[Mlir-commits] [mlir] [OpenMP][MLIR] Add omp.distribute op to the OMP dialect (PR #67720)

[Kiran Chandramohan]

kiranchandramohan wrote:

> > In the lowering in #67798, an `omp.wsloop` is created for `!$omp distribute`. Is this always correct to do as per the standard? Is it based on existing Clang lowering?
> 
> I think a omp.wsloop is created from parallel do, Afaik 'distribute' is associated with teams, so that each team takes a chunk of the iterations instead of all teams taking all (duplicating) iterations.

The example lowering created a `omp.wsloop` operation for an `omp.distribute` eventhough there was no `parallel do`. Hence the question.
https://github.com/llvm/llvm-project/pull/67798/files#diff-0652f88238afa05fb262dcebab875780ab553b3914ba7239512c45986198240d


> > > > Could you share your plan before we proceed? The proposal of this patch of a distribute operation that (possibly) nests a loop seems to be different from both the existing worksharing-loop design (that includes the loop) and the canonical-loop proposal under design where the distribute will accept a CLI value that represents a loop.
> > > 
> > > 
> > > The plan is to have some representation of 'distribute' that does not rely on meta-values (CLI) for now, since there are still a lot of unanswered questions. The version of the omp.distribute op in this patch basically works as a wrapper op that modified how the contained loop(s) execute. It does rely on there being a contained loop or (several if we want to consider collapse).
> > 
> > 
> > Will the contained loop be an `omp.wsloop` always?
> 
> No, it could be some other kind of loop.

`fir.do_loop`, `scf.for` are converted to control-flow by the time they are in the OpenMP + LLVM dialect stage. So it has to be something encoded with OpenMP, like `omp.canonical_loop`.



> The CLIs get associated with a specific canonical loop, or they are created by a top-level loop transformation op.

In the other approach, the canonical loop was always created by an omp.canonical_loop declaration or by a loop transformation op. This way it was always easy to find the canonical loop given a CLI. Now we will have to reach the `omp.cli` operation and look at its use.

Associating CLIs at the top-level will not always be possible particularly if there are other operations, like a parallel operation. For the following example,  

```
!$omp unroll
do i=1,l
  !$omp parallel
  do j=1,m
    !$omp unroll
    do k=1,n
    end do
  end do
end o
```

Should generate something like the following. 

```
%cli1 = omp.cli()
canonical_loop(%i, 1, %l, %cli1) {
   omp.parallel {
     fir.do_loop (%j,1,%m) {
       %cli2 = omp.cli()
       canonical_loop(%j, 1, %m, %cli2) {
       }
       %cli4 = omp.unroll(%cli2)
     }
   }
}
```
%cli4 = omp.unroll(%cli1)
```

https://github.com/llvm/llvm-project/pull/67720