[Flang] Generate inline reduction loops for elemental count intrinsics (

#75774)

This adds a ReductionElementalConversion transform to
OptimizedBufferizationPass, taking hlfir::count(hlfir::elemental) and
generating the inline loop to perform the count of true elements. This
lets us generate a single loop instead of ending up as two plus a
temporary.

Any and All should be able to share the same code with a different
function/initial value.

flang/lib/Optimizer/HLFIR/Transforms/OptimizedBufferization.cpp

@@ -659,6 +659,125 @@ mlir::LogicalResult VariableAssignBufferization::matchAndRewrite(
   return mlir::success();
 }
 
+using GenBodyFn =
+    std::function<mlir::Value(fir::FirOpBuilder &, mlir::Location, mlir::Value,
+                              const llvm::SmallVectorImpl<mlir::Value> &)>;
+static mlir::Value generateReductionLoop(fir::FirOpBuilder &builder,
+                                         mlir::Location loc, mlir::Value init,
+                                         mlir::Value shape, GenBodyFn genBody) {
+  auto extents = hlfir::getIndexExtents(loc, builder, shape);
+  mlir::Value reduction = init;
+  mlir::IndexType idxTy = builder.getIndexType();
+  mlir::Value oneIdx = builder.createIntegerConstant(loc, idxTy, 1);
+
+  // Create a reduction loop nest. We use one-based indices so that they can be
+  // passed to the elemental, and reverse the order so that they can be
+  // generated in column-major order for better performance.
+  llvm::SmallVector<mlir::Value> indices(extents.size(), mlir::Value{});
+  for (unsigned i = 0; i < extents.size(); ++i) {
+    auto loop = builder.create<fir::DoLoopOp>(
+        loc, oneIdx, extents[extents.size() - i - 1], oneIdx, false,
+        /*finalCountValue=*/false, reduction);
+    reduction = loop.getRegionIterArgs()[0];
+    indices[extents.size() - i - 1] = loop.getInductionVar();
+    // Set insertion point to the loop body so that the next loop
+    // is inserted inside the current one.
+    builder.setInsertionPointToStart(loop.getBody());
+  }
+
+  // Generate the body
+  reduction = genBody(builder, loc, reduction, indices);
+
+  // Unwind the loop nest.
+  for (unsigned i = 0; i < extents.size(); ++i) {
+    auto result = builder.create<fir::ResultOp>(loc, reduction);
+    auto loop = mlir::cast<fir::DoLoopOp>(result->getParentOp());
+    reduction = loop.getResult(0);
+    // Set insertion point after the loop operation that we have
+    // just processed.
+    builder.setInsertionPointAfter(loop.getOperation());
+  }
+
+  return reduction;
+}
+
+/// Given a reduction operation with an elemental mask, attempt to generate a
+/// do-loop to perform the operation inline.
+///   %e = hlfir.elemental %shape unordered
+///   %r = hlfir.count %e
+/// =>
+///   %r = for.do_loop %arg = 1 to bound(%shape) step 1 iter_args(%arg2 = init)
+///     %i = <inline elemental>
+///     %c = <reduce count> %i
+///     fir.result %c
+template <typename Op>
+class ReductionElementalConversion : public mlir::OpRewritePattern<Op> {
+public:
+  using mlir::OpRewritePattern<Op>::OpRewritePattern;
+
+  mlir::LogicalResult
+  matchAndRewrite(Op op, mlir::PatternRewriter &rewriter) const override {
+    mlir::Location loc = op.getLoc();
+    hlfir::ElementalOp elemental =
+        op.getMask().template getDefiningOp<hlfir::ElementalOp>();
+    if (!elemental || op.getDim())
+      return rewriter.notifyMatchFailure(op, "Did not find valid elemental");
+
+    fir::KindMapping kindMap =
+        fir::getKindMapping(op->template getParentOfType<mlir::ModuleOp>());
+    fir::FirOpBuilder builder{op, kindMap};
+
+    mlir::Value init;
+    GenBodyFn genBodyFn;
+    if constexpr (std::is_same_v<Op, hlfir::CountOp>) {
+      init = builder.createIntegerConstant(loc, op.getType(), 0);
+      genBodyFn = [elemental](fir::FirOpBuilder builder, mlir::Location loc,
+                              mlir::Value reduction,
+                              const llvm::SmallVectorImpl<mlir::Value> &indices)
+          -> mlir::Value {
+        // Inline the elemental and get the condition from it.
+        auto yield = inlineElementalOp(loc, builder, elemental, indices);
+        mlir::Value cond = builder.create<fir::ConvertOp>(
+            loc, builder.getI1Type(), yield.getElementValue());
+        yield->erase();
+
+        // Conditionally add one to the current value
+        mlir::Value one =
+            builder.createIntegerConstant(loc, reduction.getType(), 1);
+        mlir::Value add1 =
+            builder.create<mlir::arith::AddIOp>(loc, reduction, one);
+        return builder.create<mlir::arith::SelectOp>(loc, cond, add1,
+                                                     reduction);
+      };
+    } else {
+      static_assert("Expected Op to be handled");
+      return mlir::failure();
+    }
+
+    mlir::Value res = generateReductionLoop(builder, loc, init,
+                                            elemental.getOperand(0), genBodyFn);
+    if (res.getType() != op.getType())
+      res = builder.create<fir::ConvertOp>(loc, op.getType(), res);
+
+    // Check if the op was the only user of the elemental (apart from a
+    // destroy), and remove it if so.
+    mlir::Operation::user_range elemUsers = elemental->getUsers();
+    hlfir::DestroyOp elemDestroy;
+    if (std::distance(elemUsers.begin(), elemUsers.end()) == 2) {
+      elemDestroy = mlir::dyn_cast<hlfir::DestroyOp>(*elemUsers.begin());
+      if (!elemDestroy)
+        elemDestroy = mlir::dyn_cast<hlfir::DestroyOp>(*++elemUsers.begin());
+    }
+
+    rewriter.replaceOp(op, res);
+    if (elemDestroy) {
+      rewriter.eraseOp(elemDestroy);
+      rewriter.eraseOp(elemental);
+    }
+    return mlir::success();
+  }
+};
+
 class OptimizedBufferizationPass
     : public hlfir::impl::OptimizedBufferizationBase<
           OptimizedBufferizationPass> {
@@ -681,6 +800,7 @@ class OptimizedBufferizationPass
     patterns.insert<ElementalAssignBufferization>(context);
     patterns.insert<BroadcastAssignBufferization>(context);
     patterns.insert<VariableAssignBufferization>(context);
+    patterns.insert<ReductionElementalConversion<hlfir::CountOp>>(context);
 
     if (mlir::failed(mlir::applyPatternsAndFoldGreedily(
             func, std::move(patterns), config))) {