[llvm-dev] (RFC) Encoding code duplication factor in discriminator

[Xinliang David Li via llvm-dev]

The large percentages are from those tiny benchmarks. If you look at
omnetpp (0.52%), and xalanc (1.46%), the increase is small. To get a better
average increase, you can sum up total debug_line size before and after and
compute percentage accordingly.

David

On Thu, Oct 27, 2016 at 1:11 PM, Dehao Chen <dehao at google.com> wrote:

> The impact to debug_line is actually not small. I only implemented the
> part 1 (encoding duplication factor) for loop unrolling and loop
> vectorization. The debug_line size overhead for "-O2 -g1" binary of speccpu
> C/C++ benchmarks:
>
> 433.milc 23.59%
> 444.namd 6.25%
> 447.dealII 8.43%
> 450.soplex 2.41%
> 453.povray 5.40%
> 470.lbm 0.00%
> 482.sphinx3 7.10%
> 400.perlbench 2.77%
> 401.bzip2 9.62%
> 403.gcc 2.67%
> 429.mcf 9.54%
> 445.gobmk 7.40%
> 456.hmmer 9.79%
> 458.sjeng 9.98%
> 462.libquantum 10.90%
> 464.h264ref 30.21%
> 471.omnetpp 0.52%
> 473.astar 5.67%
> 483.xalancbmk 1.46%
> mean 7.86%
> Dehao
>
> On Thu, Oct 27, 2016 at 11:55 AM, Xinliang David Li <davidxl at google.com>
> wrote:
>
>> Do you have an estimate of the debug_line size increase? I guess it will
>> be small.
>>
>> David
>>
>> On Thu, Oct 27, 2016 at 11:39 AM, Dehao Chen <dehao at google.com> wrote:
>>
>>> Motivation:
>>> Many optimizations duplicate code. E.g. loop unroller duplicates the
>>> loop body, GVN duplicates computation, etc. The duplicated code will share
>>> the same debug info with the original code. For SamplePGO, the debug info
>>> is used to present the profile. Code duplication will affect profile
>>> accuracy. Taking loop unrolling for example:
>>>
>>> #1 foo();
>>> #2 for (i = 0; i < N; i++) {
>>> #3   bar();
>>> #4 }
>>>
>>> If N is 8 during runtime, a reasonable profile will look like:
>>>
>>> #1: 10
>>> #3: 80
>>>
>>> But if the compiler unrolls the loop by a factor of 4, the callsite to
>>> bar() is duplicated 4 times and the profile will look like:
>>>
>>> #1: 10
>>> #3: 20
>>>
>>> The sample count for #3 is 20 because all 4 callsites to bar() are
>>> sampled 20 times each, and they shared the same debug loc (#3) so that 20
>>> will be attributed to #3 (If one debugloc is mapped by multiple
>>> instructions, the max sample count of these instructions is used as
>>> debugloc's sample count).
>>>
>>> When loading this profile into compiler, it will think the loop trip
>>> count is 2 instead of 8.
>>>
>>> Proposal:
>>> When compiler duplicates code, it encodes the duplication info in the
>>> debug info. As the duplication is not interesting to debugger, I propose to
>>> encode this as part of the discriminator.
>>>
>>> There are 2 types of code duplication:
>>>
>>> 1. duplicated code are guaranteed to have the same execution count (e.g.
>>> loop unroll and loop vectorize). We can record the duplication factor, for
>>> the above example "4" is recorded in the discriminator.
>>> 2. duplicated code that may have different execution count (e.g. loop
>>> peel and gvn). For a same debugloc, a unique number is assigned to each
>>> copy and encoded in the discriminator.
>>>
>>> Assume that the discriminator is uint32. The traditional discriminator
>>> is less than 256, let's take 8 bit for it. For duplication factor (type 1
>>> duplication), we assume the maximum unroll_factor * vectorize_factor is
>>> less than 256, thus 8 bit for it. For unique number(type 2 duplication), we
>>> assume code is at most duplicated 32 times, thus 5 bit for it. Overall, we
>>> still have 11 free bits left in the discriminator encoding.
>>>
>>> Let's take the original source as an example, after loop unrolling and
>>> peeling, the code may looks like:
>>>
>>> for (i = 0; i < N & 3; i+= 4) {
>>>   foo();  // discriminator: 0x40
>>>   foo();  // discriminator: 0x40
>>>   foo();  // discriminator: 0x40
>>>   foo();  // discriminator: 0x40
>>> }
>>> if (i++ < N) {
>>>   foo();   // discriminator: 0x100
>>>   if (i++ < N) {
>>>     foo(); // discriminator: 0x200
>>>     if (i++ < N) {
>>>       foo();  // discriminator: 0x300
>>>     }
>>>   }
>>> }
>>>
>>> The cost of this change would be increased debug_line size because: 1.
>>> we are recording more discriminators 2. discriminators become larger and
>>> will take more ULEB128 encoding.
>>>
>>> The benefit is that the sample pgo profile can accurately represent the
>>> code execution frequency. And we do not need to introduce new building
>>> blocks to debug info.
>>>
>>> Comments?
>>>
>>> Thanks,
>>> Dehao
>>>
>>
>>
>
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