1 files changed, 166 insertions, 0 deletions
diff --git a/mlir/lib/Analysis/VectorAnalysis.cpp b/mlir/lib/Analysis/VectorAnalysis.cpp
new file mode 100644
index 00000000000..f6bb9d4f516
--- /dev/null
+++ b/mlir/lib/Analysis/VectorAnalysis.cpp
@@ -0,0 +1,166 @@
+//===- VectorAnalysis.cpp - Analysis for Vectorization --------------------===//
+//
+// Copyright 2019 The MLIR Authors.
+//
+// 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.
+// =============================================================================
+
+#include "mlir/Analysis/VectorAnalysis.h"
+#include "mlir/IR/BuiltinOps.h"
+#include "mlir/IR/Statements.h"
+#include "mlir/Support/Functional.h"
+#include "mlir/Support/STLExtras.h"
+
+///
+/// Implements Analysis functions specific to vectors which support
+/// the vectorization and vectorization materialization passes.
+///
+
+using namespace mlir;
+
+bool mlir::isaVectorTransferRead(const OperationStmt &stmt) {
+  return stmt.getName().getStringRef().str() == kVectorTransferReadOpName;
+}
+
+bool mlir::isaVectorTransferWrite(const OperationStmt &stmt) {
+  return stmt.getName().getStringRef().str() == kVectorTransferWriteOpName;
+}
+
+Optional<SmallVector<unsigned, 4>> mlir::shapeRatio(ArrayRef<int> superShape,
+                                                    ArrayRef<int> subShape) {
+  if (superShape.size() < subShape.size()) {
+    return Optional<SmallVector<unsigned, 4>>();
+  }
+
+  // Starting from the end, compute the integer divisors.
+  // Set the boolean `divides` if integral division is not possible.
+  std::vector<unsigned> result;
+  result.reserve(superShape.size());
+  bool divides = true;
+  auto divide = [&divides, &result](int superSize, int subSize) {
+    assert(superSize > 0 && "superSize must be > 0");
+    assert(subSize > 0 && "subSize must be > 0");
+    divides &= (superSize % subSize == 0);
+    result.push_back(superSize / subSize);
+  };
+  functional::zip(divide,
+                  SmallVector<int, 8>{superShape.rbegin(), superShape.rend()},
+                  SmallVector<int, 8>{subShape.rbegin(), subShape.rend()});
+
+  // If integral division does not occur, return and let the caller decide.
+  if (!divides) {
+    return Optional<SmallVector<unsigned, 4>>();
+  }
+
+  // At this point we computed the multiplicity (in reverse) for the common
+  // size. Fill with the remaining entries from the super-vector shape (still in
+  // reverse).
+  int commonSize = subShape.size();
+  std::copy(superShape.rbegin() + commonSize, superShape.rend(),
+            std::back_inserter(result));
+
+  assert(result.size() == superShape.size() &&
+         "multiplicity must be of the same size as the super-vector rank");
+
+  // Reverse again to get it back in the proper order and return.
+  return SmallVector<unsigned, 4>{result.rbegin(), result.rend()};
+}
+
+Optional<SmallVector<unsigned, 4>> mlir::shapeRatio(VectorType superVectorType,
+                                                    VectorType subVectorType) {
+  assert(superVectorType.getElementType() == subVectorType.getElementType() &&
+         "NYI: vector types must be of the same elemental type");
+  assert(superVectorType.getElementType() ==
+             Type::getF32(superVectorType.getContext()) &&
+         "Only f32 supported for now");
+  return shapeRatio(superVectorType.getShape(), subVectorType.getShape());
+}
+
+/// Matches vector_transfer_read, vector_transfer_write and ops that return a
+/// vector type that is at least a 2-multiple of the sub-vector type size.
+/// This allows leaving other vector types in the function untouched and avoids
+/// interfering with operations on those.
+/// This is a first approximation, it can easily be extended in the future.
+/// TODO(ntv): this could all be much simpler if we added a bit that a vector
+/// type to mark that a vector is a strict super-vector but it is not strictly
+/// needed so let's avoid adding even 1 extra bit in the IR for now.
+bool mlir::matcher::operatesOnStrictSuperVectors(const OperationStmt &opStmt,
+                                                 VectorType subVectorType) {
+  // First, extract the vector type and ditinguish between:
+  //   a. ops that *must* lower a super-vector (i.e. vector_transfer_read,
+  //      vector_transfer_write); and
+  //   b. ops that *may* lower a super-vector (all other ops).
+  // The ops that *may* lower a super-vector only do so if the vector size is
+  // an integer multiple of the HW vector size, with multiplicity 1.
+  // The ops that *must* lower a super-vector are explicitly checked for this
+  // property.
+  /// TODO(ntv): there should be a single function for all ops to do this so we
+  /// do not have to special case. Maybe a trait, or just a method, unclear atm.
+  bool mustDivide = false;
+  VectorType superVectorType;
+  if (isaVectorTransferRead(opStmt)) {
+    superVectorType = opStmt.getResult(0)->getType().cast<VectorType>();
+    mustDivide = true;
+  } else if (isaVectorTransferWrite(opStmt)) {
+    // TODO(ntv): if vector_transfer_write had store-like semantics we could
+    // have written something similar to:
+    //   auto store = storeOp->cast<StoreOp>();
+    //   auto *value = store->getValueToStore();
+    superVectorType = opStmt.getOperand(0)->getType().cast<VectorType>();
+    mustDivide = true;
+  } else if (opStmt.getNumResults() == 0) {
+    assert(opStmt.dyn_cast<ReturnOp>() &&
+           "NYI: assuming only return statements can have 0 results at this "
+           "point");
+    return false;
+  } else if (opStmt.getNumResults() == 1) {
+    if (auto v = opStmt.getResult(0)->getType().dyn_cast<VectorType>()) {
+      superVectorType = v;
+    } else {
+      // Not a vector type.
+      return false;
+    }
+  } else {
+    // Not a vector_transfer and has more than 1 result, fail hard for now to
+    // wake us up when something changes.
+    assert(false && "NYI: statement has more than 1 result");
+    return false;
+  }
+
+  // Get the multiplicity.
+  auto multiplicity = shapeRatio(superVectorType, subVectorType);
+
+  // Sanity check.
+  assert((multiplicity.hasValue() || !mustDivide) &&
+         "NYI: vector_transfer instruction in which super-vector size is not an"
+         " integer multiple of sub-vector size");
+
+  // This catches cases that are not strictly necessary to have multiplicity but
+  // still aren't divisible by the sub-vector shape.
+  // This could be useful information if we wanted to reshape at the level of
+  // the vector type (but we would have to look at the compute and distinguish
+  // between parallel, reduction and possibly other cases.
+  if (!multiplicity.hasValue()) {
+    return false;
+  }
+
+  // A strict super-vector is at least 2 sub-vectors.
+  for (auto m : *multiplicity) {
+    if (m > 1) {
+      return true;
+    }
+  }
+
+  // Not a strict super-vector.
+  return false;
+}