[llvm-dev] [RFC] Writing loop transformations on the right representation is more productive

Tue Jan 14 20:39:20 PST 2020

Am So., 12. Jan. 2020 um 20:07 Uhr schrieb Chris Lattner <
clattner at nondot.org>:

> The central idea is to use a modifiable loop tree -- similar to
> LoopInfo -- as the primary representation. LLVM-IR is converted to a
> loop tree, then optimized and finally LLVM-IR is generated again for
> subtrees that are considered profitable. This is not a new concept, it
> has already been used in compilers such as IBM XL Fortran (called ASTI
> [4]) and Silicon Graphics/Open64 (called LNO [10]), and in research
> such as the Value State Dependence Graph [3].
>
>
> Ignoring the details of its representation, this is also conceptually how
> Polly works: code is lifted into its representation, transformed, then
> lowered back down.
>

Indeed I tried to improve on Polly's internal representation, and improve
on the issue that Polly can only represent a subset of LLVM-IR code.

> Overall, I think that this discussion would be easier to process if we
> broke it into a few pieces.  There seems to be consensus that LLVM IR (as
> is) is not the right representation for aggressive loop transformations.
> If we don’t have consensus on this, then I’d make sure to start there.
>
>
> Once that is established, there is a question of “what is the right
> representation to use”?  This question has two subcomponents: what data
> structure should we use, and what is the IR within it.
>
> If you propose introducing a brand new data structure, please expect me to
> push back on that pretty hard.
>

Which I think is a good thing since I also do not want too many data
structures being more-or-less well maintained. But I also think there is a
good argument to a loop-centric data structure.

> This is a perfect application of MLIR, and using it provides a lot of
> value (including amazing testing tools, round-tripping, location tracking,
> etc) which would otherwise would have to be reinvented, and doesn’t not
> dictate the IR structure otherwise.  MLIR absolutely supports nested loop
> structures etc, as is seen in the affine dialect.
>
> The MLIR community also is highly invested in HPC-style transformations on
> this, and a lot of thought has gone into it.  You can learn more about this
> in the slides and videos from the MLIR open design meetings
> <https://docs.google.com/document/d/1y_9f1AbfgcoVdJh4_aM6-BaSHvrHl8zuA5G4jv_94K8/edit#heading=h.cite1kolful9>
> .
>

I have been following the development of MLIR.

One you achieve consensus on data structure, there is the question of what
> IR to use within it.  I would recommend starting with some combination of
> “existing LLVM IR operations + high level control flow representation”,
> e.g. parallel and affine loops.  The key here is that you need to always be
> able to lower in a simple and predictable way to LLVM IR (this is one of
> the things that classic polyhedral systems did sub optimally, making it
> difficult to reason about the cost model of various transformations), and
> this is a natural incremental starting point anyway.  Over time, more high
> level concepts can be gradually introduced.  FYI, MLIR already has a
> reasonable LLVM dialect <https://mlir.llvm.org/docs/Dialects/LLVM/> and
> can generate LLVM IR from it, so we’d just need an “LLVM IR -> MLIR LLVM
> dialect” conversion, which should be straightforward to build.
>

Adding a LLVM-IR -> MLIR -> LLVM-IR round-trip would at the beginning just
introduce compile-time overhead and what Renato described as brittleness. I
fear this hurts adaption.

Once you have the data structure and the dialect within it decided, you
> have the set of transformations.  Again, you’ve given a lot of thought to
> this, and that all sounds great to me, but the priorities can be driven by
> whoever wants to contribute and what concrete problems they have to solve.
>
>
> Once the infra for “raising to this representation and lowering back down”
> is figured out, we can open the box of having clang and other front ends
> directly generate it.
>

This suggestions would also apply to VPlan. Ignoring that work on VPlan
started before MLIR, would you have suggested to implement VPlan on MLIR as
well? Would you maybe even advise to retarget VPlan on MLIR now?

Q: Relation to MLIR?
>
> A: MLIR is more similar to LLVM-IR than a loop hierarchy.
>
>
> This is not true, MLIR is great for dialects that want to model loop
> hierarchies naturally, this is a major focus of the affine dialect
> <https://mlir.llvm.org/docs/Dialects/Affine/> (e.g. see affine.for on
> that page).  MLIR is not limited to affine loops, that is just a choice
> made by the affine dialect - the loop dialect
> <https://mlir.llvm.org/docs/Dialects/LoopOps/> has more general
> constructs that are less developed.
>

This is definitely subjective question. I think that MLIR is closer to
LLVM-IR for how it is processed. Both have a sequence of passes running
over a single source of truth. Both allow walking the entire structure from
every instruction/operation/block. Analyses are on function or module
level. Both have CFGs (I think for a certain kind of transformations it is
an advantage that control flow is handled implicitly).

For
> instance, it also does not feature cheap copies.
>
>
> I’m not sure what this means.
>
>
The possibility to make local changes speculatively without copying the
entire data structure. IMHO this is a central idea that allows applying a
transformations speculatively to pass it to a legality check and cost
heuristic without committing to apply it. As a consequence, passes do not
need to implement to implement these in a transformation-specific manner,
drastically reducing the burden of implementation.

For instance, more loop transformations are feasible if instructions are
moved into the innermost loops. With speculative transformations, we can
canonicalize the representation to sink computations into loops -- the
opposite of what LICM does -- and then see whether a transformation can
applied. If not, the speculative representation is discarded without having
an effect on the original representation (and not needing to hoist those
computations again).

Because the MLIR classes have many references to related objects (such as
pointer to parents and use-def chains), I don't think it is feasible to
implement on top of MLIR.

An advantage is that
> loops and multi-dimensional arrays can be represented in the language
> without the need of being rediscovered, but have to be inserted by a
> front-end.
>
>
> This is correct, but I don’t see how this helps if your focus is raising
> code that has already been lowered to LLVM IR, e.g. by Clang or some other
> frontend that generates LLVM IR today.
>

Indeed, I would hope that LLVM-IR can preserve multi-dimensional array
accesses in some fashion as well (
https://lists.llvm.org/pipermail/llvm-dev/2019-July/134063.html). However,
currently MLIR has the advantage of being able represent it.

That is, if Clang was generating MLIR, loops and arrays
> still have to be rediscovered.
>
>
> This isn’t true, it would be perfectly sensible to lower C control flow
> structures directly too LLVM.  The primary concern are things like
> unstructured switches (think duff’s device) and unstructured gotos, but
> these occur rarely: they need to be handled correctly, but can do so with a
> traditionally lowered CFG and other “best effort” attempts to raise them.
>

Moreover, syntactical loop structures are also not a reliable indicator
that there is a loop. Often enough, do,for and while are used for
syntactical reasons (`do { } while(0)`). Yes, you could eliminate them if a
non-loop is detected, but handling break, continue, etc correctly is a lot
of effort. Another case are corountines that are lowered with gotos into
loops, unless you think loop optimizers should handle coroutines directly.

On the other side, natural loop detection on CFGs is quite mature (with a
remaining issue of irreducible loops that might appear, but can also be
eliminated again). As a plus, optimization does depend less on how the
source code is written.

Thanks for the productive discussion,
Michael
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