//===- MemoryAllocation.cpp -----------------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//

#include "PassDetail.h"
#include "flang/Optimizer/Dialect/FIRDialect.h"
#include "flang/Optimizer/Dialect/FIROps.h"
#include "flang/Optimizer/Dialect/FIRType.h"
#include "flang/Optimizer/Transforms/Passes.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/IR/Diagnostics.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/DialectConversion.h"
#include "mlir/Transforms/Passes.h"
#include "llvm/ADT/TypeSwitch.h"

#define DEBUG_TYPE "flang-memory-allocation-opt"

// Number of elements in an array does not determine where it is allocated.
static constexpr std::size_t unlimitedArraySize = ~static_cast<std::size_t>(0);

namespace {
struct MemoryAllocationOptions {
  // Always move dynamic array allocations to the heap. This may result in more
  // heap fragmentation, so may impact performance negatively.
  bool dynamicArrayOnHeap = false;

  // Number of elements in array threshold for moving to heap. In environments
  // with limited stack size, moving large arrays to the heap can avoid running
  // out of stack space.
  std::size_t maxStackArraySize = unlimitedArraySize;
};

class ReturnAnalysis {
public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(ReturnAnalysis)

  ReturnAnalysis(mlir::Operation *op) {
    if (auto func = mlir::dyn_cast<mlir::func::FuncOp>(op))
      for (mlir::Block &block : func)
        for (mlir::Operation &i : block)
          if (mlir::isa<mlir::func::ReturnOp>(i)) {
            returnMap[op].push_back(&i);
            break;
          }
  }

  llvm::SmallVector<mlir::Operation *> getReturns(mlir::Operation *func) const {
    auto iter = returnMap.find(func);
    if (iter != returnMap.end())
      return iter->second;
    return {};
  }

private:
  llvm::DenseMap<mlir::Operation *, llvm::SmallVector<mlir::Operation *>>
      returnMap;
};
} // namespace

/// Return `true` if this allocation is to remain on the stack (`fir.alloca`).
/// Otherwise the allocation should be moved to the heap (`fir.allocmem`).
static inline bool keepStackAllocation(fir::AllocaOp alloca, mlir::Block *entry,
                                       const MemoryAllocationOptions &options) {
  // Limitation: only arrays allocated on the stack in the entry block are
  // considered for now.
  // TODO: Generalize the algorithm and placement of the freemem nodes.
  if (alloca->getBlock() != entry)
    return true;
  if (auto seqTy = alloca.getInType().dyn_cast<fir::SequenceType>()) {
    if (fir::hasDynamicSize(seqTy)) {
      // Move all arrays with runtime determined size to the heap.
      if (options.dynamicArrayOnHeap)
        return false;
    } else {
      std::int64_t numberOfElements = 1;
      for (std::int64_t i : seqTy.getShape()) {
        numberOfElements *= i;
        // If the count is suspicious, then don't change anything here.
        if (numberOfElements <= 0)
          return true;
      }
      // If the number of elements exceeds the threshold, move the allocation to
      // the heap.
      if (static_cast<std::size_t>(numberOfElements) >
          options.maxStackArraySize) {
        LLVM_DEBUG(llvm::dbgs()
                   << "memory allocation opt: found " << alloca << '\n');
        return false;
      }
    }
  }
  return true;
}

namespace {
class AllocaOpConversion : public mlir::OpRewritePattern<fir::AllocaOp> {
public:
  using OpRewritePattern::OpRewritePattern;

  AllocaOpConversion(mlir::MLIRContext *ctx,
                     llvm::ArrayRef<mlir::Operation *> rets)
      : OpRewritePattern(ctx), returnOps(rets) {}

  mlir::LogicalResult
  matchAndRewrite(fir::AllocaOp alloca,
                  mlir::PatternRewriter &rewriter) const override {
    auto loc = alloca.getLoc();
    mlir::Type varTy = alloca.getInType();
    auto unpackName =
        [](llvm::Optional<llvm::StringRef> opt) -> llvm::StringRef {
      if (opt)
        return *opt;
      return {};
    };
    auto uniqName = unpackName(alloca.getUniqName());
    auto bindcName = unpackName(alloca.getBindcName());
    auto heap = rewriter.create<fir::AllocMemOp>(
        loc, varTy, uniqName, bindcName, alloca.getTypeparams(),
        alloca.getShape());
    auto insPt = rewriter.saveInsertionPoint();
    for (mlir::Operation *retOp : returnOps) {
      rewriter.setInsertionPoint(retOp);
      [[maybe_unused]] auto free = rewriter.create<fir::FreeMemOp>(loc, heap);
      LLVM_DEBUG(llvm::dbgs() << "memory allocation opt: add free " << free
                              << " for " << heap << '\n');
    }
    rewriter.restoreInsertionPoint(insPt);
    rewriter.replaceOpWithNewOp<fir::ConvertOp>(
        alloca, fir::ReferenceType::get(varTy), heap);
    LLVM_DEBUG(llvm::dbgs() << "memory allocation opt: replaced " << alloca
                            << " with " << heap << '\n');
    return mlir::success();
  }

private:
  llvm::ArrayRef<mlir::Operation *> returnOps;
};

/// This pass can reclassify memory allocations (fir.alloca, fir.allocmem) based
/// on heuristics and settings. The intention is to allow better performance and
/// workarounds for conditions such as environments with limited stack space.
///
/// Currently, implements two conversions from stack to heap allocation.
///   1. If a stack allocation is an array larger than some threshold value
///      make it a heap allocation.
///   2. If a stack allocation is an array with a runtime evaluated size make
///      it a heap allocation.
class MemoryAllocationOpt
    : public fir::MemoryAllocationOptBase<MemoryAllocationOpt> {
public:
  MemoryAllocationOpt() {
    // Set options with default values. (See Passes.td.) Note that the
    // command-line options, e.g. dynamicArrayOnHeap,  are not set yet.
    options = {dynamicArrayOnHeap, maxStackArraySize};
  }

  MemoryAllocationOpt(bool dynOnHeap, std::size_t maxStackSize) {
    // Set options with default values. (See Passes.td.)
    options = {dynOnHeap, maxStackSize};
  }

  /// Override `options` if command-line options have been set.
  inline void useCommandLineOptions() {
    if (dynamicArrayOnHeap)
      options.dynamicArrayOnHeap = dynamicArrayOnHeap;
    if (maxStackArraySize != unlimitedArraySize)
      options.maxStackArraySize = maxStackArraySize;
  }

  void runOnOperation() override {
    auto *context = &getContext();
    auto func = getOperation();
    mlir::RewritePatternSet patterns(context);
    mlir::ConversionTarget target(*context);

    useCommandLineOptions();
    LLVM_DEBUG(llvm::dbgs()
               << "dynamic arrays on heap: " << options.dynamicArrayOnHeap
               << "\nmaximum number of elements of array on stack: "
               << options.maxStackArraySize << '\n');

    // If func is a declaration, skip it.
    if (func.empty())
      return;

    const auto &analysis = getAnalysis<ReturnAnalysis>();

    target.addLegalDialect<fir::FIROpsDialect, mlir::arith::ArithmeticDialect,
                           mlir::func::FuncDialect>();
    target.addDynamicallyLegalOp<fir::AllocaOp>([&](fir::AllocaOp alloca) {
      return keepStackAllocation(alloca, &func.front(), options);
    });

    patterns.insert<AllocaOpConversion>(context, analysis.getReturns(func));
    if (mlir::failed(
            mlir::applyPartialConversion(func, target, std::move(patterns)))) {
      mlir::emitError(func.getLoc(),
                      "error in memory allocation optimization\n");
      signalPassFailure();
    }
  }

private:
  MemoryAllocationOptions options;
};
} // namespace

std::unique_ptr<mlir::Pass> fir::createMemoryAllocationPass() {
  return std::make_unique<MemoryAllocationOpt>();
}

std::unique_ptr<mlir::Pass>
fir::createMemoryAllocationPass(bool dynOnHeap, std::size_t maxStackSize) {
  return std::make_unique<MemoryAllocationOpt>(dynOnHeap, maxStackSize);
}
