llvm dev - Mar 2013 - [LLVMdev] [Polly]GSoC Proposal: Reducing LLVM-Polly Compiling overhead

Hello Tobi,

I am interested in Polly project. Polly seems to be a very promising tool to
find out program parallelization based on LLVM infrastructure.   However, I find
that Polly analysis and optimization can consume significant compiling time, so
I propose a GSoC project to reduce Polly compiling time and I hope my work can
make the Polly tool more applicable for all LLVM users.

I have done some preliminary experiments.  My experimental environment is built
as follows:
First, I build the LLVM, Clang and Polly using -O3 option, so all of these tools
can be run in best case;
Second,  I evaluate the compiling time of Polybench using the following options:
      Clang-O3:  clang -O3  (the basic clang without polly)
      Polly-basic:  clang -Xclang -load -Xclang LLVMPolly.so -O3  (load polly
but no use of polly optimization)
      Polly-optimize: clang -Xclang -load -Xclang LLVMPolly.so -mllvm -polly -O3
(use polly optimization)

The preliminary experimental results are as follows: (benchmarks are collected
from Po

|
| Clang
(seconds) | Polly-basic
(seconds) | Polly-optimize
(seconds) | Polly-load overhead | Polly-optimize
overhead |
| 2mm.c | 0.786 | 0.802 | 1.944 | 2.0% | 147.3% |
| correlation.c | 0.782 | 0.792 | 2.005 | 1.3% | 156.4% |
| gesummv.c | 0.583 | 0.603 | 1.08 | 3.4% | 85.2% |
| ludcmp.c | 0.787 | 0.806 | 2.475 | 2.4% | 214.5% |
| 3mm.c | 0.786 | 0.811 | 2.617 | 3.2% | 233.0% |
| covariance.c | 0.73 | 0.74 | 2.294 | 1.4% | 214.2% |
| gramschmidt.c | 0.63 | 0.643 | 1.134 | 2.1% | 80.0% |
| seidel.c | 0.632 | 0.645 | 2.036 | 2.1% | 222.2% |
| adi.c | 0.8 | 0.811 | 3.044 | 1.4% | 280.5% |
| doitgen.c | 0.742 | 0.752 | 2.32 | 1.3% | 212.7% |
| instrument.c | 0.445 | 0.45 | 0.495 | 1.1% | 11.2% |
| atax.c | 0.614 | 0.627 | 1.007 | 2.1% | 64.0% |
| gemm.c | 0.721 | 0.74 | 1.327 | 2.6% | 84.0% |
| jacobi-2d-imper.c | 0.721 | 0.735 | 2.211 | 1.9% | 206.7% |
| bicg.c | 0.577 | 0.597 | 1.01 | 3.5% | 75.0% |
| gemver.c | 0.799 | 0.857 | 1.296 | 7.3% | 62.2% |
| lu.c | 0.68 | 0.702 | 1.132 | 3.2% | 66.5% |
| Average |
|
|
| 2.49% | 142.10% |

Experimental results show that Polly analysis and optimization can leads to 142%
extra compiling overhead, which maybe unacceptable in many large software
building. As a result, it is an urgent task to reduce the compiling time of
Polly analysis and optimization.

My plan for this proposal is to reduce Polly compiling overhead step by step:
1) Investigate the details of Polly, find out how much time spent on analysis
and how much time spent on optimization. Of course it is very important to
distinguish the overhead on codes where  Polly is applicable and codes where
Polly is not applicable.
2) Profile the Polly to find out the hot code and find out the sources of
compiling overhead; Based on the profiling, I will try to rewrite the hot code
to improving the compiling process.
3) Remove expensive analysis passes. For example, the scop detection currently
requires both the post-dominance analysis
as well as the dominance frontier analysis. Not requiring these up front (at
all) would be great.
4) Canonicalization passes scheduled before Polly.  Before running Polly, we
currently schedule a set of passes to canonicalize the LLVM-IR on which the scop
detection is run on. If I can reduce the number of preparing passes, then the
compiling overhead can be reduced.
5) Find out other ways to reduce compiling overhead.

Hope you can give me further advices.

Best Regards,
Star Tan
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On 03/17/2013 11:54 PM, Star Tan wrote:
>   Hello Tobi,
>
> I am interested in Polly project. Polly seems to be a very promising tool
to find out program parallelization based on LLVM infrastructure.   However, I
find that Polly analysis and optimization can consume significant compiling
time, so I propose a GSoC project to reduce Polly compiling time and I hope my
work can make the Polly tool more applicable for all LLVM users.

Dear Star Tan,

the project your propose sounds both interesting and important. As you 
correctly pointed out, maintaining fast compile times when Polly is 
enabled is a very important point. Especially, if we want to think of 
enabling Polly by default.
> I have done some preliminary experiments.  My experimental environment is
built as follows:
> First, I build the LLVM, Clang and Polly using -O3 option, so all of these
tools can be run in best case;
> Second,  I evaluate the compiling time of Polybench using the following
options:
>        Clang-O3:  clang -O3  (the basic clang without polly)
>        Polly-basic:  clang -Xclang -load -Xclang LLVMPolly.so -O3  (load
polly but no use of polly optimization)
>        Polly-optimize: clang -Xclang -load -Xclang LLVMPolly.so -mllvm
-polly -O3 (use polly optimization)
I believe this setup is a very good start. However, to draw useful 
conclusions we probably need more information:

1) Did you build LLVM/Polly in release mode?

The compile times with and without Polly look very high. Compiling 2mm 
with a current version of clang takes 0.076 seconds for me, whereas you
report a compile time of 0.780 seconds. This may caused by performance
differences of our machines or, what I believe is more likely, that you
did not compile LLVM and Polly in Release mode. Profiling of debug 
builds may give a wrong idea on where compile time is spent. Can you
verify you built in Release mode?

2) Compile time impact when Polly does not optimize the program code

The benchmarks you have chosen can be optimized well by Polly. This is
obviously a nice thing, but it also implies that Polly transforms and
optimizes a large percentage of this code. In cases, where Polly can 
create an optimized version of the code, (limited) increases in compile 
time are often acceptable. However, one area where we should be super 
critical with compile time is the case when Polly is enabled, but when 
it can not perform any useful transformation.

For polybench, you can get a first idea of the current overhead, by 
timing only the polly-detect part, but by disabling the polly 
optimizations and the polly code-generation. However, to get a more 
realistic picture, you probably want to run Polly on the LLVM 
test-suite. I know of some in-house nightly testers, that track Polly
performance on the LLVM test suite. Your work would be even another 
reason to get a public version of such a tester. I will see if I can get 
hardware to do so. Meanwhile, you can run it on your own machine.
> The preliminary experimental results are as follows: (benchmarks are
collected from Po
>
> |
> | Clang
> (seconds) | Polly-basic
> (seconds) | Polly-optimize
> (seconds) | Polly-load overhead | Polly-optimize
> overhead |
> | 2mm.c | 0.786 | 0.802 | 1.944 | 2.0% | 147.3% |
> | correlation.c | 0.782 | 0.792 | 2.005 | 1.3% | 156.4% |
> | gesummv.c | 0.583 | 0.603 | 1.08 | 3.4% | 85.2% |
> | ludcmp.c | 0.787 | 0.806 | 2.475 | 2.4% | 214.5% |
> | 3mm.c | 0.786 | 0.811 | 2.617 | 3.2% | 233.0% |
> | covariance.c | 0.73 | 0.74 | 2.294 | 1.4% | 214.2% |
> | gramschmidt.c | 0.63 | 0.643 | 1.134 | 2.1% | 80.0% |
> | seidel.c | 0.632 | 0.645 | 2.036 | 2.1% | 222.2% |
> | adi.c | 0.8 | 0.811 | 3.044 | 1.4% | 280.5% |
> | doitgen.c | 0.742 | 0.752 | 2.32 | 1.3% | 212.7% |
> | instrument.c | 0.445 | 0.45 | 0.495 | 1.1% | 11.2% |
It is interesting to see that the only file that does not contain a 
kernel that is optimized by polly, but just some auxiliary functions has 
a very low compile time overhead. This may imply that most of the 
compile time overhead is due to optimizations Polly can perform.
However, we should only draw conclusions from this after we verified 
those numbers are from a Release build.
> Experimental results show that Polly analysis and optimization can leads to
142% extra compiling overhead, which maybe unacceptable in many large software
building. As a result, it is an urgent task to reduce the compiling time of
Polly analysis and optimization.
>
> My plan for this proposal is to reduce Polly compiling overhead step by
step:
> 1) Investigate the details of Polly, find out how much time spent on
analysis and how much time spent on optimization. Of course it is very important
to distinguish the overhead on codes where  Polly is applicable and codes where
Polly is not applicable.
> 2) Profile the Polly to find out the hot code and find out the sources of
compiling overhead; Based on the profiling, I will try to rewrite the hot code
to improving the compiling process.
> 3) Remove expensive analysis passes. For example, the scop detection
currently requires both the post-dominance analysis
> as well as the dominance frontier analysis. Not requiring these up front
(at all) would be great.
> 4) Canonicalization passes scheduled before Polly.  Before running Polly,
we currently schedule a set of passes to canonicalize the LLVM-IR on which the
scop detection is run on. If I can reduce the number of preparing passes, then
the compiling overhead can be reduced.
> 5) Find out other ways to reduce compiling overhead.
Very good points.

I believe the general direction is great. As a next step I propose to 
continue your profiling work to get a better idea of the performance 
characteristics of Polly and to understand where compile time is spent.
I have some ideas myself, but I would prefer that you do this analysis 
independent of my suggestions to double check my own findings. I invite 
you to regularly report your findings. I should be able to both help you 
to ensure that the numbers you get allow us to draw correct conclusions 
and also to point you to source code changes that you could perform to 
reduce the compile time.

Thanks again for this interesting proposal.

All the best,
Tobias

Dear Tobias Grosser,


Thank you so much for your kind reply. Your advice is very helpful and
inspiring.
At 2013-03-18 20:40:50,"Tobias Grosser" <tobias at grosser.es>
wrote:
>On 03/17/2013 11:54 PM, Star Tan wrote:
>>   Hello Tobi,
>>
>> I am interested in Polly project. Polly seems to be a very promising
tool to find out program parallelization based on LLVM infrastructure.  
However, I find that Polly analysis and optimization can consume significant
compiling time, so I propose a GSoC project to reduce Polly compiling time and I
hope my work can make the Polly tool more applicable for all LLVM users.
>
>
>Dear Star Tan,
>
>the project your propose sounds both interesting and important. As you 
>correctly pointed out, maintaining fast compile times when Polly is 
>enabled is a very important point. Especially, if we want to think of 
>enabling Polly by default.
Yes, it is very important to reduce Polly compiling overhead, especially if
Polly is enabled by default. That is the motivation why I propose this GSoC
project and I hope my work can be helpful for the further development of Polly
project.
>
>> I have done some preliminary experiments.  My experimental environment
is built as follows:
>> First, I build the LLVM, Clang and Polly using -O3 option, so all of
these tools can be run in best case;
>> Second,  I evaluate the compiling time of Polybench using the following
options:
>>        Clang-O3:  clang -O3  (the basic clang without polly)
>>        Polly-basic:  clang -Xclang -load -Xclang LLVMPolly.so -O3 
(load polly but no use of polly optimization)
>>        Polly-optimize: clang -Xclang -load -Xclang LLVMPolly.so -mllvm
-polly -O3 (use polly optimization)
>
>I believe this setup is a very good start. However, to draw useful 
>conclusions we probably need more information:
>
>1) Did you build LLVM/Polly in release mode?
>
>The compile times with and without Polly look very high. Compiling 2mm 
>with a current version of clang takes 0.076 seconds for me, whereas you
>report a compile time of 0.780 seconds. This may caused by performance
>differences of our machines or, what I believe is more likely, that you
>did not compile LLVM and Polly in Release mode. Profiling of debug 
>builds may give a wrong idea on where compile time is spent. Can you
>verify you built in Release mode?
>
Thank you so much for your advice. You are right. I just use the polly.sh
(provided by Polly website) to build LLVM-Polly and it builds LLVM-Polly in
Debug mode in default.  I will rebuild the LLVM-Polly in Release mode by
configuring with --enable-optimized option and I will report the new data after
I redo these experiments in the new environments.
>2) Compile time impact when Polly does not optimize the program code
>
>The benchmarks you have chosen can be optimized well by Polly. This is
>obviously a nice thing, but it also implies that Polly transforms and
>optimizes a large percentage of this code. In cases, where Polly can 
>create an optimized version of the code, (limited) increases in compile 
>time are often acceptable. However, one area where we should be super 
>critical with compile time is the case when Polly is enabled, but when 
>it can not perform any useful transformation.
>
>For polybench, you can get a first idea of the current overhead, by 
>timing only the polly-detect part, but by disabling the polly 
>optimizations and the polly code-generation. However, to get a more 
>realistic picture, you probably want to run Polly on the LLVM 
>test-suite. I know of some in-house nightly testers, that track Polly
>performance on the LLVM test suite. Your work would be even another 
>reason to get a public version of such a tester. I will see if I can get 
>hardware to do so. Meanwhile, you can run it on your own machine.
>
That is OK. I will evaluate Polly using both LLVM testsuite and Polybench in the
following experiments.
>> The preliminary experimental results are as follows: (benchmarks are
collected from Po
>>
>> |
>> | Clang
>> (seconds) | Polly-basic
>> (seconds) | Polly-optimize
>> (seconds) | Polly-load overhead | Polly-optimize
>> overhead |
>> | 2mm.c | 0.786 | 0.802 | 1.944 | 2.0% | 147.3% |
>> | correlation.c | 0.782 | 0.792 | 2.005 | 1.3% | 156.4% |
>> | gesummv.c | 0.583 | 0.603 | 1.08 | 3.4% | 85.2% |
>> | ludcmp.c | 0.787 | 0.806 | 2.475 | 2.4% | 214.5% |
>> | 3mm.c | 0.786 | 0.811 | 2.617 | 3.2% | 233.0% |
>> | covariance.c | 0.73 | 0.74 | 2.294 | 1.4% | 214.2% |
>> | gramschmidt.c | 0.63 | 0.643 | 1.134 | 2.1% | 80.0% |
>> | seidel.c | 0.632 | 0.645 | 2.036 | 2.1% | 222.2% |
>> | adi.c | 0.8 | 0.811 | 3.044 | 1.4% | 280.5% |
>> | doitgen.c | 0.742 | 0.752 | 2.32 | 1.3% | 212.7% |
>> | instrument.c | 0.445 | 0.45 | 0.495 | 1.1% | 11.2% |
>
>It is interesting to see that the only file that does not contain a 
>kernel that is optimized by polly, but just some auxiliary functions has 
>a very low compile time overhead. This may imply that most of the 
>compile time overhead is due to optimizations Polly can perform.
>However, we should only draw conclusions from this after we verified 
>those numbers are from a Release build.
>
Yes, I will report the new data from the Release build in the next few days and
then we can discuss the results.
>> Experimental results show that Polly analysis and optimization can
leads to 142% extra compiling overhead, which maybe unacceptable in many large
software building. As a result, it is an urgent task to reduce the compiling
time of Polly analysis and optimization.
>>
>> My plan for this proposal is to reduce Polly compiling overhead step by
step:
>> 1) Investigate the details of Polly, find out how much time spent on
analysis and how much time spent on optimization. Of course it is very important
to distinguish the overhead on codes where  Polly is applicable and codes where
Polly is not applicable.
>> 2) Profile the Polly to find out the hot code and find out the sources
of compiling overhead; Based on the profiling, I will try to rewrite the hot
code to improving the compiling process.
>> 3) Remove expensive analysis passes. For example, the scop detection
currently requires both the post-dominance analysis
>> as well as the dominance frontier analysis. Not requiring these up
front (at all) would be great.
>> 4) Canonicalization passes scheduled before Polly.  Before running
Polly, we currently schedule a set of passes to canonicalize the LLVM-IR on
which the scop detection is run on. If I can reduce the number of preparing
passes, then the compiling overhead can be reduced.
>> 5) Find out other ways to reduce compiling overhead.
>
>Very good points.
>
>I believe the general direction is great. As a next step I propose to 
>continue your profiling work to get a better idea of the performance 
>characteristics of Polly and to understand where compile time is spent.
>I have some ideas myself, but I would prefer that you do this analysis 
>independent of my suggestions to double check my own findings. I invite 
>you to regularly report your findings. I should be able to both help you 
>to ensure that the numbers you get allow us to draw correct conclusions 
>and also to point you to source code changes that you could perform to 
>reduce the compile time.
>
>Thanks again for this interesting proposal.
>
>All the best,
>Tobias
>
>
Thank you so much for your kindly help. I will try my best to contribute to the
LLVM and Polly, and I hope this project can be useful for Polly development.
Best regards,
Star Tan
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