| //===- 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 = [÷s, &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; |
| } |