[llvm-dev] llvm and clang are getting slower

[Sean Silva via llvm-dev]

On Tue, Mar 8, 2016 at 10:42 AM, Richard Smith via llvm-dev <
llvm-dev at lists.llvm.org> wrote:

> On Tue, Mar 8, 2016 at 8:13 AM, Rafael Espíndola
> <llvm-dev at lists.llvm.org> wrote:
> > I have just benchmarked building trunk llvm and clang in Debug,
> > Release and LTO modes (see the attached scrip for the cmake lines).
> >
> > The compilers used were clang 3.5, 3.6, 3.7, 3.8 and trunk. In all
> > cases I used the system libgcc and libstdc++.
> >
> > For release builds there is a monotonic increase in each version. From
> > 163 minutes with 3.5 to 212 minutes with trunk. For comparison, gcc
> > 5.3.2 takes 205 minutes.
> >
> > Debug and LTO show an improvement in 3.7, but have regressed again in
> 3.8.
>
> I'm curious how these times divide across Clang and various parts of
> LLVM; rerunning with -ftime-report and summing the numbers across all
> compiles could be interesting.
>

Based on the results I posted upthread about the relative time spend in the
backend for debug vs release, we can estimate this.
To summarize:
10% of time spent in LLVM for Debug
33% of time spent in LLVM for Release
(I'll abbreviate "in LLVM" as just "backend"; this is "backend" from
clang's perspective)

Let's look at the difference between 3.5 and trunk.

For debug, the user time jumps from 174m50.251s to 197m9.932s.
That's {10490.3, 11829.9} seconds, respectively.
For release, the corresponding numbers are:
{9826.71, 12714.3} seconds.

debug35 = 10490.251
debugTrunk = 11829.932

debugTrunk/debug35 == 1.12771
debugRatio = 1.12771

release35 = 9826.705
releaseTrunk = 12714.288

releaseTrunk/release35 == 1.29385
releaseRatio = 1.29385

For simplicity, let's use a simple linear model for the distribution of
slowdown between the frontend and backend: a constant factor slowdown for
the backend, and an independent constant factor slowdown for the frontend.
This gives the following linear system:
debugRatio = .1 * backendRatio + (1 - .1) * frontendRatio
releaseRatio = .33 * backendRatio + (1 - .33) * frontendRatio

Solving this linear system we find that under this simple model, the
expected slowdown factors are:
backendRatio = 1.77783
frontendRatio = 1.05547

Intuitively, backendRatio comes out larger in this comparison because we
see the biggest slowdown during release (1.29 vs 1.12), and during release
we are spending a larger fraction of time in the backend (33% vs 10%).

Applying this same model to across Rafael's data, we find the following
(numbers have been rounded for clarity):

transition       backendRatio   frontendRatio
3.5->3.6         1.08           1.03
3.6->3.7         1.30           0.95
3.7->3.8         1.34           1.07
3.8->trunk       0.98           1.02

Note that in Rafael's measurements LTO is pretty similar to Release from a
CPU time (user time) standpoint. While the final LTO link takes a large
amount of real time, it is single threaded. Based on the real time numbers
the LTO link was only spending about 20 minutes single-threaded (i.e. about
20 minutes CPU time), which is pretty small compared to the 300-400 minutes
of total CPU time. It would be interesting to see the numbers for -O0 or
-O1 per-TU together with LTO.

-- Sean Silva


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