[llvm-dev] Machine learning and compiler optimizations: using inter-procedural analysis to select optimizations

Mon Mar 30 17:29:18 PDT 2020

On 3/27/20 3:46 PM, Shiva Stanford wrote:
> Hi Johannes - great we are engaging on this.
>
> Some responses now and some later.
>
> 1. When you say setup LLVM dev environment +. clang + tools etc, do you
> mean setup LLVM compiler code from the repo and build it locally? If so,
> yes, this is all done from my end - that is, I have built all this on my
> machine and compiled and run a couple of function passes. I have look at
> some LLVM emits from clang tools but I will familiarize more. I have added
> some small code segments, modified CMAKE Lists and re-built code to get a
> feel for the packaging  structure. Btw, is there a version of Basel build
> for this? Right now, I am using OS X as the SDK as Apple is the one that
> has adopted LLVM the most. But I can switch to Linux containers to
> completely wall off the LLVM build against any OS X system builds to
> prevent path obfuscation and truly have a separate address space. Is there
> a preferable environment? In any case, I am thinking of containerizing the
> build, so OS X system paths don't interfere with include paths - have you
> received feedback from other developers on whether the include paths
> interfere with OS X LLVM system build?

Setup sounds good.

I have never used OS X but people do and I would expect it to be OK.

I don't think you need to worry about this right now.

> 2. The attributor pass refactoring gives some specific direction as a
> startup project - so that's great. Let me study this pass and I will get
> back to you with more questions.

Sure.

> 3. Yes, I will stick to the style guide (Baaaah...Stanford is strict on
> code styling and so are you guys :)) for sure.

For better or worse.

Cheers,

   Johannes

> On Thu, Mar 26, 2020 at 9:42 AM Johannes Doerfert <
> johannesdoerfert at gmail.com> wrote:
>
>> Hi Shiva,
>>
>> apologies for the delayed response.
>>
>> On 3/24/20 4:13 AM, Shiva Stanford via llvm-dev wrote:
>>   > I am a grad CS student at Stanford and wanted to engage with EJ Park,
>>   > Giorgis Georgakoudis, Johannes Doerfert to further develop the Machine
>>   > Learning and Compiler Optimization concept.
>>
>> Cool!
>>
>>
>>   > My background is in machine learning, cluster computing, distributed
>>   > systems etc. I am a good C/C++ developer and have a strong background in
>>   > algorithms and data structure.
>>
>> Sounds good.
>>
>>
>>   > I am also taking an advanced compiler course this quarter at
>> Stanford. So I
>>   > would be studying several of these topics anyways - so I thought I
>> might as
>>   > well co-engage on the LLVM compiler infra project.
>>
>> Agreed ;)
>>
>>
>>   > I am currently studying the background information on SCC Call Graphs,
>>   > Dominator Trees and other Global and inter-procedural analysis to lay
>> some
>>   > ground work on how to tackle this optimization pass using ML models.
>> I have
>>   > run a couple of all program function passes and visualized call graphs
>> to
>>   > get familiarized with the LLVM optimization pass setup. I have also
>> setup
>>   > and learnt the use of GDB to debug function pass code.
>>
>> Very nice.
>>
>>
>>   > I have submitted the ML and Compiler Optimization proposal to GSOC
>> 2020. I
>>   > have added an additional feature to enhance the ML optimization to
>> include
>>   > crossover code to GPU and investigate how the function call graphs can
>> be
>>   > visualized as SCCs across CPU and GPU implementations. If the
>> extension to
>>   > GPU is too much for a summer project, potentially we can focus on
>>   > developing a framework for studying SCCs across a unified CPU, GPU setup
>>   > and leave the coding, if feasible, to next Summer. All preliminary
>> ideas.
>>
>> I haven't looked at the proposals yet (I think we can only after the
>> deadline). TBH, I'm not sure I fully understand your extension. Also,
>> full disclosure, the project is pretty open-ended from my side at least.
>> I do not necessarily believe we (=llvm) is ready for a ML driven pass or
>> even inference in practice. What I want is to explore the use of ML to
>> improve the code we have, especially heuristics. We build analysis and
>> transformations but it is hard to combine them in a way that balances
>> compile-time, code-size, and performance.
>>
>> Some high-level statements that might help to put my view into
>> perspective:
>>
>> I want to use ML to identify patterns and code features that we can
>> check for using common techniques but when we base our decision making
>> on these patterns or features we achieve better compile-time, code-size,
>> and/or performance.
>> I want to use ML to identify shortcomings in our existing heuristics,
>> e.g. transformation cut-off values or pass schedules. This could also
>> mean to identify alternative (combination of) values that perform
>> substantially better (on some inputs).
>>
>>
>>   > Not sure how to proceed from here. Hence my email to this list.
>> Please let
>>   > me know.
>>
>> The email to the list was a great first step. The next one usually is to
>> setup an LLVM development and testing environment, thus LLVM + Clang +
>> LLVM-Test Suite that you can use. It is also advised to work on a small
>> task before the GSoC to get used to the LLVM development.
>>
>> I don't have a really small ML "coding" task handy right now but the
>> project is more about experiments anyway. To get some LLVM development
>> experience we can just take a small task in the IPO Attributor pass.
>>
>> One thing we need and we don't have is data. The Attributor is a
>> fixpoint iteration framework so the number of iterations is pretty
>> integral part. We have a statistics counter to determine if the number
>> required was higher than the given threshold but not one to determine
>> the maximum iteration count required during compilation. It would be
>> great if you could add that, thus a statistics counter that shows how
>> many iterations where required until a fixpoint was found across all
>> invocations of the Attributor. Does this make sense? Let me know what
>> you think and feel free to ask questions via email or on IRC.
>>
>> Cheers,
>>     Johannes
>>
>> P.S. Check out the coding style guide and the how to contribute guide!
>>
>>
>>   > Thank you
>>   > Shiva Badruswamy
>>   > shivastanford at gmail.com
>>   >
>>   >
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>>
>>