[LLVMdev] [llvm-commits] [PATCH] BasicBlock Autovectorization Pass

[Hal Finkel]

On Tue, 2011-11-08 at 12:12 +0100, Tobias Grosser wrote:
> On 11/08/2011 11:45 AM, Hal Finkel wrote:
> > I've attached the latest version of my autovectorization patch.
> >
> > Working through the test suite has proved to be a productive
> > experience ;) -- And almost all of the bugs that it revealed have now
> > been fixed. There are still two programs that don't compile with
> > vectorization turned on, and I'm working on those now, but in case
> > anyone feels like playing with vectorization, this patch will probably
> > work for you.
> 
> Hey Hal,
> 
> those are great news. Especially as the numbers seem to show that 
> vectorization has a significant performance impact. What did you compare 
> exactly. 'clang -O3' against 'clang -O3 -mllvm -vectorize'?

Yes. [I've tested the current patch directly using opt -vectorize
-unroll-allow-partial; for running the test suite I recompiled
llvm/clang to hardcode the options as I wanted them].

> 
> > The largest three performance speedups are:
> > SingleSource/Benchmarks/BenchmarkGame/puzzle - 59.2% speedup
> > SingleSource/UnitTests/Vector/multiplies - 57.7% speedup
> > SingleSource/Benchmarks/Misc/flops-7 - 50.75% speedup
> >
> > The largest three performance slowdowns are:
> > MultiSource/Benchmarks/MiBench/security-rijndael/security-rijndael -
> > 114% slowdown
> > MultiSource/Benchmarks/MiBench/network-patricia/network-patricia - 66.6%
> > slowdown
> > SingleSource/Benchmarks/Misc/flops-8 - 64.2% slowdown
> >
> Interesting. Do you understand what causes these slowdowns? Can your 
> heuristic be improved?

I've not specifically looked at these cases.

Generally, I've observed slowdowns from the introduction of too many
permutations per chain (the chain selection procedure can be changed to
help this, and I'll work on that). Also, sometimes legalization of
non-native vector operations creates inefficient code, and I'll also
look at these cases in more detail.

> 
> > Largest three compile-time slowdowns:
> > MultiSource/Benchmarks/MiBench/security-rijndael/security-rijndael -
> > 1276% slowdown
> > SingleSource/Benchmarks/Misc/salsa20 - 1000% slowdown
> > MultiSource/Benchmarks/Trimaran/enc-3des/enc-3des - 508% slowdown
> 
> Yes, that is a lot. Do you understand if this time is invested well 
> (does it give significant speedups)?

No, not always. Actually, the security-rijndael test not only takes the
longest to vectorize, but it also shows the largest slowdown. This is
certainly something that I'll investigate.

> 
> If I understood correctly it seems your vectorizer has quadratic 
> complexity which may cause large slowdowns. Do you think it may be 
> useful/possible to make it linear by introducing a constant upper bound 
> somewhere? E.g. limiting it to 10/20/100 steps. Maybe we are lucky and 
> most of the vectorization opportunities are close by (in some sense), 
> such that we get most of the speedup by locking at a subset of the problem.

Yes, I agree. That makes a lot of sense.

What would be even better is if the loop unroller would intermix
statements from the loops where possible instead of leaving it to the
vectorizer to do all of the grouping after the fact. That, I fear, is a
whole other project.

> 
> > Not everything slows down, MultiSource/Benchmarks/Prolangs-C
> > ++/city/city, for example, compiles 10% faster with vectorization
> > enabled; but, for the most part, things certainly take longer to compile
> > with vectorization enabled. The average slowdown over all tests was 29%,
> > the median was 11%. On the other hand, the average speedup over all
> > tests was 5.2%, the median was 1.3%.
> Nice. I think this is a great start.

Thanks!

> 
> > Compared to previous patches, which had a minimum required chain length
> > of 3 or 4, I've now made the default 6. While using a chain length of 4
> > worked well for targeted benchmarks, it caused an overall slowdown on
> > almost all test-suite programs. Using a minimum length of 6 causes, on
> > average, a speedup; so I think that is a better default choice.
> 
> I also try to understand if it is possible to use your vectorizer for 
> Polly. My idea is to do some clever loop unrolling.
> 
> Starting from this loop.
> 
> for (int i = 0; i < 4; i++)
>     A[i] += 1;
>     A[i] = B[i] + 3;
>     C[i] = A[i];
> 
> The classical unroller would create this code:
> 
>     A[0] += 1;
>     A[0] = B[i] + 3;
>     C[0] = A[i];
> 
>     A[1] += 1;
>     A[1] = B[i] + 3;
>     C[1] = A[i];
> 
>     A[2] += 1;
>     A[2] = B[i] + 3;
>     C[2] = A[i];
> 
>     A[3] += 1;
>     A[3] = B[i] + 3;
>     C[3] = A[i];
> 
> However, in case I can prove this loop is parallel, I want to create 
> this code:
> 
>     A[0] += 1;
>     A[1] += 1;
>     A[2] += 1;
>     A[3] += 1;
> 
>     A[0] = B[i] + 3;
>     A[1] = B[i] + 3;
>     A[2] = B[i] + 3;
>     A[3] = B[i] + 3;
> 
>     C[0] = A[i];
>     C[1] = A[i];
>     C[2] = A[i];
>     C[3] = A[i];
> 
> I assume this will allow the vectorization of test cases, that failed 
> because of possible aliasing. However, I am more interested, if the
> execution order change could also improve the vectorization outcome or 
> reduce compile time overhead of your vectorizer.

Yes, this would certainly help.

By the way, the current implementation, by default, it will create
unaligned vector loads and stores, but these are generally broken up by
the legalizer. This behavior can be suppressed using the
-bb-vectorize-aligned-only flag. It would be nice if the loop unroller
chose the unrolling factor to preserve the maximum available alignment,
but I don't think that it currently does so.

One problem with the current implementation is that it relies on
GetPointerBaseWithConstantOffset to determine if two loads or stores
share the same base address. This fails with partially-unrolled loops
because it cannot "undo" all of the additions to the offset induction
variable in order to understand that some of the loads and stores are
really adjacent in memory. This is something that I think can be
improved within the vectorizer itself, and I'm planning on doing some
work on this in the future.

Thanks for your feedback,
Hal

> 
> Thanks for working on the vectorization
> Cheers
> 
> Tobi
> 
> 
> 
> 
> 

-- 
Hal Finkel
Postdoctoral Appointee
Leadership Computing Facility
Argonne National Laboratory