Lift the restriction in liveness-traversal.h that supported max 65535 locals in a function. (#4567)

* Lift the restriction in liveness-traversal.h that supported max 65535 locals in a function.

* Lint

* Fix typo

* Fix static

* Lint

* Lint

* Lint

* Add needed canRun function

* lint

* Use either a sparse or a dense matrix for tracking liveness copies, depending on the locals count.

* Lint

* Fix lint

* Lint

* Implement sparse_square_matrix class and use that as a backing.

* Lint

* Lint

* Lint #includes

* Lint

* Lint includes

* Remove unnecessary code

* Fix canonical accesses to copies matrix

* Lint

* Add missing variable update

* Remove canRun() function

* Address review

* Update expected test results

* Update test name

* Add asserts to sparse_square_matrix set and get functions that they are not out of bound.

* Lint includes

* Update test expectation

* Use .clear() + .resize() to reset totalCopies vector

1 files changed, 76 insertions, 0 deletions

diff --git a/src/support/sparse_square_matrix.h b/src/support/sparse_square_matrix.h
new file mode 100644
index 000000000..03ebcb5c6
--- /dev/null
+++ b/src/support/sparse_square_matrix.h
@@ -0,0 +1,76 @@
+/*
+ * Copyright 2022 WebAssembly Community Group participants
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+// A helper type for potentially sparse N*N matrix container.
+
+#pragma once
+
+#include <assert.h>
+#include <stdint.h>
+#include <unordered_map>
+#include <vector>
+
+template<typename Ty> class sparse_square_matrix {
+  std::vector<Ty> denseStorage;
+  std::unordered_map<uint64_t, Ty> sparseStorage;
+  uint32_t N;
+
+public:
+  sparse_square_matrix() : N(0) {}
+
+  explicit sparse_square_matrix(int N) : N(N) {
+    if (N < DenseLimit) {
+      denseStorage.resize(N * N);
+    }
+  }
+
+  static const size_t DenseLimit = 8192;
+
+  uint32_t width() const { return N; }
+
+  bool usingDenseStorage() const { return !denseStorage.empty(); }
+
+  void set(uint32_t i, uint32_t j, const Ty& value) {
+    assert(i < N);
+    assert(j < N);
+    if (usingDenseStorage()) {
+      denseStorage[i * N + j] = value;
+    } else {
+      sparseStorage[i * N + j] = value;
+    }
+  }
+
+  const Ty get(uint32_t i, uint32_t j) const {
+    assert(i < N);
+    assert(j < N);
+    if (usingDenseStorage()) {
+      return denseStorage[i * N + j];
+    }
+    auto iter = sparseStorage.find(i * N + j);
+    return iter == sparseStorage.end() ? Ty() : iter->second;
+  }
+
+  // Resizes the matrix to a new n*n size, and clears all entries
+  // to the default-initialized value.
+  void recreate(uint32_t n) {
+    N = n;
+    denseStorage.clear();
+    sparseStorage.clear();
+    if (N < DenseLimit) {
+      denseStorage.resize(N * N);
+    }
+  }
+};