[BACKEND] Fix ProgramPoint passing in AxisInfoAnalysis (#5181)

Fixes #5122.

The `ProgramPoint`
[here](https://github.com/triton-lang/triton/blob/0bd30a2f3192204c5a50d5ffde27ad8493f6c026/lib/Analysis/AxisInfo.cpp#L1087)
is created on the stack. Then its address is
[passed](https://github.com/triton-lang/triton/blob/0bd30a2f3192204c5a50d5ffde27ad8493f6c026/lib/Analysis/AxisInfo.cpp#L1088-L1089)
to the MLIR `SparseAnalysis` code, where it is [added as a
dependency](https://github.com/llvm/llvm-project/blob/33ff9e43b4c5bdc3da31c6b11ad51d35a69bec5f/mlir/lib/Analysis/DataFlow/SparseAnalysis.cpp#L311)
and later
[dereferenced](https://github.com/llvm/llvm-project/blob/33ff9e43b4c5bdc3da31c6b11ad51d35a69bec5f/mlir/lib/Analysis/DataFlow/SparseAnalysis.cpp#L90).
By the time the `ProramPoint` is dereferenced in the
`AbstractSparseForwardDataFlowAnalysis::visit`, the
`AxisInfoAnalysis::visitForOpInductionVar` will have finished and the
`ProgramPoint` stack variable destroyed. This leads to a segfault (which
can be reproed on the base rev with the lit test added in this PR).

The code modified in this PR was originally added in #4927, in
conjunction with updating the `llvm-project` hash to `b5cc222d7429`.
However, as noted in llvm/llvm-project#110344
(the `llvm-project` PR that has made the refactoring prompting the
`AxisInfo.cpp` change in #4927):

> For dense forward data-flow analysis and other analysis (except dense
backward data-flow analysis), the program point corresponding to the
original operation can be obtained by `getProgramPointAfter(op)`

As the `AxisInfoAnalysis` (in Triton) inherits from
`SparseForwardDataFlowAnalysis` (in MLIR), in this PR we follow the
above which resolves the segfault issue (as the `ProgramPoint` is now
stored in the instance-level state of the pass).

P.S. The lit test added in this PR is not exactly minimal. However, I
did my best to minimize it starting from the 400-line repro TTGIR in
#5122. Further minimization does not seem to expose the segfault.

Author: aakhundov

lib/Analysis/AxisInfo.cpp

@@ -1084,9 +1084,9 @@ LogicalResult AxisInfoAnalysis::visitOperation(
 
 void AxisInfoAnalysis::visitForOpInductionVar(
     scf::ForOp op, ArrayRef<dataflow::Lattice<AxisInfo> *> argLattices) {
-  ProgramPoint programPoint(op);
-  auto lb = getLatticeElementFor(&programPoint, op.getLowerBound())->getValue();
-  auto step = getLatticeElementFor(&programPoint, op.getStep())->getValue();
+  ProgramPoint *programPoint = getProgramPointAfter(op);
+  auto lb = getLatticeElementFor(programPoint, op.getLowerBound())->getValue();
+  auto step = getLatticeElementFor(programPoint, op.getStep())->getValue();
 
   AxisInfo::DimVectorT knownContiguity(1, 1);
   AxisInfo::DimVectorT knownDivisibility(1, 1);

test/TritonGPU/coalesce.mlir

@@ -131,3 +131,32 @@ module attributes {"triton_gpu.num-warps" = 4 : i32, "triton_gpu.threads-per-war
     tt.return
   }
 }
+
+// -----
+
+// COM: Reproducer for issue #5122
+// CHECK-LABEL: @test_5122
+module {
+  tt.func public @test_5122(%arg0: i32) attributes {noinline = false} {
+    %c1_i32 = arith.constant 1 : i32
+    %0 = arith.cmpi sgt, %arg0, %c1_i32 : i32
+    scf.if %0 {
+      %1 = scf.if %0 -> (i32) {
+        scf.yield %c1_i32 : i32
+      } else {
+        scf.yield %c1_i32 : i32
+      }
+      %2 = arith.cmpi sgt, %1, %c1_i32 : i32
+      %3 = scf.if %2 -> (i32) {
+        scf.yield %c1_i32 : i32
+      } else {
+        scf.yield %c1_i32 : i32
+      }
+      %4 = scf.for %arg1 = %1 to %1 step %c1_i32 iter_args(%arg2 = %3) -> (i32) : i32 {
+        %5 = arith.addi %arg2, %c1_i32 : i32
+        scf.yield %5 : i32
+      }
+    }
+    tt.return
+  }
+}