently being implemented, mainly for the f18 compiler.
> Below, I summarize the current state of various efforts in clang / f18 /
> MLIR / LLVM regarding this. Feel free to add to the list in case I have
> missed something.
>
> 1. [May 2019] An OpenMPIRBuilder in LLVM was proposed for flang and clang
> frontends. Note that this proposal was before considering MLIR for FIR.
>
> a. llvm-dev proposal :
> http://lists.flang-compiler.org/pipermail/flang-dev_lists.flang-compiler.org/2019-May/000197.html
>
> b. Patches in review: https://reviews.llvm.org/D70290. This also includes
> the clang codegen changes.
>
> 2. [July - September 2019] OpenMP dialect for MLIR was discussed /
> proposed with respect to the f18 compilation stack (keeping FIR in mind).
>
> a. flang-dev discussion link:
> https://lists.llvm.org/pipermail/flang-dev/2019-September/000020.html
>
> b. Design decisions captured in PPT:
> https://drive.google.com/file/d/1vU6LsblsUYGA35B_3y9PmBvtKOTXj1Fu/view
>
> c. MLIR google groups discussion:
> https://groups.google.com/a/tensorflow.org/forum/#!topic/mlir/4Aj_eawdHiw
>
> d. Target constructs design:
> http://lists.flang-compiler.org/pipermail/flang-dev_lists.flang-compiler.org/2019-September/000285.html
>
> e. SIMD constructs design:
> http://lists.flang-compiler.org/pipermail/flang-dev_lists.flang-compiler.org/2019-September/000278.html
>
> 3. [Jan 2020] OpenMP dialect RFC in llvm discourse :
> https://llvm.discourse.group/t/rfc-openmp-dialect-in-mlir/397
>
> 4. [Jan- Feb 2020] Implementation of OpenMP dialect in MLIR:
>
> a. The first patch which introduces the OpenMP dialect was pushed.
>
> b. Review of barrier construct is in progress:
> https://reviews.llvm.org/D72962
> https://reviews.llvm.org/D72400
>
> I have tried to list below different topics of interest (to different
> people) around this work. Most of these are in the design phase (or very
> new) and multiple parties are interested with different sets of goals in
> mind.
>
> I. Flang frontend and its integration
>
> II. Fortran representation in MLIR / FIR development
>
> III. OpenMP development for flang, OpenMP builder in LLVM.
>
> IV. Loop Transformations in MLIR / LLVM with respect to OpenMP.
>
> It looks like the design has evolved over time and there is no one place
> which contains the latest design decisions that fits all the different
> pieces of the puzzle. I will try to deduce it from the above mentioned
> references. Please correct me If I am referring to anything which has
> changed.
>
> A. For most OpenMP design discussions, FIR examples are used (as seen in
> (2) and (3)). The MLIR examples mentioned in the design only talks about
> FIR dialect and LLVM dialect.
>
> This completely ignores the likes of standard, affine (where most loop
> transformations are supposed to happen) and loop dialects. I think it is
> critical to decouple the OpenMP dialect development in MLIR from the
> current flang / FIR effort. It would be useful if someone can mention these
> examples using existing dialects in MLIR and also how the different
> transformations / lowerings are planned.
>
> B. In latest RFC(3), it is mentioned that the initial OpenMP dialect
> version will be as follows,
>
> omp.parallel {
>
> omp.do {
>
> fir.do %i = 0 to %ub3 : !fir.integer {
>
> ...
>
> }
>
> }
>
> }
>
> and then after the "LLVM conversion" it is converted as follows:
>
> omp.parallel {
>
> %ub3 =
>
> omp.do %i = 0 to %ub3 : !llvm.integer {
>
> ...
>
> }
>
> }
>
>
> a. Is it the same omp.do operation which now contains the bounds and
> induction variables of the loop after the LLVM conversion? If so, will the
> same operation have two different semantics during a single compilation?
>
> b. Will there be different lowerings for various loop operations from
> different dialects? loop.for and affine.for under omp operations would need
> different OpenMP / LLVM lowerings. Currently, both of them are lowered to
> the CFG based loops during the LLVM dialect conversion (which is much
> before the proposed OpenMP dialect lowering).
>
> There would be no standard way to represent OpenMP operations (especially
> the ones which involve loops) in MLIR. This would drastically complicate
> lowering.
>
> C. It is also not mentioned how clauses like firstprivate, shared,
> private, reduce, map, etc are lowered to OpenMP dialect. The example in
> the RFC contains FIR and LLVM types and nothing about std dialect types.
> Consider the below example:
>
> #pragma omp parallel for reduction(+:x)
>
> for (int i = 0; i < N; ++i)
>
> x += a[i];
>
> How would the above be represented in OpenMP dialect? and What type would
> "x" be in MLIR? It is not mentioned in the design as to how the various
> SSA values for various OpenMP clauses are passed around in OpenMP
> operations.
>
> D. Because of (A), (B) and (C), it would be beneficial to have an omp.
> parallel_do operation which has semantics similar to other loop
> structures (may not be LoopLikeInterface) in MLIR. To me, it looks like
> having OpenMP operations based on standard MLIR types and operations
> (scalars and memrefs mainly) is the right way to go.
>
> Why not have omp.parallel_do operation with AffineMap based bounds, so as
> to decouple it from Value/Type similar to affine.for?
>
> 1. With the current design, the number of transformations / optimizations
> that one can write on OpenMP constructs would become limited as there can
> be any custom loop structure with custom operations / types inside it.
>
> 2. It would also be easier to transform the Loop nests containing OpenMP
> constructs if the body of the OpenMP operations is well defined (i.e., does
> not accept arbitrary loop structures). Having nested redundant "parallel" ,
> "target" and "do" regions seems unnecessary.
>
> 3. There would also be new sets of loop structures in new dialects when
> C/C++ is compiled to MLIR. It would complicate the number of possible
> combinations inside the OpenMP region.
>
> E. Lowering of target constructs mentioned in ( 2(d) ) specifies direct
> lowering to LLVM IR ignoring all the advantages that MLIR provides. Being
> able to compile the code for heterogeneous hardware is one of the biggest
> advantages that MLIR brings to the table. That is being completely missed
> here. This also requires solving the problem of handling target information
> in MLIR. But that is a problem which needs to be solved anyway. Using GPU
> dialect also gives us an opportunity to represent offloading semantics in
> MLIR.
>
> Given the ability to represent multiple ModuleOps and the existence of GPU
> dialect, couldn't higher level optimizations on offloaded code be done at
> MLIR level?. The proposed design would lead us to the same problems that we
> are currently facing in LLVM IR.
>
> Also, OpenMP codegen will automatically benefit from the GPU dialect based
> optimizations. For example, it would be way easier to hoist a memory
> reference out of GPU kernel in MLIR than in LLVM IR.
>
> Thanks,
>
> Vinay
>
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org
> https://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>
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