================
@@ -53,6 +53,79 @@ that:
* It has been tested in a very limited way so far.
* It has been tested mostly on simple synthetic inputs.
+### Loop nest detection
+
+On the `FIR` dialect level, the following loop:
+```fortran
+ do concurrent(i=1:n, j=1:m, k=1:o)
+ a(i,j,k) = i + j + k
+ end do
+```
+is modelled as a nest of `fir.do_loop` ops such that an outer loop's region
+contains **only** the following:
+ 1. The operations needed to assign/update the outer loop's induction
variable.
+ 1. The inner loop itself.
+
+So the MLIR structure for the above example looks similar to the following:
+```
+ fir.do_loop %i_idx = %34 to %36 step %c1 unordered {
+ %i_idx_2 = fir.convert %i_idx : (index) -> i32
+ fir.store %i_idx_2 to %i_iv#1 : !fir.ref<i32>
+
+ fir.do_loop %j_idx = %37 to %39 step %c1_3 unordered {
+ %j_idx_2 = fir.convert %j_idx : (index) -> i32
+ fir.store %j_idx_2 to %j_iv#1 : !fir.ref<i32>
+
+ fir.do_loop %k_idx = %40 to %42 step %c1_5 unordered {
+ %k_idx_2 = fir.convert %k_idx : (index) -> i32
+ fir.store %k_idx_2 to %k_iv#1 : !fir.ref<i32>
+
+ ... loop nest body goes here ...
+ }
+ }
+ }
+```
+This applies to multi-range loops in general; they are represented in the IR as
+a nest of `fir.do_loop` ops with the above nesting structure.
+
+Therefore, the pass detects such "perfectly" nested loop ops to identify
multi-range
+loops and map them as "collapsed" loops in OpenMP.
+
+#### Further info regarding loop nest detection
+
+Loop nest detection is currently limited to the scenario described in the
previous
+section. However, this is quite limited and can be extended in the future to
cover
+more cases. For example, for the following loop nest, even though, both loops
are
+perfectly nested; at the moment, only the outer loop is parallelized:
----------------
skatrak wrote:
Nit: I think it's easier to follow like this, but feel free to disagree.
```suggestion
more cases. At the moment, for the following loop nest, even though both loops
are
perfectly nested, only the outer loop is parallelized:
```
https://github.com/llvm/llvm-project/pull/127595
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