llvm dev - Feb 2017 - (RFC) Adjusting default loop fully unroll threshold

> On Feb 16, 2017, at 4:41 PM, Xinliang David Li via llvm-dev <llvm-dev at
lists.llvm.org> wrote:
> 
> 
> 
> On Thu, Feb 16, 2017 at 3:45 PM, Chandler Carruth via llvm-dev <llvm-dev
at lists.llvm.org <mailto:llvm-dev at lists.llvm.org>> wrote:
> First off, I just want to say wow and thank you. This kind of data is
amazing. =D
> 
> On Thu, Feb 16, 2017 at 2:46 AM Kristof Beyls <Kristof.Beyls at arm.com
<mailto:Kristof.Beyls at arm.com>> wrote:
> The biggest relative code size increases indeed didn't happen for the
biggest programs, but instead for a few programs weighing in at about 100KB.
> I'm assuming the Google benchmark set covers much bigger programs than
the ones displayed here.
> FWIW, the cluster of programs where code size increases between 60% to 80%
with a size of about 100KB, all come from MultiSource/Benchmarks/TSVC.
Interestingly, these programs seem to have float and double variants,  e.g.
(MultiSource/Benchmarks/TSVC/Searching-flt/Searching-flt and
MultiSource/Benchmarks/TSVC/Searching-dbl/Searching-dbl), and the code size
bloat only happens for the double variants.
> 
> I think we should definitely look at this (as it seems likely to be a bug
somewhere), but I'm also not overly concerned with size regressions in the
TSVC benchmarks which are unusually loop heavy and small. We've have several
other changes that caused big fluctuations here.
>  
>  
> I think it may still be worthwhile to check if this also happens on other
architectures, and why it happens only for the double-variants, not the
float-variants.
> 
> +1
> 
> The second chart shows relative code size increase (vertical axis) vs
relative performance improvement (horizontal axis):
> I manually checked the cause of the 3 biggest performance regressions
(proprietary benchmark1: -13.70%; MultiSource/Applications/hexxagon/hexxagon:
-10.10%; MultiSource/Benchmarks/FreeBench/fourinarow/fourinarow
> -5.23%).
> For the proprietary benchmark and hexxagon, the code generation didn't
change for the hottest parts, so probably is caused by micro-architectural
effects of code layout changes.
> 
> This is always good to know, even though it is frustrating. =]
>  
> For fourinarow, there seemed to be a lot more spill/fill code, so probably
due to non-optimality of register allocation.
> 
> This is something we should probably look at. If you have the output lying
around, maybe file a PR about it?
> 
> The third chart below just zooms in on the above chart to the -5% to 5%
performance improvement range:
> <unroll_codesize_vs_performance_zoom.png>
> 
> 
> Whether to enable the increase in unroll threshold only at O3 or also at
O2: I don't have a strong opinion based on the above data.
> 
> FWIW, this data seems to clearly indicate that we don't get performance
wins with any consistency when the code size goes up (and thus the change has
impact). As a consequence, I pretty strongly suspect that this should be *just*
used at O3 at least for now.
> 
> The correlation is there -- when there is performance improvement, there is
size increase.
I didn’t quite get this impression from the graph, the highest improvement
didn’t come with code size increase:





And on the other hand there were many code-size increase without any runtime
improvement.

> The opposite is not true -- but that is expected. If the speedup is in the
cold path, there won't be visible performance improvement but size increase.
> 
> Put it another way. If we reduce the threshold, there will be sizable size
improvement for many benchmarks without regressing performance, shall we use the
reduced threshold for O2 instead?
Yes, all the ones here IIUC:





However it is likely that we could consider these “small” benchmarks should use
-Os if they're sensitive to size, and so O2 would be fine with the more
aggressive threshold (as larger program aren’t affected).

With good heuristic we’d have every dot forming a straight line  
code_size_increase = m * runtime_perf (with m as small as possible). The current
lack of shape (or the exact opposite distribution to the ideal I imagine above)
seems to show that our "profitability” heuristics are pretty bad and the
current threshold knob is bad predictor of the runtime performance.

— 
Mehdi

> 
> It is usually tiny programs that are sensitive (size) to this change. The
size vs size increase chart confirms that point. There is basically no large
size increase for programs > 1MB (clang release build size is 78M). In other
words, I believe the actual size impact on real world applications should be
negligible.  This behavior is very different from the case when we increase
inline threshold for instance -- which will have size impact across the board.
The latter is certainly more limited to higher optimization levels.
> 
> thanks,
> 
> David
> 
> 
> 
>  
> 
> I see two further directions for Dehao that make sense here (at least to
me):
> 1) I suspect we should investigate *why* the size increases are happening
without helping speed. I can imagine some reasons that this would of course
happen (cold loops getting unrolled), but especially in light of the oddities
you point out above, I suspect there may be issues where more unrolling is
uncovering other problems and if we fix those other problems the shape of things
will be different. We should at least address the issues you uncovered above.
> 
> 2) If this turns out to be architecture specific (it seems that way at
least initially, but hard to tell for sure with different benchmark sets) we
might make AArch64 and x86 use different thresholds here. I'm skeptical
about this though. I suspect we should do #1, and we'll either get a
different shape, or just decide that O3 is more appropriate.
>  
> Maybe the compile time impact is what should be driving that discussion the
most? I'm afraid I don't have compile time numbers.
> 
> FWIW, I strongly suspect that for *this* change, compile time and code size
will be pretty precisely correlated. Dehao's data shows that to be true in
several cases certainly.
>  
> Ultimately, I guess this boils down to what exactly the difference is in
intent between O2 and O3, which seems like a never-ending discussion...
> 
> The definitions I am working from are here:
>
https://github.com/llvm-project/llvm-project/blob/master/llvm/include/llvm/Passes/PassBuilder.h#L81-L90
<https://github.com/llvm-project/llvm-project/blob/master/llvm/include/llvm/Passes/PassBuilder.h#L81-L90>
> 
> I've highlighted the part that makes me think O3 is better here: the
code size increases (and thus compile time increases) don't seem to
correspond to runtime improvements.
>  
> 
> Hoping you find this useful,
> 
> Very. Once again, this kind of data and analysis is awesome. =D 
> 
> Kristof
> 
>> 
>> On Tue, Feb 14, 2017 at 1:06 PM Kristof Beyls via llvm-dev <llvm-dev
at lists.llvm.org <mailto:llvm-dev at lists.llvm.org>> wrote:
>> I've run the patch on https://reviews.llvm.org/D28368
<https://reviews.llvm.org/D28368> on the test-suite and other benchmarks,
for AArch64 -O3 -fomit-frame-pointer, both for Cortex-A53 and Cortex-A57.
>> 
>> The geomean over the few hundred programs in there is roughly the same
for Cortex-A53 and Cortex-A57: a bit over 1% improvement in execution speed for
a bit over 5% increase in code size.
>> Obviously I wouldn't want this for optimization levels where code
size is of any concern, like -Os or -Oz, but don't have a problem with this
going in for other optimization levels where this isn't a concern.
>> 
>> Thanks,
>> 
>> Kristof
> 
> 
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org <mailto:llvm-dev at lists.llvm.org>
> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
<http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev>
> 
> 
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org <mailto:llvm-dev at lists.llvm.org>
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On Thu, Feb 16, 2017 at 5:43 PM Mehdi Amini <mehdi.amini at apple.com>
wrote:
> On Feb 16, 2017, at 4:41 PM, Xinliang David Li via llvm-dev <
> llvm-dev at lists.llvm.org> wrote:
>
> On Thu, Feb 16, 2017 at 3:45 PM, Chandler Carruth via llvm-dev <
> llvm-dev at lists.llvm.org> wrote:
>
> First off, I just want to say wow and thank you. This kind of data is
> amazing. =D
>
> On Thu, Feb 16, 2017 at 2:46 AM Kristof Beyls <Kristof.Beyls at
arm.com>
> wrote:
>
> The biggest relative code size increases indeed didn't happen for the
> biggest programs, but instead for a few programs weighing in at about
100KB.
> I'm assuming the Google benchmark set covers much bigger programs than
the
> ones displayed here.
> FWIW, the cluster of programs where code size increases between 60% to 80%
> with a size of about 100KB, all come from MultiSource/Benchmarks/TSVC.
> Interestingly, these programs seem to have float and double variants,  e.g.
> (MultiSource/Benchmarks/TSVC/Searching-flt/Searching-flt and
> MultiSource/Benchmarks/TSVC/Searching-dbl/Searching-dbl), and the code size
> bloat only happens for the double variants.
>
>
> I think we should definitely look at this (as it seems likely to be a bug
> somewhere), but I'm also not overly concerned with size regressions in
the
> TSVC benchmarks which are unusually loop heavy and small. We've have
> several other changes that caused big fluctuations here.
>
>
>
> I think it may still be worthwhile to check if this also happens on other
> architectures, and why it happens only for the double-variants, not the
> float-variants.
>
>
> +1
>
> The second chart shows relative code size increase (vertical axis) vs
> relative performance improvement (horizontal axis):
> I manually checked the cause of the 3 biggest performance regressions
> (proprietary benchmark1: -13.70%;
> MultiSource/Applications/hexxagon/hexxagon: -10.10%;
> MultiSource/Benchmarks/FreeBench/fourinarow/fourinarow -5.23%).
> For the proprietary benchmark and hexxagon, the code generation didn't
> change for the hottest parts, so probably is caused by micro-architectural
> effects of code layout changes.
>
>
> This is always good to know, even though it is frustrating. =]
>
>
> For fourinarow, there seemed to be a lot more spill/fill code, so probably
> due to non-optimality of register allocation.
>
>
> This is something we should probably look at. If you have the output lying
> around, maybe file a PR about it?
>
> The third chart below just zooms in on the above chart to the -5% to 5%
> performance improvement range:
> <unroll_codesize_vs_performance_zoom.png>
>
>
> Whether to enable the increase in unroll threshold only at O3 or also at
> O2: I don't have a strong opinion based on the above data.
>
>
> FWIW, this data seems to clearly indicate that we don't get performance
> wins with any consistency when the code size goes up (and thus the change
> has impact). As a consequence, I pretty strongly suspect that this should
> be *just* used at O3 at least for now.
>
>
> The correlation is there -- when there is performance improvement, there
> is size increase.
>
>
> I didn’t quite get this impression from the graph, the highest improvement
> didn’t come with code size increase:
>
>
>
>
> And on the other hand there were many code-size increase without any
> runtime improvement.
>

the zoomed in graph does not show the trend indeed, but the original graph
does 😀
>
>
> The opposite is not true -- but that is expected. If the speedup is in the
> cold path, there won't be visible performance improvement but size
increase.
>
> Put it another way. If we reduce the threshold, there will be sizable size
> improvement for many benchmarks without regressing performance, shall we
> use the reduced threshold for O2 instead?
>
>
> Yes, all the ones here IIUC:
>
>
>
>
> However it is likely that we could consider these “small” benchmarks
> should use -Os if they're sensitive to size, and so O2 would be fine
with
> the more aggressive threshold (as larger program aren’t affected).
>
> With good heuristic we’d have every dot forming a straight line
> code_size_increase = m * runtime_perf (with m as small as possible). The
> current lack of shape (or the exact opposite distribution to the ideal I
> imagine above) seems to show that our "profitability” heuristics are
pretty
> bad and the current threshold knob is bad predictor of the runtime
> performance.
>
To get that, profile data is needed. Downstream component bugs also makes
it hard to achieve.

David
>
> —
> Mehdi
>
>
>
> It is usually tiny programs that are sensitive (size) to this change. The
> size vs size increase chart confirms that point. There is basically no
> large size increase for programs > 1MB (clang release build size is
78M).
> In other words, I believe the actual size impact on real world applications
> should be negligible.  This behavior is very different from the case when
> we increase inline threshold for instance -- which will have size impact
> across the board. The latter is certainly more limited to higher
> optimization levels.
>
> thanks,
>
> David
>
>
>
>
>
>
> I see two further directions for Dehao that make sense here (at least to
> me):
> 1) I suspect we should investigate *why* the size increases are happening
> without helping speed. I can imagine some reasons that this would of course
> happen (cold loops getting unrolled), but especially in light of the
> oddities you point out above, I suspect there may be issues where more
> unrolling is uncovering other problems and if we fix those other problems
> the shape of things will be different. We should at least address the
> issues you uncovered above.
>
> 2) If this turns out to be architecture specific (it seems that way at
> least initially, but hard to tell for sure with different benchmark sets)
> we might make AArch64 and x86 use different thresholds here. I'm
skeptical
> about this though. I suspect we should do #1, and we'll either get a
> different shape, or just decide that O3 is more appropriate.
>
>
> Maybe the compile time impact is what should be driving that discussion
> the most? I'm afraid I don't have compile time numbers.
>
>
> FWIW, I strongly suspect that for *this* change, compile time and code
> size will be pretty precisely correlated. Dehao's data shows that to be
> true in several cases certainly.
>
>
> Ultimately, I guess this boils down to what exactly the difference is in
> intent between O2 and O3, which seems like a never-ending discussion...
>
>
> The definitions I am working from are here:
>
>
https://github.com/llvm-project/llvm-project/blob/master/llvm/include/llvm/Passes/PassBuilder.h#L81-L90
>
> I've highlighted the part that makes me think O3 is better here: the
code
> size increases (and thus compile time increases) don't seem to
correspond
> to runtime improvements.
>
>
>
> Hoping you find this useful,
>
>
> Very. Once again, this kind of data and analysis is awesome. =D
>
>
> Kristof
>
>
> On Tue, Feb 14, 2017 at 1:06 PM Kristof Beyls via llvm-dev <
> llvm-dev at lists.llvm.org> wrote:
>
> I've run the patch on https://reviews.llvm.org/D28368 on the test-suite
> and other benchmarks, for AArch64 -O3 -fomit-frame-pointer, both for
> Cortex-A53 and Cortex-A57.
>
> The geomean over the few hundred programs in there is roughly the same for
> Cortex-A53 and Cortex-A57: a bit over 1% improvement in execution speed for
> a bit over 5% increase in code size.
> Obviously I wouldn't want this for optimization levels where code size
is
> of any concern, like -Os or -Oz, but don't have a problem with this
going
> in for other optimization levels where this isn't a concern.
>
> Thanks,
>
> Kristof
>
>
>
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org
> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>
>
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org
> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>
>
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On Thu, Feb 16, 2017 at 7:06 PM Xinliang David Li <xinliangli at
gmail.com>
wrote:
> On Thu, Feb 16, 2017 at 5:43 PM Mehdi Amini <mehdi.amini at
apple.com> wrote:
>
> On Feb 16, 2017, at 4:41 PM, Xinliang David Li via llvm-dev <
> llvm-dev at lists.llvm.org> wrote:
>
> On Thu, Feb 16, 2017 at 3:45 PM, Chandler Carruth via llvm-dev <
> llvm-dev at lists.llvm.org> wrote:
>
> First off, I just want to say wow and thank you. This kind of data is
> amazing. =D
>
> On Thu, Feb 16, 2017 at 2:46 AM Kristof Beyls <Kristof.Beyls at
arm.com>
> wrote:
>
> The biggest relative code size increases indeed didn't happen for the
> biggest programs, but instead for a few programs weighing in at about
100KB.
> I'm assuming the Google benchmark set covers much bigger programs than
the
> ones displayed here.
> FWIW, the cluster of programs where code size increases between 60% to 80%
> with a size of about 100KB, all come from MultiSource/Benchmarks/TSVC.
> Interestingly, these programs seem to have float and double variants,  e.g.
> (MultiSource/Benchmarks/TSVC/Searching-flt/Searching-flt and
> MultiSource/Benchmarks/TSVC/Searching-dbl/Searching-dbl), and the code size
> bloat only happens for the double variants.
>
>
> I think we should definitely look at this (as it seems likely to be a bug
> somewhere), but I'm also not overly concerned with size regressions in
the
> TSVC benchmarks which are unusually loop heavy and small. We've have
> several other changes that caused big fluctuations here.
>
>
>
> I think it may still be worthwhile to check if this also happens on other
> architectures, and why it happens only for the double-variants, not the
> float-variants.
>
>
> +1
>
> The second chart shows relative code size increase (vertical axis) vs
> relative performance improvement (horizontal axis):
> I manually checked the cause of the 3 biggest performance regressions
> (proprietary benchmark1: -13.70%;
> MultiSource/Applications/hexxagon/hexxagon: -10.10%;
> MultiSource/Benchmarks/FreeBench/fourinarow/fourinarow -5.23%).
> For the proprietary benchmark and hexxagon, the code generation didn't
> change for the hottest parts, so probably is caused by micro-architectural
> effects of code layout changes.
>
>
> This is always good to know, even though it is frustrating. =]
>
>
> For fourinarow, there seemed to be a lot more spill/fill code, so probably
> due to non-optimality of register allocation.
>
>
> This is something we should probably look at. If you have the output lying
> around, maybe file a PR about it?
>
> The third chart below just zooms in on the above chart to the -5% to 5%
> performance improvement range:
> <unroll_codesize_vs_performance_zoom.png>
>
>
> Whether to enable the increase in unroll threshold only at O3 or also at
> O2: I don't have a strong opinion based on the above data.
>
>
> FWIW, this data seems to clearly indicate that we don't get performance
> wins with any consistency when the code size goes up (and thus the change
> has impact). As a consequence, I pretty strongly suspect that this should
> be *just* used at O3 at least for now.
>
>
> The correlation is there -- when there is performance improvement, there
> is size increase.
>
>
> I didn’t quite get this impression from the graph, the highest improvement
> didn’t come with code size increase:
>
>
>
>
> And on the other hand there were many code-size increase without any
> runtime improvement.
>
>
>
> the zoomed in graph does not show the trend indeed, but the original graph
> does 😀
>
I kind of agree with how Mehdi is interpreting this data. =]

>
>
> The opposite is not true -- but that is expected. If the speedup is in the
> cold path, there won't be visible performance improvement but size
increase.
>
> Put it another way. If we reduce the threshold, there will be sizable size
> improvement for many benchmarks without regressing performance, shall we
> use the reduced threshold for O2 instead?
>
>
> Yes, all the ones here IIUC:
>
>
>
>
> However it is likely that we could consider these “small” benchmarks
> should use -Os if they're sensitive to size, and so O2 would be fine
with
> the more aggressive threshold (as larger program aren’t affected).
>
> With good heuristic we’d have every dot forming a straight line
> code_size_increase = m * runtime_perf (with m as small as possible). The
> current lack of shape (or the exact opposite distribution to the ideal I
> imagine above) seems to show that our "profitability” heuristics are
pretty
> bad and the current threshold knob is bad predictor of the runtime
> performance.
>
>
> To get that, profile data is needed. Downstream component bugs also makes
> it hard to achieve.
>
Sure. I think what I'm saying (don't want to put words in Mehdi's
mouth) is
that until the bugs are fixed, this probably belongs at O3 rather than O2
based on this data.

FWIW, I suspect there might be some bug fixes that would change this even
without profile data, but its of course impossible to know until the bugs
are analyzed.


I don't think this should be a show stopper, I think the change is still a
really good one at O3.
>
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