MLIR current only supports a custom inlining interface per dialect, so
we cannot change the inlining decision of `func.func`.
https://discourse.llvm.org/t/avoid-inlining-some-functions-using-the-func-dialect/69830/3
Could revert it back once they've designed a better inliner interface.
Inlining attributes will be implemented in the next PR since this PR is
already huge.
- Rewrite the AxisInfo analysis to handle each op case by case.
- Add bit shift, min max, div/rem, and select ops to AxisInfo.
- Rematerialize across load/store ops in the following two cases:
- A size 1 tensor is considered not expensive since all threads will
load the same
- the targeEncoding may expose more vectorization opportunities (more
elements per thread on the first dim)
**_res2next_** benchmark GPU Kernel time comparison on A100.
- Average kernel sum. Triton 16838630ns vs Triton-MLIR 17105166ns.
**1.016x slowdown**.
- Total kernel sum. Triton 6511735460ns vs Triton-MLIR 6512370620ns.
