[Mlir-commits] [mlir] [mlir][affine] Add affine-super-vectorize docs (PR #204603)

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<!--LLVM PR SUMMARY COMMENT-->

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Author: Federico Bruzzone (FedericoBruzzone)

<details>
<summary>Changes</summary>

This pull request is simply to add documentation to the `affine-super-vectorizer`.

Also, I'm open to adding more information if anyone already has any specific aspects that should be added :D

---
Full diff: https://github.com/llvm/llvm-project/pull/204603.diff


1 Files Affected:

- (modified) mlir/include/mlir/Dialect/Affine/Transforms/Passes.td (+12) 


``````````diff
diff --git a/mlir/include/mlir/Dialect/Affine/Transforms/Passes.td b/mlir/include/mlir/Dialect/Affine/Transforms/Passes.td
index 7cecbcac5b932..11085a865de6f 100644
--- a/mlir/include/mlir/Dialect/Affine/Transforms/Passes.td
+++ b/mlir/include/mlir/Dialect/Affine/Transforms/Passes.td
@@ -345,6 +345,18 @@ def AffineScalarReplacement : Pass<"affine-scalrep", "func::FuncOp"> {
 
 def AffineVectorize : Pass<"affine-super-vectorize", "func::FuncOp"> {
   let summary = "Vectorize to a target independent n-D vector abstraction";
+  let description = [{
+    Transforms affine loops into vector operations (transfer_read/write,
+    load/store, gather/scatter, etc.) using a virtual target-independent
+    n-D vector size. The resulting IR uses vector ops instead of scalar
+    affine loads/stores.
+
+    When accesses are provably within bounds (all dimensions statically known
+    and access patterns fit the memref layout), the generated vector operations
+    carry `in_bounds = [true, ...]` attributes asserting that masking is not
+    needed. These properties enable downstream optimizations in vectorization-aware
+    lowering passes (e.g., LLVM code generation).
+  }];
   let dependentDialects = ["vector::VectorDialect"];
   let options = [
     ListOption<"vectorSizes", "virtual-vector-size", "int64_t",

``````````

</details>


https://github.com/llvm/llvm-project/pull/204603