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

[Johannes Doerfert via llvm-dev]

Hi Konstantin,

I didn't find the time to write new GSoC projects for 2021 yet but
if you are interested we could probably set one up in this area. I
also CC'ed Mircea who might be interested in this too, maybe as
(co-)mentor.

We could look at loop transformations such as unrolling and fusion,
similar to the inliner work. Best case, we can distill a heuristic
out of a model we learned. We could also  look at pass selection and
ordering. We started last year and I was hoping to continue. You
might want to watch https://youtu.be/TSMputNvHlk?t=617 
<https://youtu.be/TSMputNvHlk?t=617> and
https://youtu.be/nxfew3hsMFM?t=1435 <https://youtu.be/nxfew3hsMFM?t=1435> .

In case your interested in a runtime topic, I really would love to
have a predictor for grid/block/thread block size for (OpenMP) GPU
kernels. We are having real trouble on that end.

I also would like to look at ML use in testing and CI.

Let me know what area sounds most interesting to you and we can
take it from there.

~ Johannes


On 2/6/21 4:35 AM, Сидоров , Константин Сергеевич via llvm-dev wrote:
> Dear all,
>
> I would like to continue the discussion of the GSoC project I mentioned in
> the previous email. Now, when I know my way around the LLVM codebase, I
> would like to propose the first draft of the plan:
>
> * Improving heuristics for existing passes – to start the discussion, I
> propose to start the project by working on `MLInlineAdvisor` (as far as I
> understand, in this class the ML infrastructure is already developed, and
> thus it seems to be a good idea to start there) and after that switching to
> the other passes (e.g., `LoopVectorizationPlanner` seems to be a good
> candidate for such an approach, and `LoopRotate` class contains a
> profitability heuristic which could also be studied deeper).
> * Machine learning models to select the optimizations – to the best of my
> understanding, the key concept here is the pass manager, but here I don't
> quite understand the technical details of deciding which optimization to
> select. For this reason, I would like to discuss this part more thoroughly.
>
> If the project mentors are reading this mailing list and are interested in
> the discussion, can we start the discussion here?
>
> By the way – I would like to thank Stefanos for the comprehensive response
> to my previous questions that helped me to get started :)
>
> Looking forward to a further discussion,
> Konstantin Sidorov
>
> вт, 19 янв. 2021 г. в 07:04, Сидоров , Константин Сергеевич <
> sidorov.ks at phystech.edu>:
>
>> Dear all,
>>
>> My name is Konstantin Sidorov, and I am a graduate student in Mathematics
>> at Moscow Institute of Physics and Technology.
>>
>> I would like to work on a project "Machine learning and compiler
>> optimizations: using inter-procedural analysis to select optimizations"
>> during the Google Summer of Code 2021.
>>
>> I have an extensive background relevant to this project - in particular:
>>
>> * I have already participated in GSoC before in 2017 with mlpack
>> organization on the project "Augmented RNNs":
>> https://summerofcode.withgoogle.com/archive/2017/projects/4583913502539776/
>> * In 2019 I have graduated from the Yandex School of Data Analysis — a
>> two-year program in Data Analysis by Yandex (the leading Russian search
>> engine); more info on the curriculum could be also found at
>> https://yandexdataschool.com/.
>> * I have also been working as a software engineer at Adeptik from July
>> 2018 to date, where I have predominantly worked on projects on applied
>> combinatorial optimization problems, such as vehicle-routing problems or
>> supply chain modeling. In particular, I have had experience with both
>> metaheuristic algorithms (e.g., local search or genetic algorithms) and
>> more "traditional" mathematical modeling (e.g., linear programming or
>> constraint programming).
>>
>> I would like to discuss this project in more detail. While it is hard to
>> discuss any kind of exact plan at this stage, I already have two questions
>> concerning this project:
>>
>> (1) I have set up an LLVM dev environment, but I am unsure what to do
>> next. Could you advise me on any simple (and, preferably, relevant) tasks
>> to work on?
>> (2) Could you suggest any learning materials to improve the understanding
>> of "low-level" concepts? (E.g., CPU concepts such as caching and SIMD)
>>
>> Best regards,
>> Konstantin Sidorov
>>
>
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org
> https://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev