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

Tue Nov 1 14:07:47 PDT 2016

Oops... pressed the wrong button and sent out early...

On Tue, Nov 1, 2016 at 2:01 PM, Dehao Chen <dehao at google.com> wrote:

> If Hal's proposal is for SamplePGO purpose, let me clarify some design
> principles of SamplePGO.
>
> The profile for sample pgo uses source location as the key to map the
> execution count back to IR. This design is based on the principle that we
> do not want the profile to be tightly couple with compiler IR. Instead,
> profile is simple an attribute of the source code. We have been benefited
>  a lot from this design that the profile can easily be reused across
> different source versions and compiler versions, or even compilers.
>
> That being said, the design to encode more info into discriminator does
> not mean that we will change the profile. The encoded info in discriminator
> will be handled by the create_llvm_prof tool, which combines counts from
> different clones of the same source code and generate the combined profile
> data. The output profile will not have any cloning/dupliaction bits at all.
> So for the initial example profile I provided, the output profile will be:
>

#1: 10
#3: 80

Not:

#1: 10
#3.0x400: 70
#3.0x10400: 5
#3.0x20400: 3
#3.0x30400: 2

The goal of the proposed change, is to make profile more accurately
represent the attribute of the source.
The non-goal of the proposed change, is to provide more context in the
profile to present the behavior of program in the context of different
context.

If we are pursuing more context-sensitive profile, that would be a very
different design. In this design, we will need to read profile multiple
times, and have the profile tightly coupled with the compiler IR/pass
manager. That is doable, but I don't think that probably better suits
instrumentation based PGO's domain. Comments?

Thanks,
Dehao

>
> On Tue, Nov 1, 2016 at 1:04 PM, Hal Finkel <hfinkel at anl.gov> wrote:
>
>>
>> ------------------------------
>>
>> *From: *"Paul Robinson" <paul.robinson at sony.com>
>> *To: *"Dehao Chen" <dehao at google.com>, "Hal Finkel" <hfinkel at anl.gov>
>> *Cc: *"Xinliang David Li" <davidxl at google.com>, llvm-dev at lists.llvm.org
>> *Sent: *Tuesday, November 1, 2016 2:15:38 PM
>> *Subject: *RE: [llvm-dev] (RFC) Encoding code duplication factor
>> in        discriminator
>>
>> As illustrated in the above example, it is not like "vectorization has a
>> distinct bit". All different optimizations make clones of code which will
>> be labeled by UIDs represented by N (e.g. 8) bits. In this way, the space
>> will be capped by the number of clones all optimizations have made, instead
>> of # of optimizations that has applied. And it will be capped at 2^N-1. The
>> cons of using uid is that you will not know if a clone is coming from
>> vectorization or unroll or loop distribution.
>>
>> Okay, but that kind of semantic mapping is important. How should we
>> encode/recover that information? To be clear, I'm not saying that we need
>> to implement that up front, but there needs to be a clear path to an
>> implementation, because I don't want to have two disjoint schemes.
>>
>>
>>
>> You mean that you want to know which optimization created the clone? How
>> would you use that info? Looks to me this will expose compiler
>> implementation detail in debug info.
>>
>>
>>
>> This is still doable, assume we have 15 interesting optimizations to
>> track, we can use 4 bits to encode the optimization type that created the
>> clone. But this becomes nasty if the a clone is created by more than one
>> optimizations. In that way, discriminator may not be fit for this purpose.
>>
>>
>>
>> My understanding was that the encoding scheme would allow the profiling
>> analysis to correctly map execution data back to the original source
>> construct, while preserving the property that each distinct basic block
>> would have its own discriminator value.  That is, the execution data would
>> be attributed back to the original source construct, not whatever each
>> individual optimization had done to it, and the data for the original
>> source construct would correctly reflect the execution (e.g. profiling says
>> you got 82 hits on the original loop, rather than reporting 20 hits on the
>> unrolled-by-4 loop plus 1 each on 2 of the trailing copies).
>>
>>
>>
>> It sounds like Hal is thinking that the per-discriminator execution info
>> would be preserved down to the point where an individual optimization could
>> look at the profile for each piece, and make decisions on that basis.
>>
>>
>>
>> I'm not clear how that would be possible, as the optimization would have
>> to first do the transform (or predict how it would do the transform) in
>> order to see which individual-discriminator counts mapped to which actual
>> blocks, and then make some kind of decision about whether to do the
>> transform differently based on that information.  Then, if the optimization
>> did choose to do the transform differently, then that leaves the IR in a
>> state where the individual discriminators *cannot* map back to it.  (Say
>> you unroll by 2 instead of 4; then you have only 1 trailing copy, not 3,
>> and a discriminator that maps to the second trailing copy now maps to
>> nothing.  The individual-discriminator data becomes useless.)
>>
>>
>>
>> Am I expressing this well enough to show that what Hal is looking for is
>> not feasible?
>>
>> Yes, it will need to predict how the transformation would affect the
>> blocks produced. That does not seem problematic (at least at a coarse
>> level). Yes, if transformations made earlier in the pipeline make different
>> decisions, then that will invalidate later fine-grained data (at least
>> potentially). I don't see how any of this makes this infeasible. We just
>> need a way for the profiling counts, per descriminator, to remain
>> available, and for the transformations themselves to know which
>> discriminators (loop ids, or whatever) to consider.
>>
>>  -Hal
>>
>> --paulr
>>
>>
>>
>>
>>
>>
>> --
>> Hal Finkel
>> Lead, Compiler Technology and Programming Languages
>> Leadership Computing Facility
>> Argonne National Laboratory
>>
>
>
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