Each vector element is reduced independently, which is a form of
multi-reduction.
The plan is to allow for gradual lowering of multi-reduction that
results in fewer `gpu.shuffle` ops at the end:
1d `vector.multi_reduction` --> 1d `gpu.subgroup_reduce` --> smaller 1d
`gpu.subgroup_reduce` --> packed `gpu.shuffle` over i32
For example we can perform 2 independent f16 reductions with a series of
`gpu.shuffles` over i32, reducing the final number of `gpu.shuffles` by 2x.
This is to avoid confusion when dealing with reduction/combining kinds.
For example, see a recent PR comment:
https://github.com/llvm/llvm-project/pull/75846#discussion_r1430722175.
Previously, they were picked to mostly mirror the names of the llvm
vector reduction intrinsics:
https://llvm.org/docs/LangRef.html#llvm-vector-reduce-fmin-intrinsic. In
isolation, it was not clear if `<maxf>` has `arith.maxnumf` or
`arith.maximumf` semantics. The new reduction kind names map 1:1 to
arith ops, which makes it easier to tell/look up their semantics.
Because both the vector and the gpu dialect depend on the arith dialect,
it's more natural to align names with those in arith than with the
lowering to llvm intrinsics.
Issue: https://github.com/llvm/llvm-project/issues/72354
The motivation for this change is explained in
https://github.com/llvm/llvm-project/issues/72354.
Before this change, we could not tell between signed/unsigned
minimum/maximum and NaN treatment for floating point values.
The mapping of old reduction operations to the new ones is as follows:
* `min` --> `minsi` for ints, `minf` for floats
* `max` --> `maxsi` for ints, `maxf` for floats
New reduction kinds not represented in the old enum: `minui`, `maxui`,
`minimumf`, `maximumf`.
As a next step, I would like to have a common definition of combining
kinds used by the `vector` and `gpu` dialects. Separately, the GPU to
SPIR-V lowering does not yet properly handle zero and NaN values -- the
behavior of floating point min/max group reductions is not specified by
the SPIR-V spec, see https://github.com/llvm/llvm-project/issues/73459.
Issue: https://github.com/llvm/llvm-project/issues/72354
