[llvm-dev] [RFC] Polly Status and Integration

[Hal Finkel via llvm-dev]

Hi, Johannes,

Thanks for writing this. I certainly think you have the right idea in 
terms of the desired end state and modular design.

On 09/19/2017 07:33 PM, Johannes Doerfert wrote:
> Hi Hal, Tobias, Michael, and others,
>
> I'd like to add my view (and a proposal) to this discussion and I
> apologize directly for doing this so late*. I also want to apologize
> because this email is long, contains various technical details and also
> argumentations that might need more justification. However, I am happy
> to provide further information (and/or examples) to explain my views if
> required.
>
> tldr;
> We should introduce polyhedral analysis and optimization capabilities
> into LLVM step by step. Along the way we should revisit design decisions
> made by Polly and adjust them according to the use cases in the rest of
> LLVM. Finally, we should keep Polly as a stand-alone tool to allow
> research into, and prototyping of, complex loop transformations.
>
> * There was a paper deadline end of last week and I simply had to prioritize.
>
> -------------------------------------------------------------------------------
>
> LLVM performs "simple" loop transformations and targets almost
> exclusively inner-most loops. Polly offers a pipeline to perform
> "complex" polyhedral-based loop optimizations on a sequence of loop
> nests. It seems natural to integrate Polly into the LLVM pipeline as it
> apparently complements it well. However, I do not believe that it is
> wise to integrate Polly into LLVM for a variety of reasons, some of
> which I will explain in more detail now. Afterwards I will propose a
> different way to achieve (most of) the things Hal mentioned in his mail
> in an incremental way. Nevertheless, I want to stress that I am still an
> advocate of Polly and I honestly believe it to be a valuable part of the
> LLVM environment. Though I strongly feel it should be continued as a
> research tool and test bed to allow research into, and prototyping of,
> (polyhedral-model-based) analysis and optimizations.

While this may end up being the conclusion, I'd find that splitting 
unfortunate. One of the strengths of LLVM is that, within the framework 
of a production-quality compiler, we enable new compiler research. This 
strengthens research not only by allowing new ideas to be surrounded by 
existing ones in a realistic way, allowing the effects of the new ideas 
to be isolated convincingly, but also encourages new ideas to be 
developed and tested in a way that mirrors how they might be deployed in 
practice. This also encourages the research community to be part of the 
LLVM community, and I believe that's a positive for the community as a 
whole. The more that we isolate the "research tool" from the rest of the 
ecosystem, the less value the research tool has, and the less the 
community as a whole benefits from interactions with researchers.

>
> ---
>
> Polly is a deep pipeline of passes that were developed for the sole
> purpose of applying scheduling transformations at the very end. This
> "main purpose" of Polly makes it hard to effectively reuse intermediate
> parts, e.g. the dependence analysis or the code generation framework, at
> least to the degree we might want to. In a different thread [1] Hal
> asked for the possibility to reuse Polly for tuning via pragmas e.g.,
> unrolling/interleaving/tiling/interchange. While this is interesting and
> generally possible it won't take long before the restrictions Polly
> places on the input code (to enable scheduling optimizations in the end)
> become a serious problem. The point here is that Polly has too many
> features and dependences for such an "easy" use case. (Note that I do
> not question the legality of a user requested transformation here.) If
> you are not looking for "end-to-end polyhedral loop optimizations" you
> want a system that answers a very specific question (e.g.,
> isVectorizable) or performs a very specific transformation (e.g, tiling)
> on a maximal set of programs. In contrast, Polly is (and I strongly
> believe it should be) developed as a system that performs complex
> optimizations, based on specialized analysis results, on a constraint
> type of programs.
>
> One might argue that Polly will become more modular when it is integrated
> into LLVM and when the intermediate results are used in more and more
> places. However, I'd say this is the "wrong direction" with regards to:
>    1) incremental design and development,
>    2) maintainability of individual parts, and
>    3) the development of a suitable cost model (which Polly does not ship).
>
> Instead of starting with a full, hard to understand, scheduling pipeline
> we should start with the use cases at hand and design specific analysis
> (and also transformation) passes "from scratch". The long term goal
> should be a full scheduling pipeline but the parts need to be designed
> in a modular (LLVM-way) from the very beginning. This allows us to:
>    - provide __immediate benefit__ to other developers,
>    - allow active participation in (and understanding of) the design of
>      each part, and
>    - develop the intermediate parts with the requirements of the whole
>      LLVM project in mind.
>
> Let me give two examples to make my point:
>
> -- Example 1 --
> In addition to the applicability issues there are other problems that
> arise from the full pipeline design. Let's assume we want to apply a
> pragma driven optimization to a loop that can be represented (and
> optimized) by Polly. Depending on the pragma we only need to perform a
> very specific task, e.g., adjust the iteration variable (loop inversion)
> or introduce new loops and adjust existing iteration variables (tiling).
> Polly will however represent (and actually analyze) the whole loop nest
> including the exact control flow and all accesses. In addition it
> will compute alias checks, constraints under which the representation
> is not truthful (e.g., an access function might overflow) and a lot of
> other things that are not needed for the task at hand.

I understand your point, but I think that you're assuming too much about 
the semantics of the pragmas. I believe that our current vectorization 
pragma clauses demonstrate the philosophy we should follow with other 
loop pragmas in this sense: We have vectorize(enable) and 
vectorize(assume_safety). The latter one does indeed just vectorize the 
loop without requiring dependency analysis, but the vectorize(enable) 
clause instructs the vectorizer to vectorize the loop 
(overriding/loosening some of the cost model constraints), but still 
uses the dependency analysis and generates runtime checks. Even if we 
have pragmas to direct the process, by default, we still likely want the 
full dependency analysis and the framework for generating safety predicates.

>
> -- Example 2 --
> We can also imagine we want to determine if a loop can be vectorized,
> thus if there are (short) loop carried dependences. No matter which
> technique is used, the complexity of a dependence analysis will
> certainly increase with the number (and complexity) of the analyzed
> accesses. Since Polly is designed with fine-grained scheduling
> optimizations in mind, the dependences it will compute are
> disproportionate with regards to the question asked.

Could you explain this in more detail?

>   Consequently, it
> will either take more time to determine if there are loop carried
> dependences

I think that this is clearly a question of degree. Almost any non-lazy 
analysis will over-compute for a particular transformation (e.g. 
computing a dominator tree), but there's engineering value in 
consistency. The question is just in the cost vs. the engineering 
complexity in customizing the analysis.

>   or a time-out in the computation will cause a conservatively
> negative result.
>
> ---
>
> While it is generally possible to disable some "features" of Polly or to
> "work around them", it requires new independent code paths in an already
> highly interleaved project. The explicit (and implicit) interactions
> between the different parts of Polly are plentiful and subtle. I don't
> think there are 5 people that know about more than half of them. (I also
> doubt there is no one that knows them all.)

This point is well taken. For better or worse, it reminds me of another 
component we've discussed a lot recently: InstCombine. Both (excluding 
isl) are also nearly the same size.

In this context, documenting these interactions is important (especially 
if we hope to rewrite large parts of it).

>
> ---
>
> I want to propose an alternative plan for which I would appreciate
> feedback. The feedback is especially useful since I will present this,
> or more accurately the concrete polyhedral analyses described below, in
> the student research competition at LLVM Dev meeting in October.
>
> The idea is simple. We rewrite parts of Polly with two goals in mind:
>    1) to provide analysis results and transformation options to LLVM, and
>    2) allow polyhedral loop transformation.
>
> A rewrite allows to revisit various design decisions that are buried
> deep in the Polly code and that hinder its application (in any context).
> The interested reader can find a short list at the end.
>
> I think, we should incrementally introduce polyhedral analysis
> capabilities in order to provide immediate benefits and to allow
> developers to get involved with the design and usage from an early point
> in time. Decoupled analyses also allow easier integration, interfaces
> that come "more natural" to non-polyhedral people, and better use of the
> capabilities if polyhedral scheduling is not the goal.
>
> To demonstrate this incremental process I started to write a polyhedral
> value analysis**. Think of it as Scalar Evolution but with piece-wise
> defined polyhedral values as the abstract domain. This analysis is
> demand driven, works on the granularity of a LLVM value, is flow
> sensitive, and especially designed to be applicable on partially affine
> programs. It already supports most of what the polyhedral model does
> allow and includes a lot of things we prototyped in Polly. It shall be
> used when Scalar Evolution is not able to provide a sufficient result.
> On top I implemented a polyhedral memory analysis*** that is (currently)
> capable of summarizing the memory effects of a code region, e.g., a
> function. The next step is a demand-driven dependence analysis**** that
> utilizes the (often) very structured nature of a CFG. Afterwards, I
> would like to see a transformation framework that allows classical but
> also scheduling based transformations.
>
> While these analyses still depend on isl as a back-end, they never
> directly use it. Instead there is a C++ interface in-between that
> encapsulates the features needed. Once our use cases are clear we can
> re-implement this interface.
>
> ** For comparison, the value analysis covers parts of the ScopDetection,
> all of SCEVValidator and SCEVAffinator as well as parts of ScopInfo and
> ScopBuilder in Polly.
> *** The memory analysis is concerned with the construction and
> functionality Polly implements in the MemoryAccess class.
> **** The dependence analysis is similar to Polly's DependenceInfo class
> but is supposed to allow more fine-grained control.

Is the code for these available? Are you planning to contribute them? We 
could certainly consider these part of the plan.

>
> ---
>
> These are a few design decisions that I think should be revisited when
> we think about polyhedral-based analysis and optimizations in LLVM:
>
>    - We should not rely on Scalar Evolution. Instead we want to build
>      polyhedral values straight from the underlying IR. While
>      Scalar Evolution did certainly simplify Polly's development it
>      induced various problems:
>        - The lack of piece-wise affine values (other than min/max)
>          limits applicability and precision. (Though conditional SCEVs
>          are a small step in this direction.)
>        - The flow insensitive value analysis (Scalar Evolution) causes a
>          lot of "assumptions", thus versioning, for the otherwise flow
>          sensitive Polly.
>        - There are caching issues when parts of the program are
>          transformed or when Polly is used for inter-procedural
>          analysis/optimization.
>
>    - We should not depend on single-entry-single-exit (SESE) regions.
>      Instead we analyze the code optimistically to the extend possible
>      (or required by the user). Afterwards we can easily specialize the
>      results to the code regions we are interested in. While SESE regions
>      always caused compile time issues (due to the use of the post
>      dominance tree) they also limit the analysis/transformations that
>      can be performed. As an example think of accesses that are
>      non-affine with regards to the smallest surrounding SESE region but
>      not in a smaller code region (e.g., a conditional). If the goal is
>      not loop scheduling but, for example, instruction reordering, it
>      is still valuable to determine the dependences between these
>      accesses in the smaller code region.
>
>    - We should iteratively and selective construct polyhedral
>      representations. The same holds for analysis results, e.g.
>      dependences. Let's reconsider example 2 from above. We want to visit
>      one memory access at a time in order to build the polyhedral
>      representation and compute the new dependences. We also want to
>      immediately stop if we identify a loop-carried dependence. Finally,
>      we do not want to compute dependences in outer loop iterations or
>      dependences that are completely contained in one loop iteration.

If we're only considering inner-loop vectorization, then yes, we don't 
need outer-loop dependencies. If I understand what you mean, we actually 
might want intra-iteration dependencies for cases where reordering might 
allow for vectorization.

>
>    - We should encapsulate the code generation part completely from the
>      transformation part.

This separation sounds useful, but not necessarily to enable us to write 
a bunch of separate loop transformations. We may to split things for 
canonicaliation vs. lowering transformations, however.

>   Additionally we might want to start with
>      classical loop transformations instead of full polyhedral
>      scheduling. For a lot of classical loop transformations code
>      generation only needs to understand/change loop induction variables
>      and exit conditions. Duplication + rewriting of the loop body is
>      often not necessary. Pragma driven optimizations could be easily
>      done and we could also use heuristics similar to the ones we have
>      today (e.g., for loop distribution). The transformations we allow
>      should than grow with the scheduling decisions we allow and these
>      should be limited by a yet to be determined cost model.

Much of this sounds potentially good, but it's not clear to me that any 
of this is really an argument against integrating Polly into LLVM right 
now. The components you propose should be usable for both separate and 
integrated transformations and analysis, and at least in the short term, 
we'll end up needing isl regardless. Is your skepticism mainly about 
whether the current Polly could be transitioned to use the new 
infrastructure (without essentially rewriting all of it)? If so, I'd 
like to understand why.

Thanks again,
Hal

>
> ---
>
> I am aware that not all Polly developers will agree with my views and
> that some are simply trade-offs that do not offer a "correct way".
> Nevertheless, I hope that the simple examples I used to point out
> various problems are enough to consider the route I proposed.
>
> Cheers,
>    Johannes
>
> [1] https://groups.google.com/d/msg/polly-dev/ACSRlFqtpDE/t5EDlIwtAgAJ
>
> On 09/01, Hal Finkel via llvm-dev wrote:
>> **
>>
>> *Hi everyone,As you may know, stock LLVM does not provide the kind of
>> ...
>>
>> -- 
>> Hal Finkel
>> Lead, Compiler Technology and Programming Languages
>> Leadership Computing Facility
>> Argonne National Laboratory
>>
>> _______________________________________________
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>

-- 
Hal Finkel
Lead, Compiler Technology and Programming Languages
Leadership Computing Facility
Argonne National Laboratory