<div dir="ltr">Hi Hal,<div><br></div><div class="gmail_extra"><br><div class="gmail_quote">2017-09-21 20:59 GMT-07:00 Hal Finkel via llvm-dev <span dir="ltr"><<a href="mailto:llvm-dev@lists.llvm.org" target="_blank">llvm-dev@lists.llvm.org</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
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<div class="m_-2166750394864443591moz-cite-prefix">On 09/12/2017 10:26 PM, Gerolf
Hoflehner wrote:<br>
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<div>On Sep 11, 2017, at 10:47 PM, Hal Finkel via
llvm-dev <<a href="mailto:llvm-dev@lists.llvm.org" target="_blank">llvm-dev@lists.llvm.org</a>>
wrote:</div>
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<div class="m_-2166750394864443591moz-cite-prefix">On 09/11/2017 12:26 PM,
Adam Nemet wrote:<br>
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</span><blockquote type="cite"><span class=""> Hi Hal, Tobias, Michael and
others,
</span><div><b>...</b><span class="">
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<div>One thing that I’d like to see more
details on is what this means for the evolution
of loop transformations in LLVM.</div>
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<div>Our more-or-less established
direction was so far to incrementally improve
and generalize the required analyses (e.g. the
LoopVectorizer’s dependence analysis + loop
versioning analysis into a stand-alone analysis
pass (LoopAccessAnalysis)) and then build new
transformations (e.g. LoopDistribution,
LoopLoadElimination, LICMLoopVersioning) on top
of these.</div>
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<div>The idea was that infrastructure
would be incrementally improved from two
directions:</div>
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<div>- As new transformations are built
analyses have to be improved (e.g. past
improvements to LAA to support the
LoopVersioning utility, future improvements for
full LoopSROA beyond just store->load
forwarding [1] or the improvements to LAA for
the LoopFusion proposal[2])</div>
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<div>- As more complex loops would have
to be analyzed we either improve LAA or make
DependenceAnalysis a drop-in replacement for the
memory analysis part in LAA</div>
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Or we could use Polly's dependence analysis, which I
believe to be more powerful, more robust, and more
correct than DependenceAnalysis. I believe that the
difficult part here is actually the pairing with
predicated SCEV or whatever mechanism we want to use
generate runtime predicates (this applies to use of
DependenceAnalysis too).<br>
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What is a good way to measure these assertions (More powerful,
more robust)? Are you saying the LLVM Dependence Analysis is
incorrect or do you actually mean less conservative (or "more
accurate" or something like that)?<br>
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Sebastian's email covers the issues with the DependenceAnalysis pass
pretty well.<br>
<br>
Regarding what's in LoopAccessAnalysis, I believe it to be correct,
but more limited. It is not clear to me that LAA is bad at what it
does based on what the vectorizer can handle. LAA could do better in
some cases with non-unit-stride loops. Polly also handles
piecewise-affine functions, which allows the modeling of loops with
conditionals. Extending LAA to handle loop nests, moreover, seems
likely to be non-trivial.<br>
<br>
Regardless, measuring these differences certainly seems like a good
idea. I think that we can do this using optimization remarks. LAA
already emits optimization remarks for loops in which it finds
unsafe memory dependencies. Polly also emits optimization remarks.
We may need to iterate some in order to setup a good comparison, but
we should be able to collect statistics (and other information) by
compiling code using -fsave-optimization-record (in combination with
some other flags), and then analyzing the resulting YAML files.<span class=""><br>
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<div>While this model may be slow it has
all the benefits of the incremental development
model.</div>
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The current model may have been slow in many areas, but
I think that's mostly a question of development effort.
My largest concern about the current model is that, to
the extent that we're implementing classic loop
transformations (e.g., fusion, distribution,
interchange, skewing, tiling, and so on), we're
repeating a historical design that is known to have
several suboptimal properties. Chief among them is the
lack of integration: many of these transformations are
interconnected, and there's no good pass ordering in
which to make independent decisions. Many of these
transformations can be captured in a single model and we
can get much better results by integrating them. There's
also the matter of whether building these transformation
on SCEV (or IR directly) is the best underlying
infrastructure, or whether parts of Polly would be
better.<br>
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I believe that is true. What I wonder is is there a good
method to reason about it?</div>
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If I understand what you mean, one way to look at it is this: This
is not a canonicalization problem. Picking an optimal way to
interchange loops may depend on how the result can be skewed and/or
tiled, picking an optimal way to distribute loops often depends on
what can be done afterward in each piece. Optimal here generally
involves reasoning about the memory hierarchy (e.g., cache
properties), available prefetching streams, register-file size, and
so on.<br>
<br>
I know that I've seen some good examples in papers over the years
that illustrate the phase-ordering challenges. Hopefully, someone
will jump in here with some good references. One classic one is:
William Pugh. Uniform Techniques for Loop Optimization. 1991.<span class=""><br>
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<div> Perhaps concrete examples or perhaps opt-viewer based
comparisons on large sets of benchmarks? In the big picture
you could make such a modeling argument for all compiler
optimizations.<br>
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Certainly. However, in this case there's a well-studied unified
model for this set of optimizations known to reduce phase-ordering
effects. That's not true in general.<span class=""><br>
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That having been said, I think that integrating this
technology into LLVM will also mean applying appropriate
modularity. I think that we'll almost definitely want to
make use of the dependence analysis separately as an
analysis. We'll want to decide which of these
transformations will be considered canonicalization (and
run in the iterative pipeline) and which will be
lowering (and run near the vectorizer). LoopSROA
certainly sounds to me like canonicalization, but loop
fusion might also fall into that category (i.e., we
might want to fuse early to enable optimizations and
then split late).<br>
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<div>Then there is the question of use
cases. It’s fairly obvious that anybody wanting
to optimize a 5-deep highly regular loop-nest
operating on arrays should use Polly. On the
other hand it’s way less clear that we should
use it for singly or doubly nested
not-so-regular loops which are the norm in
non-HPC workloads.</div>
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This is clearly a good question, but thinking about
Polly as a set of components, not as a monolithic
transformation component, I think that polyhedral
analysis and transformations can underlie a lot of the
transformations we need for non-HPC code (and, which
I'll point out, we need for modern HPC code too). In
practice, the loops that we can actually analyze have
affine dependencies, and Polly does, or can do, a better
job at generating runtime predicates and dealing with
piecewise-linear expressions than our current
infrastructure.<br>
<br>
In short, I look at Polly as two things: First, an
infrastructure for dealing with loop analysis and
transformation. I view this as being broadly applicable.
Second, an application of that to apply
cost-model-driven classic loop transformations. To some
extent this is going to be more useful for HPC codes,
but also applies to machine learning, signal processing,
graphics, and other areas. <br>
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I’m wondering if it could be used for pointing out headroom
for the existing LLVM ecosystem (*)<br>
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Sure.<span class=""><br>
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<div>And this brings me to the
maintenance question. Is it reasonable to
expect people to fix Polly when they have a
seemingly unrelated change that happens to break
a Polly bot.</div>
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The eventual goal here is to have this technology in
appropriate parts of the main pipeline, and so the
question here is not really about breaking a "Polly
bot", but just about a "bot" in general. I've given this
question some thought and I think it sits in a
reasonable place in the risk-reward space. The answer
would be, yes, we'd need to treat this like any other
part of the pipeline. However, I believe that Polly has
as many, or more, active contributors than essentially
any other individual part of the mid-level optimizer or
CodeGen. As a result, there will be people around in
many time zones to help with problems with Polly-related
code.<br>
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<div> As far as I know, there were
companies in the past that tried Polly without a
whole lot of prior experience. It would be
great to hear what the experience was before
adopting Polly at a much larger scale.</div>
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I'm also interested, although I'll caution against
over-interpreting any evidence here (positive or
negative). Before a few weeks ago, Polly didn't
effectively run in the pipeline after inlining, and so I
doubt it would have been much use outside of embedded
environments (and maybe some HPC environments) with
straightforwardly-presented C code. It's only now that
this has been fixed that I find the possibility of
integrating this in production interesting.<br>
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That is a good point. There are also biases independent of
past experiences (for disclosure mine is (*) above). But I
think it is objective to say a Polly integration is a big
piece to swallow.Your pro-Polly argument lists a number of
categories that I think could be reasoned about individually
and partly evaluated with a data-driven approach:</div>
<div>A) Architecture</div>
<div>- support for autoparallelism</div>
<div>- support for accelerators</div>
<div>- isl- rewrite? etc</div>
<div>...</div>
<div>B) Modelling</div>
<div>- polyhedral model</div>
<div>- temporal locality</div>
<div>- spatial locality </div>
<div>…</div>
<div>C) Analysis/Optimizations</div>
<div>- Dependence Analysis</div>
<div>- Transformation effective/power (loop nests, quality of
transformations, #vectorizable loops etc)</div>
<div><br>
</div>
<div>A) is mostly Polly independent (except for the isl question
I guess). For B and C performance/ compile-time /opt-viewer
data on a decent/wide range of benchmarks possibly at
different optimization levels (O2, O3, LTO, PGO etc and
combinations) should provide data-driven insight into
costs/benefits. <br>
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I agree. In practice, the first question is: Are will willing to
take on Polly (+isl), in whole or in part, as a build dependency? If
the answer is yes, the next question is: what parts should be reused
or refactored for use in other parts of the pipeline? My argument is
that we should take on Polly, or most of it, as a build dependency.
Work on better unifying the developer communities as we start
experimenting with other kinds of integration. This will, however,
allow us to provide to all of our users these transformations
through pragmas (and other kinds of optional enablement). This is an
important first step.<br></div></blockquote><div><br></div><div>When you write that we should take Polly as a build dependency: are you envisioning this to be tied into LLVM to the point where we can't build LLVM without Polly?</div><div>I thought the approach would rather be that a default build of LLVM would have Polly available but that there will "forever" be a `-DENABLE_POLLY=OFF` option?</div><div>This seems like an important distinction to me, as making it more integrated but still optional for the correct behavior of LLVM means that people can continue to work and maintain "forever" an optimization pipeline which operates without Polly, while starting to get more integration in a pluggable form. I believe this is the direction that was taken with the GSoC last year, trying to get Polly as a "pluggable" dependency analysis.</div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div bgcolor="#FFFFFF" text="#000000">
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I'm not sure exactly how good this is, but polly has LNT-submitting
bots, so the website can generate a comparison (e.g., <a class="m_-2166750394864443591moz-txt-link-freetext" href="http://lnt.llvm.org/db_default/v4/nts/71208?compare_to=71182" target="_blank">http://lnt.llvm.org/db_<wbr>default/v4/nts/71208?compare_<wbr>to=71182</a>).
Looking at this comparison shows a number of potential problems but
also cases where Polly really helps (and, FWIW, the largest two
compile-time regressions are also associated with very large
execution performance improvements). My first focus would certainly
be on pragma-driven enablement.<br></div></blockquote><div><br></div><div>I'll add: PGO-driven enablement: spending compile-time where we know it can have an impact. What do you think?</div><div><br></div><div>Best,</div><div><br></div><div>-- </div><div>Mehdi</div><div><br></div></div></div></div>