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llvm-mirror/include/llvm/Analysis/BlockFrequencyInfoImpl.h
Duncan P. N. Exon Smith 99868899c1 BFI: Update ScaledNumber header docs
llvm-svn: 211556
2014-06-23 23:49:31 +00:00

1677 lines
60 KiB
C++

//==- BlockFrequencyInfoImpl.h - Block Frequency Implementation -*- C++ -*-===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// Shared implementation of BlockFrequency for IR and Machine Instructions.
// See the documentation below for BlockFrequencyInfoImpl for details.
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_ANALYSIS_BLOCKFREQUENCYINFOIMPL_H
#define LLVM_ANALYSIS_BLOCKFREQUENCYINFOIMPL_H
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/PostOrderIterator.h"
#include "llvm/ADT/iterator_range.h"
#include "llvm/IR/BasicBlock.h"
#include "llvm/Support/BlockFrequency.h"
#include "llvm/Support/BranchProbability.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/ScaledNumber.h"
#include "llvm/Support/raw_ostream.h"
#include <deque>
#include <list>
#include <string>
#include <vector>
#define DEBUG_TYPE "block-freq"
//===----------------------------------------------------------------------===//
//
// ScaledNumber definition.
//
// TODO: Move to include/llvm/Support/ScaledNumber.h
//
//===----------------------------------------------------------------------===//
namespace llvm {
class ScaledNumberBase {
public:
static const int32_t MaxExponent = 16383;
static const int32_t MinExponent = -16382;
static const int DefaultPrecision = 10;
static void dump(uint64_t D, int16_t E, int Width);
static raw_ostream &print(raw_ostream &OS, uint64_t D, int16_t E, int Width,
unsigned Precision);
static std::string toString(uint64_t D, int16_t E, int Width,
unsigned Precision);
static int countLeadingZeros32(uint32_t N) { return countLeadingZeros(N); }
static int countLeadingZeros64(uint64_t N) { return countLeadingZeros(N); }
static uint64_t getHalf(uint64_t N) { return (N >> 1) + (N & 1); }
static std::pair<uint64_t, bool> splitSigned(int64_t N) {
if (N >= 0)
return std::make_pair(N, false);
uint64_t Unsigned = N == INT64_MIN ? UINT64_C(1) << 63 : uint64_t(-N);
return std::make_pair(Unsigned, true);
}
static int64_t joinSigned(uint64_t U, bool IsNeg) {
if (U > uint64_t(INT64_MAX))
return IsNeg ? INT64_MIN : INT64_MAX;
return IsNeg ? -int64_t(U) : int64_t(U);
}
};
/// \brief Simple representation of a scaled number.
///
/// ScaledNumber is a number represented by digits and a scale. It uses simple
/// saturation arithmetic and every operation is well-defined for every value.
/// It's somewhat similar in behaviour to a soft-float, but is *not* a
/// replacement for one. If you're doing numerics, look at \a APFloat instead.
/// Nevertheless, we've found these semantics useful for modelling certain cost
/// metrics.
///
/// The number is split into a signed scale and unsigned digits. The number
/// represented is \c getDigits()*2^getExponent(). In this way, the digits are
/// much like the mantissa in the x87 long double, but there is no canonical
/// form so the same number can be represented by many bit representations.
///
/// ScaledNumber is templated on the underlying integer type for digits, which
/// is expected to be unsigned.
///
/// Unlike APFloat, ScaledNumber does not model architecture floating point
/// behaviour -- while this might make it a little faster and easier to reason
/// about, it certainly makes it more dangerous for general numerics.
///
/// ScaledNumber is totally ordered. However, there is no canonical form, so
/// there are multiple representations of most scalars. E.g.:
///
/// ScaledNumber(8u, 0) == ScaledNumber(4u, 1)
/// ScaledNumber(4u, 1) == ScaledNumber(2u, 2)
/// ScaledNumber(2u, 2) == ScaledNumber(1u, 3)
///
/// ScaledNumber implements most arithmetic operations. Precision is kept
/// where possible. Uses simple saturation arithmetic, so that operations
/// saturate to 0.0 or getLargest() rather than under or overflowing. It has
/// some extra arithmetic for unit inversion. 0.0/0.0 is defined to be 0.0.
/// Any other division by 0.0 is defined to be getLargest().
///
/// As a convenience for modifying the exponent, left and right shifting are
/// both implemented, and both interpret negative shifts as positive shifts in
/// the opposite direction.
///
/// Exponents are limited to the range accepted by x87 long double. This makes
/// it trivial to add functionality to convert to APFloat (this is already
/// relied on for the implementation of printing).
///
/// Possible (and conflicting) future directions:
///
/// 1. Turn this into a wrapper around \a APFloat.
/// 2. Share the algorithm implementations with \a APFloat.
/// 3. Allow \a ScaledNumber to represent a signed number.
template <class DigitsT> class ScaledNumber : ScaledNumberBase {
public:
static_assert(!std::numeric_limits<DigitsT>::is_signed,
"only unsigned floats supported");
typedef DigitsT DigitsType;
private:
typedef std::numeric_limits<DigitsType> DigitsLimits;
static const int Width = sizeof(DigitsType) * 8;
static_assert(Width <= 64, "invalid integer width for digits");
private:
DigitsType Digits;
int16_t Exponent;
public:
ScaledNumber() : Digits(0), Exponent(0) {}
ScaledNumber(DigitsType Digits, int16_t Exponent)
: Digits(Digits), Exponent(Exponent) {}
private:
ScaledNumber(const std::pair<uint64_t, int16_t> &X)
: Digits(X.first), Exponent(X.second) {}
public:
static ScaledNumber getZero() { return ScaledNumber(0, 0); }
static ScaledNumber getOne() { return ScaledNumber(1, 0); }
static ScaledNumber getLargest() {
return ScaledNumber(DigitsLimits::max(), MaxExponent);
}
static ScaledNumber getFloat(uint64_t N) { return adjustToWidth(N, 0); }
static ScaledNumber getInverseFloat(uint64_t N) {
return getFloat(N).invert();
}
static ScaledNumber getFraction(DigitsType N, DigitsType D) {
return getQuotient(N, D);
}
int16_t getExponent() const { return Exponent; }
DigitsType getDigits() const { return Digits; }
/// \brief Convert to the given integer type.
///
/// Convert to \c IntT using simple saturating arithmetic, truncating if
/// necessary.
template <class IntT> IntT toInt() const;
bool isZero() const { return !Digits; }
bool isLargest() const { return *this == getLargest(); }
bool isOne() const {
if (Exponent > 0 || Exponent <= -Width)
return false;
return Digits == DigitsType(1) << -Exponent;
}
/// \brief The log base 2, rounded.
///
/// Get the lg of the scalar. lg 0 is defined to be INT32_MIN.
int32_t lg() const { return ScaledNumbers::getLg(Digits, Exponent); }
/// \brief The log base 2, rounded towards INT32_MIN.
///
/// Get the lg floor. lg 0 is defined to be INT32_MIN.
int32_t lgFloor() const {
return ScaledNumbers::getLgFloor(Digits, Exponent);
}
/// \brief The log base 2, rounded towards INT32_MAX.
///
/// Get the lg ceiling. lg 0 is defined to be INT32_MIN.
int32_t lgCeiling() const {
return ScaledNumbers::getLgCeiling(Digits, Exponent);
}
bool operator==(const ScaledNumber &X) const { return compare(X) == 0; }
bool operator<(const ScaledNumber &X) const { return compare(X) < 0; }
bool operator!=(const ScaledNumber &X) const { return compare(X) != 0; }
bool operator>(const ScaledNumber &X) const { return compare(X) > 0; }
bool operator<=(const ScaledNumber &X) const { return compare(X) <= 0; }
bool operator>=(const ScaledNumber &X) const { return compare(X) >= 0; }
bool operator!() const { return isZero(); }
/// \brief Convert to a decimal representation in a string.
///
/// Convert to a string. Uses scientific notation for very large/small
/// numbers. Scientific notation is used roughly for numbers outside of the
/// range 2^-64 through 2^64.
///
/// \c Precision indicates the number of decimal digits of precision to use;
/// 0 requests the maximum available.
///
/// As a special case to make debugging easier, if the number is small enough
/// to convert without scientific notation and has more than \c Precision
/// digits before the decimal place, it's printed accurately to the first
/// digit past zero. E.g., assuming 10 digits of precision:
///
/// 98765432198.7654... => 98765432198.8
/// 8765432198.7654... => 8765432198.8
/// 765432198.7654... => 765432198.8
/// 65432198.7654... => 65432198.77
/// 5432198.7654... => 5432198.765
std::string toString(unsigned Precision = DefaultPrecision) {
return ScaledNumberBase::toString(Digits, Exponent, Width, Precision);
}
/// \brief Print a decimal representation.
///
/// Print a string. See toString for documentation.
raw_ostream &print(raw_ostream &OS,
unsigned Precision = DefaultPrecision) const {
return ScaledNumberBase::print(OS, Digits, Exponent, Width, Precision);
}
void dump() const { return ScaledNumberBase::dump(Digits, Exponent, Width); }
ScaledNumber &operator+=(const ScaledNumber &X) {
std::tie(Digits, Exponent) =
ScaledNumbers::getSum(Digits, Exponent, X.Digits, X.Exponent);
// Check for exponent past MaxExponent.
if (Exponent > MaxExponent)
*this = getLargest();
return *this;
}
ScaledNumber &operator-=(const ScaledNumber &X) {
std::tie(Digits, Exponent) =
ScaledNumbers::getDifference(Digits, Exponent, X.Digits, X.Exponent);
return *this;
}
ScaledNumber &operator*=(const ScaledNumber &X);
ScaledNumber &operator/=(const ScaledNumber &X);
ScaledNumber &operator<<=(int16_t Shift) {
shiftLeft(Shift);
return *this;
}
ScaledNumber &operator>>=(int16_t Shift) {
shiftRight(Shift);
return *this;
}
private:
void shiftLeft(int32_t Shift);
void shiftRight(int32_t Shift);
/// \brief Adjust two floats to have matching exponents.
///
/// Adjust \c this and \c X to have matching exponents. Returns the new \c X
/// by value. Does nothing if \a isZero() for either.
///
/// The value that compares smaller will lose precision, and possibly become
/// \a isZero().
ScaledNumber matchExponents(ScaledNumber X) {
ScaledNumbers::matchScales(Digits, Exponent, X.Digits, X.Exponent);
return X;
}
public:
/// \brief Scale a large number accurately.
///
/// Scale N (multiply it by this). Uses full precision multiplication, even
/// if Width is smaller than 64, so information is not lost.
uint64_t scale(uint64_t N) const;
uint64_t scaleByInverse(uint64_t N) const {
// TODO: implement directly, rather than relying on inverse. Inverse is
// expensive.
return inverse().scale(N);
}
int64_t scale(int64_t N) const {
std::pair<uint64_t, bool> Unsigned = splitSigned(N);
return joinSigned(scale(Unsigned.first), Unsigned.second);
}
int64_t scaleByInverse(int64_t N) const {
std::pair<uint64_t, bool> Unsigned = splitSigned(N);
return joinSigned(scaleByInverse(Unsigned.first), Unsigned.second);
}
int compare(const ScaledNumber &X) const {
return ScaledNumbers::compare(Digits, Exponent, X.Digits, X.Exponent);
}
int compareTo(uint64_t N) const {
ScaledNumber Float = getFloat(N);
int Compare = compare(Float);
if (Width == 64 || Compare != 0)
return Compare;
// Check for precision loss. We know *this == RoundTrip.
uint64_t RoundTrip = Float.template toInt<uint64_t>();
return N == RoundTrip ? 0 : RoundTrip < N ? -1 : 1;
}
int compareTo(int64_t N) const { return N < 0 ? 1 : compareTo(uint64_t(N)); }
ScaledNumber &invert() { return *this = ScaledNumber::getFloat(1) / *this; }
ScaledNumber inverse() const { return ScaledNumber(*this).invert(); }
private:
static ScaledNumber getProduct(DigitsType LHS, DigitsType RHS) {
return ScaledNumbers::getProduct(LHS, RHS);
}
static ScaledNumber getQuotient(DigitsType Dividend, DigitsType Divisor) {
return ScaledNumbers::getQuotient(Dividend, Divisor);
}
static int countLeadingZerosWidth(DigitsType Digits) {
if (Width == 64)
return countLeadingZeros64(Digits);
if (Width == 32)
return countLeadingZeros32(Digits);
return countLeadingZeros32(Digits) + Width - 32;
}
/// \brief Adjust a number to width, rounding up if necessary.
///
/// Should only be called for \c Shift close to zero.
///
/// \pre Shift >= MinExponent && Shift + 64 <= MaxExponent.
static ScaledNumber adjustToWidth(uint64_t N, int32_t Shift) {
assert(Shift >= MinExponent && "Shift should be close to 0");
assert(Shift <= MaxExponent - 64 && "Shift should be close to 0");
auto Adjusted = ScaledNumbers::getAdjusted<DigitsT>(N, Shift);
return Adjusted;
}
static ScaledNumber getRounded(ScaledNumber P, bool Round) {
// Saturate.
if (P.isLargest())
return P;
return ScaledNumbers::getRounded(P.Digits, P.Exponent, Round);
}
};
#define SCALED_NUMBER_BOP(op, base) \
template <class DigitsT> \
ScaledNumber<DigitsT> operator op(const ScaledNumber<DigitsT> &L, \
const ScaledNumber<DigitsT> &R) { \
return ScaledNumber<DigitsT>(L) base R; \
}
SCALED_NUMBER_BOP(+, += )
SCALED_NUMBER_BOP(-, -= )
SCALED_NUMBER_BOP(*, *= )
SCALED_NUMBER_BOP(/, /= )
SCALED_NUMBER_BOP(<<, <<= )
SCALED_NUMBER_BOP(>>, >>= )
#undef SCALED_NUMBER_BOP
template <class DigitsT>
raw_ostream &operator<<(raw_ostream &OS, const ScaledNumber<DigitsT> &X) {
return X.print(OS, 10);
}
#define SCALED_NUMBER_COMPARE_TO_TYPE(op, T1, T2) \
template <class DigitsT> \
bool operator op(const ScaledNumber<DigitsT> &L, T1 R) { \
return L.compareTo(T2(R)) op 0; \
} \
template <class DigitsT> \
bool operator op(T1 L, const ScaledNumber<DigitsT> &R) { \
return 0 op R.compareTo(T2(L)); \
}
#define SCALED_NUMBER_COMPARE_TO(op) \
SCALED_NUMBER_COMPARE_TO_TYPE(op, uint64_t, uint64_t) \
SCALED_NUMBER_COMPARE_TO_TYPE(op, uint32_t, uint64_t) \
SCALED_NUMBER_COMPARE_TO_TYPE(op, int64_t, int64_t) \
SCALED_NUMBER_COMPARE_TO_TYPE(op, int32_t, int64_t)
SCALED_NUMBER_COMPARE_TO(< )
SCALED_NUMBER_COMPARE_TO(> )
SCALED_NUMBER_COMPARE_TO(== )
SCALED_NUMBER_COMPARE_TO(!= )
SCALED_NUMBER_COMPARE_TO(<= )
SCALED_NUMBER_COMPARE_TO(>= )
#undef SCALED_NUMBER_COMPARE_TO
#undef SCALED_NUMBER_COMPARE_TO_TYPE
template <class DigitsT>
uint64_t ScaledNumber<DigitsT>::scale(uint64_t N) const {
if (Width == 64 || N <= DigitsLimits::max())
return (getFloat(N) * *this).template toInt<uint64_t>();
// Defer to the 64-bit version.
return ScaledNumber<uint64_t>(Digits, Exponent).scale(N);
}
template <class DigitsT>
template <class IntT>
IntT ScaledNumber<DigitsT>::toInt() const {
typedef std::numeric_limits<IntT> Limits;
if (*this < 1)
return 0;
if (*this >= Limits::max())
return Limits::max();
IntT N = Digits;
if (Exponent > 0) {
assert(size_t(Exponent) < sizeof(IntT) * 8);
return N << Exponent;
}
if (Exponent < 0) {
assert(size_t(-Exponent) < sizeof(IntT) * 8);
return N >> -Exponent;
}
return N;
}
template <class DigitsT>
ScaledNumber<DigitsT> &ScaledNumber<DigitsT>::
operator*=(const ScaledNumber &X) {
if (isZero())
return *this;
if (X.isZero())
return *this = X;
// Save the exponents.
int32_t Exponents = int32_t(Exponent) + int32_t(X.Exponent);
// Get the raw product.
*this = getProduct(Digits, X.Digits);
// Combine with exponents.
return *this <<= Exponents;
}
template <class DigitsT>
ScaledNumber<DigitsT> &ScaledNumber<DigitsT>::
operator/=(const ScaledNumber &X) {
if (isZero())
return *this;
if (X.isZero())
return *this = getLargest();
// Save the exponents.
int32_t Exponents = int32_t(Exponent) - int32_t(X.Exponent);
// Get the raw quotient.
*this = getQuotient(Digits, X.Digits);
// Combine with exponents.
return *this <<= Exponents;
}
template <class DigitsT> void ScaledNumber<DigitsT>::shiftLeft(int32_t Shift) {
if (!Shift || isZero())
return;
assert(Shift != INT32_MIN);
if (Shift < 0) {
shiftRight(-Shift);
return;
}
// Shift as much as we can in the exponent.
int32_t ExponentShift = std::min(Shift, MaxExponent - Exponent);
Exponent += ExponentShift;
if (ExponentShift == Shift)
return;
// Check this late, since it's rare.
if (isLargest())
return;
// Shift the digits themselves.
Shift -= ExponentShift;
if (Shift > countLeadingZerosWidth(Digits)) {
// Saturate.
*this = getLargest();
return;
}
Digits <<= Shift;
return;
}
template <class DigitsT> void ScaledNumber<DigitsT>::shiftRight(int32_t Shift) {
if (!Shift || isZero())
return;
assert(Shift != INT32_MIN);
if (Shift < 0) {
shiftLeft(-Shift);
return;
}
// Shift as much as we can in the exponent.
int32_t ExponentShift = std::min(Shift, Exponent - MinExponent);
Exponent -= ExponentShift;
if (ExponentShift == Shift)
return;
// Shift the digits themselves.
Shift -= ExponentShift;
if (Shift >= Width) {
// Saturate.
*this = getZero();
return;
}
Digits >>= Shift;
return;
}
template <class T> struct isPodLike<ScaledNumber<T>> {
static const bool value = true;
};
}
//===----------------------------------------------------------------------===//
//
// BlockMass definition.
//
// TODO: Make this private to BlockFrequencyInfoImpl or delete.
//
//===----------------------------------------------------------------------===//
namespace llvm {
/// \brief Mass of a block.
///
/// This class implements a sort of fixed-point fraction always between 0.0 and
/// 1.0. getMass() == UINT64_MAX indicates a value of 1.0.
///
/// Masses can be added and subtracted. Simple saturation arithmetic is used,
/// so arithmetic operations never overflow or underflow.
///
/// Masses can be multiplied. Multiplication treats full mass as 1.0 and uses
/// an inexpensive floating-point algorithm that's off-by-one (almost, but not
/// quite, maximum precision).
///
/// Masses can be scaled by \a BranchProbability at maximum precision.
class BlockMass {
uint64_t Mass;
public:
BlockMass() : Mass(0) {}
explicit BlockMass(uint64_t Mass) : Mass(Mass) {}
static BlockMass getEmpty() { return BlockMass(); }
static BlockMass getFull() { return BlockMass(UINT64_MAX); }
uint64_t getMass() const { return Mass; }
bool isFull() const { return Mass == UINT64_MAX; }
bool isEmpty() const { return !Mass; }
bool operator!() const { return isEmpty(); }
/// \brief Add another mass.
///
/// Adds another mass, saturating at \a isFull() rather than overflowing.
BlockMass &operator+=(const BlockMass &X) {
uint64_t Sum = Mass + X.Mass;
Mass = Sum < Mass ? UINT64_MAX : Sum;
return *this;
}
/// \brief Subtract another mass.
///
/// Subtracts another mass, saturating at \a isEmpty() rather than
/// undeflowing.
BlockMass &operator-=(const BlockMass &X) {
uint64_t Diff = Mass - X.Mass;
Mass = Diff > Mass ? 0 : Diff;
return *this;
}
BlockMass &operator*=(const BranchProbability &P) {
Mass = P.scale(Mass);
return *this;
}
bool operator==(const BlockMass &X) const { return Mass == X.Mass; }
bool operator!=(const BlockMass &X) const { return Mass != X.Mass; }
bool operator<=(const BlockMass &X) const { return Mass <= X.Mass; }
bool operator>=(const BlockMass &X) const { return Mass >= X.Mass; }
bool operator<(const BlockMass &X) const { return Mass < X.Mass; }
bool operator>(const BlockMass &X) const { return Mass > X.Mass; }
/// \brief Convert to floating point.
///
/// Convert to a float. \a isFull() gives 1.0, while \a isEmpty() gives
/// slightly above 0.0.
ScaledNumber<uint64_t> toFloat() const;
void dump() const;
raw_ostream &print(raw_ostream &OS) const;
};
inline BlockMass operator+(const BlockMass &L, const BlockMass &R) {
return BlockMass(L) += R;
}
inline BlockMass operator-(const BlockMass &L, const BlockMass &R) {
return BlockMass(L) -= R;
}
inline BlockMass operator*(const BlockMass &L, const BranchProbability &R) {
return BlockMass(L) *= R;
}
inline BlockMass operator*(const BranchProbability &L, const BlockMass &R) {
return BlockMass(R) *= L;
}
inline raw_ostream &operator<<(raw_ostream &OS, const BlockMass &X) {
return X.print(OS);
}
template <> struct isPodLike<BlockMass> {
static const bool value = true;
};
}
//===----------------------------------------------------------------------===//
//
// BlockFrequencyInfoImpl definition.
//
//===----------------------------------------------------------------------===//
namespace llvm {
class BasicBlock;
class BranchProbabilityInfo;
class Function;
class Loop;
class LoopInfo;
class MachineBasicBlock;
class MachineBranchProbabilityInfo;
class MachineFunction;
class MachineLoop;
class MachineLoopInfo;
namespace bfi_detail {
struct IrreducibleGraph;
// This is part of a workaround for a GCC 4.7 crash on lambdas.
template <class BT> struct BlockEdgesAdder;
}
/// \brief Base class for BlockFrequencyInfoImpl
///
/// BlockFrequencyInfoImplBase has supporting data structures and some
/// algorithms for BlockFrequencyInfoImplBase. Only algorithms that depend on
/// the block type (or that call such algorithms) are skipped here.
///
/// Nevertheless, the majority of the overall algorithm documention lives with
/// BlockFrequencyInfoImpl. See there for details.
class BlockFrequencyInfoImplBase {
public:
typedef ScaledNumber<uint64_t> Float;
/// \brief Representative of a block.
///
/// This is a simple wrapper around an index into the reverse-post-order
/// traversal of the blocks.
///
/// Unlike a block pointer, its order has meaning (location in the
/// topological sort) and it's class is the same regardless of block type.
struct BlockNode {
typedef uint32_t IndexType;
IndexType Index;
bool operator==(const BlockNode &X) const { return Index == X.Index; }
bool operator!=(const BlockNode &X) const { return Index != X.Index; }
bool operator<=(const BlockNode &X) const { return Index <= X.Index; }
bool operator>=(const BlockNode &X) const { return Index >= X.Index; }
bool operator<(const BlockNode &X) const { return Index < X.Index; }
bool operator>(const BlockNode &X) const { return Index > X.Index; }
BlockNode() : Index(UINT32_MAX) {}
BlockNode(IndexType Index) : Index(Index) {}
bool isValid() const { return Index <= getMaxIndex(); }
static size_t getMaxIndex() { return UINT32_MAX - 1; }
};
/// \brief Stats about a block itself.
struct FrequencyData {
Float Floating;
uint64_t Integer;
};
/// \brief Data about a loop.
///
/// Contains the data necessary to represent represent a loop as a
/// pseudo-node once it's packaged.
struct LoopData {
typedef SmallVector<std::pair<BlockNode, BlockMass>, 4> ExitMap;
typedef SmallVector<BlockNode, 4> NodeList;
LoopData *Parent; ///< The parent loop.
bool IsPackaged; ///< Whether this has been packaged.
uint32_t NumHeaders; ///< Number of headers.
ExitMap Exits; ///< Successor edges (and weights).
NodeList Nodes; ///< Header and the members of the loop.
BlockMass BackedgeMass; ///< Mass returned to loop header.
BlockMass Mass;
Float Scale;
LoopData(LoopData *Parent, const BlockNode &Header)
: Parent(Parent), IsPackaged(false), NumHeaders(1), Nodes(1, Header) {}
template <class It1, class It2>
LoopData(LoopData *Parent, It1 FirstHeader, It1 LastHeader, It2 FirstOther,
It2 LastOther)
: Parent(Parent), IsPackaged(false), Nodes(FirstHeader, LastHeader) {
NumHeaders = Nodes.size();
Nodes.insert(Nodes.end(), FirstOther, LastOther);
}
bool isHeader(const BlockNode &Node) const {
if (isIrreducible())
return std::binary_search(Nodes.begin(), Nodes.begin() + NumHeaders,
Node);
return Node == Nodes[0];
}
BlockNode getHeader() const { return Nodes[0]; }
bool isIrreducible() const { return NumHeaders > 1; }
NodeList::const_iterator members_begin() const {
return Nodes.begin() + NumHeaders;
}
NodeList::const_iterator members_end() const { return Nodes.end(); }
iterator_range<NodeList::const_iterator> members() const {
return make_range(members_begin(), members_end());
}
};
/// \brief Index of loop information.
struct WorkingData {
BlockNode Node; ///< This node.
LoopData *Loop; ///< The loop this block is inside.
BlockMass Mass; ///< Mass distribution from the entry block.
WorkingData(const BlockNode &Node) : Node(Node), Loop(nullptr) {}
bool isLoopHeader() const { return Loop && Loop->isHeader(Node); }
bool isDoubleLoopHeader() const {
return isLoopHeader() && Loop->Parent && Loop->Parent->isIrreducible() &&
Loop->Parent->isHeader(Node);
}
LoopData *getContainingLoop() const {
if (!isLoopHeader())
return Loop;
if (!isDoubleLoopHeader())
return Loop->Parent;
return Loop->Parent->Parent;
}
/// \brief Resolve a node to its representative.
///
/// Get the node currently representing Node, which could be a containing
/// loop.
///
/// This function should only be called when distributing mass. As long as
/// there are no irreducilbe edges to Node, then it will have complexity
/// O(1) in this context.
///
/// In general, the complexity is O(L), where L is the number of loop
/// headers Node has been packaged into. Since this method is called in
/// the context of distributing mass, L will be the number of loop headers
/// an early exit edge jumps out of.
BlockNode getResolvedNode() const {
auto L = getPackagedLoop();
return L ? L->getHeader() : Node;
}
LoopData *getPackagedLoop() const {
if (!Loop || !Loop->IsPackaged)
return nullptr;
auto L = Loop;
while (L->Parent && L->Parent->IsPackaged)
L = L->Parent;
return L;
}
/// \brief Get the appropriate mass for a node.
///
/// Get appropriate mass for Node. If Node is a loop-header (whose loop
/// has been packaged), returns the mass of its pseudo-node. If it's a
/// node inside a packaged loop, it returns the loop's mass.
BlockMass &getMass() {
if (!isAPackage())
return Mass;
if (!isADoublePackage())
return Loop->Mass;
return Loop->Parent->Mass;
}
/// \brief Has ContainingLoop been packaged up?
bool isPackaged() const { return getResolvedNode() != Node; }
/// \brief Has Loop been packaged up?
bool isAPackage() const { return isLoopHeader() && Loop->IsPackaged; }
/// \brief Has Loop been packaged up twice?
bool isADoublePackage() const {
return isDoubleLoopHeader() && Loop->Parent->IsPackaged;
}
};
/// \brief Unscaled probability weight.
///
/// Probability weight for an edge in the graph (including the
/// successor/target node).
///
/// All edges in the original function are 32-bit. However, exit edges from
/// loop packages are taken from 64-bit exit masses, so we need 64-bits of
/// space in general.
///
/// In addition to the raw weight amount, Weight stores the type of the edge
/// in the current context (i.e., the context of the loop being processed).
/// Is this a local edge within the loop, an exit from the loop, or a
/// backedge to the loop header?
struct Weight {
enum DistType { Local, Exit, Backedge };
DistType Type;
BlockNode TargetNode;
uint64_t Amount;
Weight() : Type(Local), Amount(0) {}
};
/// \brief Distribution of unscaled probability weight.
///
/// Distribution of unscaled probability weight to a set of successors.
///
/// This class collates the successor edge weights for later processing.
///
/// \a DidOverflow indicates whether \a Total did overflow while adding to
/// the distribution. It should never overflow twice.
struct Distribution {
typedef SmallVector<Weight, 4> WeightList;
WeightList Weights; ///< Individual successor weights.
uint64_t Total; ///< Sum of all weights.
bool DidOverflow; ///< Whether \a Total did overflow.
Distribution() : Total(0), DidOverflow(false) {}
void addLocal(const BlockNode &Node, uint64_t Amount) {
add(Node, Amount, Weight::Local);
}
void addExit(const BlockNode &Node, uint64_t Amount) {
add(Node, Amount, Weight::Exit);
}
void addBackedge(const BlockNode &Node, uint64_t Amount) {
add(Node, Amount, Weight::Backedge);
}
/// \brief Normalize the distribution.
///
/// Combines multiple edges to the same \a Weight::TargetNode and scales
/// down so that \a Total fits into 32-bits.
///
/// This is linear in the size of \a Weights. For the vast majority of
/// cases, adjacent edge weights are combined by sorting WeightList and
/// combining adjacent weights. However, for very large edge lists an
/// auxiliary hash table is used.
void normalize();
private:
void add(const BlockNode &Node, uint64_t Amount, Weight::DistType Type);
};
/// \brief Data about each block. This is used downstream.
std::vector<FrequencyData> Freqs;
/// \brief Loop data: see initializeLoops().
std::vector<WorkingData> Working;
/// \brief Indexed information about loops.
std::list<LoopData> Loops;
/// \brief Add all edges out of a packaged loop to the distribution.
///
/// Adds all edges from LocalLoopHead to Dist. Calls addToDist() to add each
/// successor edge.
///
/// \return \c true unless there's an irreducible backedge.
bool addLoopSuccessorsToDist(const LoopData *OuterLoop, LoopData &Loop,
Distribution &Dist);
/// \brief Add an edge to the distribution.
///
/// Adds an edge to Succ to Dist. If \c LoopHead.isValid(), then whether the
/// edge is local/exit/backedge is in the context of LoopHead. Otherwise,
/// every edge should be a local edge (since all the loops are packaged up).
///
/// \return \c true unless aborted due to an irreducible backedge.
bool addToDist(Distribution &Dist, const LoopData *OuterLoop,
const BlockNode &Pred, const BlockNode &Succ, uint64_t Weight);
LoopData &getLoopPackage(const BlockNode &Head) {
assert(Head.Index < Working.size());
assert(Working[Head.Index].isLoopHeader());
return *Working[Head.Index].Loop;
}
/// \brief Analyze irreducible SCCs.
///
/// Separate irreducible SCCs from \c G, which is an explict graph of \c
/// OuterLoop (or the top-level function, if \c OuterLoop is \c nullptr).
/// Insert them into \a Loops before \c Insert.
///
/// \return the \c LoopData nodes representing the irreducible SCCs.
iterator_range<std::list<LoopData>::iterator>
analyzeIrreducible(const bfi_detail::IrreducibleGraph &G, LoopData *OuterLoop,
std::list<LoopData>::iterator Insert);
/// \brief Update a loop after packaging irreducible SCCs inside of it.
///
/// Update \c OuterLoop. Before finding irreducible control flow, it was
/// partway through \a computeMassInLoop(), so \a LoopData::Exits and \a
/// LoopData::BackedgeMass need to be reset. Also, nodes that were packaged
/// up need to be removed from \a OuterLoop::Nodes.
void updateLoopWithIrreducible(LoopData &OuterLoop);
/// \brief Distribute mass according to a distribution.
///
/// Distributes the mass in Source according to Dist. If LoopHead.isValid(),
/// backedges and exits are stored in its entry in Loops.
///
/// Mass is distributed in parallel from two copies of the source mass.
void distributeMass(const BlockNode &Source, LoopData *OuterLoop,
Distribution &Dist);
/// \brief Compute the loop scale for a loop.
void computeLoopScale(LoopData &Loop);
/// \brief Package up a loop.
void packageLoop(LoopData &Loop);
/// \brief Unwrap loops.
void unwrapLoops();
/// \brief Finalize frequency metrics.
///
/// Calculates final frequencies and cleans up no-longer-needed data
/// structures.
void finalizeMetrics();
/// \brief Clear all memory.
void clear();
virtual std::string getBlockName(const BlockNode &Node) const;
std::string getLoopName(const LoopData &Loop) const;
virtual raw_ostream &print(raw_ostream &OS) const { return OS; }
void dump() const { print(dbgs()); }
Float getFloatingBlockFreq(const BlockNode &Node) const;
BlockFrequency getBlockFreq(const BlockNode &Node) const;
raw_ostream &printBlockFreq(raw_ostream &OS, const BlockNode &Node) const;
raw_ostream &printBlockFreq(raw_ostream &OS,
const BlockFrequency &Freq) const;
uint64_t getEntryFreq() const {
assert(!Freqs.empty());
return Freqs[0].Integer;
}
/// \brief Virtual destructor.
///
/// Need a virtual destructor to mask the compiler warning about
/// getBlockName().
virtual ~BlockFrequencyInfoImplBase() {}
};
namespace bfi_detail {
template <class BlockT> struct TypeMap {};
template <> struct TypeMap<BasicBlock> {
typedef BasicBlock BlockT;
typedef Function FunctionT;
typedef BranchProbabilityInfo BranchProbabilityInfoT;
typedef Loop LoopT;
typedef LoopInfo LoopInfoT;
};
template <> struct TypeMap<MachineBasicBlock> {
typedef MachineBasicBlock BlockT;
typedef MachineFunction FunctionT;
typedef MachineBranchProbabilityInfo BranchProbabilityInfoT;
typedef MachineLoop LoopT;
typedef MachineLoopInfo LoopInfoT;
};
/// \brief Get the name of a MachineBasicBlock.
///
/// Get the name of a MachineBasicBlock. It's templated so that including from
/// CodeGen is unnecessary (that would be a layering issue).
///
/// This is used mainly for debug output. The name is similar to
/// MachineBasicBlock::getFullName(), but skips the name of the function.
template <class BlockT> std::string getBlockName(const BlockT *BB) {
assert(BB && "Unexpected nullptr");
auto MachineName = "BB" + Twine(BB->getNumber());
if (BB->getBasicBlock())
return (MachineName + "[" + BB->getName() + "]").str();
return MachineName.str();
}
/// \brief Get the name of a BasicBlock.
template <> inline std::string getBlockName(const BasicBlock *BB) {
assert(BB && "Unexpected nullptr");
return BB->getName().str();
}
/// \brief Graph of irreducible control flow.
///
/// This graph is used for determining the SCCs in a loop (or top-level
/// function) that has irreducible control flow.
///
/// During the block frequency algorithm, the local graphs are defined in a
/// light-weight way, deferring to the \a BasicBlock or \a MachineBasicBlock
/// graphs for most edges, but getting others from \a LoopData::ExitMap. The
/// latter only has successor information.
///
/// \a IrreducibleGraph makes this graph explicit. It's in a form that can use
/// \a GraphTraits (so that \a analyzeIrreducible() can use \a scc_iterator),
/// and it explicitly lists predecessors and successors. The initialization
/// that relies on \c MachineBasicBlock is defined in the header.
struct IrreducibleGraph {
typedef BlockFrequencyInfoImplBase BFIBase;
BFIBase &BFI;
typedef BFIBase::BlockNode BlockNode;
struct IrrNode {
BlockNode Node;
unsigned NumIn;
std::deque<const IrrNode *> Edges;
IrrNode(const BlockNode &Node) : Node(Node), NumIn(0) {}
typedef std::deque<const IrrNode *>::const_iterator iterator;
iterator pred_begin() const { return Edges.begin(); }
iterator succ_begin() const { return Edges.begin() + NumIn; }
iterator pred_end() const { return succ_begin(); }
iterator succ_end() const { return Edges.end(); }
};
BlockNode Start;
const IrrNode *StartIrr;
std::vector<IrrNode> Nodes;
SmallDenseMap<uint32_t, IrrNode *, 4> Lookup;
/// \brief Construct an explicit graph containing irreducible control flow.
///
/// Construct an explicit graph of the control flow in \c OuterLoop (or the
/// top-level function, if \c OuterLoop is \c nullptr). Uses \c
/// addBlockEdges to add block successors that have not been packaged into
/// loops.
///
/// \a BlockFrequencyInfoImpl::computeIrreducibleMass() is the only expected
/// user of this.
template <class BlockEdgesAdder>
IrreducibleGraph(BFIBase &BFI, const BFIBase::LoopData *OuterLoop,
BlockEdgesAdder addBlockEdges)
: BFI(BFI), StartIrr(nullptr) {
initialize(OuterLoop, addBlockEdges);
}
template <class BlockEdgesAdder>
void initialize(const BFIBase::LoopData *OuterLoop,
BlockEdgesAdder addBlockEdges);
void addNodesInLoop(const BFIBase::LoopData &OuterLoop);
void addNodesInFunction();
void addNode(const BlockNode &Node) {
Nodes.emplace_back(Node);
BFI.Working[Node.Index].getMass() = BlockMass::getEmpty();
}
void indexNodes();
template <class BlockEdgesAdder>
void addEdges(const BlockNode &Node, const BFIBase::LoopData *OuterLoop,
BlockEdgesAdder addBlockEdges);
void addEdge(IrrNode &Irr, const BlockNode &Succ,
const BFIBase::LoopData *OuterLoop);
};
template <class BlockEdgesAdder>
void IrreducibleGraph::initialize(const BFIBase::LoopData *OuterLoop,
BlockEdgesAdder addBlockEdges) {
if (OuterLoop) {
addNodesInLoop(*OuterLoop);
for (auto N : OuterLoop->Nodes)
addEdges(N, OuterLoop, addBlockEdges);
} else {
addNodesInFunction();
for (uint32_t Index = 0; Index < BFI.Working.size(); ++Index)
addEdges(Index, OuterLoop, addBlockEdges);
}
StartIrr = Lookup[Start.Index];
}
template <class BlockEdgesAdder>
void IrreducibleGraph::addEdges(const BlockNode &Node,
const BFIBase::LoopData *OuterLoop,
BlockEdgesAdder addBlockEdges) {
auto L = Lookup.find(Node.Index);
if (L == Lookup.end())
return;
IrrNode &Irr = *L->second;
const auto &Working = BFI.Working[Node.Index];
if (Working.isAPackage())
for (const auto &I : Working.Loop->Exits)
addEdge(Irr, I.first, OuterLoop);
else
addBlockEdges(*this, Irr, OuterLoop);
}
}
/// \brief Shared implementation for block frequency analysis.
///
/// This is a shared implementation of BlockFrequencyInfo and
/// MachineBlockFrequencyInfo, and calculates the relative frequencies of
/// blocks.
///
/// LoopInfo defines a loop as a "non-trivial" SCC dominated by a single block,
/// which is called the header. A given loop, L, can have sub-loops, which are
/// loops within the subgraph of L that exclude its header. (A "trivial" SCC
/// consists of a single block that does not have a self-edge.)
///
/// In addition to loops, this algorithm has limited support for irreducible
/// SCCs, which are SCCs with multiple entry blocks. Irreducible SCCs are
/// discovered on they fly, and modelled as loops with multiple headers.
///
/// The headers of irreducible sub-SCCs consist of its entry blocks and all
/// nodes that are targets of a backedge within it (excluding backedges within
/// true sub-loops). Block frequency calculations act as if a block is
/// inserted that intercepts all the edges to the headers. All backedges and
/// entries point to this block. Its successors are the headers, which split
/// the frequency evenly.
///
/// This algorithm leverages BlockMass and ScaledNumber to maintain precision,
/// separates mass distribution from loop scaling, and dithers to eliminate
/// probability mass loss.
///
/// The implementation is split between BlockFrequencyInfoImpl, which knows the
/// type of graph being modelled (BasicBlock vs. MachineBasicBlock), and
/// BlockFrequencyInfoImplBase, which doesn't. The base class uses \a
/// BlockNode, a wrapper around a uint32_t. BlockNode is numbered from 0 in
/// reverse-post order. This gives two advantages: it's easy to compare the
/// relative ordering of two nodes, and maps keyed on BlockT can be represented
/// by vectors.
///
/// This algorithm is O(V+E), unless there is irreducible control flow, in
/// which case it's O(V*E) in the worst case.
///
/// These are the main stages:
///
/// 0. Reverse post-order traversal (\a initializeRPOT()).
///
/// Run a single post-order traversal and save it (in reverse) in RPOT.
/// All other stages make use of this ordering. Save a lookup from BlockT
/// to BlockNode (the index into RPOT) in Nodes.
///
/// 1. Loop initialization (\a initializeLoops()).
///
/// Translate LoopInfo/MachineLoopInfo into a form suitable for the rest of
/// the algorithm. In particular, store the immediate members of each loop
/// in reverse post-order.
///
/// 2. Calculate mass and scale in loops (\a computeMassInLoops()).
///
/// For each loop (bottom-up), distribute mass through the DAG resulting
/// from ignoring backedges and treating sub-loops as a single pseudo-node.
/// Track the backedge mass distributed to the loop header, and use it to
/// calculate the loop scale (number of loop iterations). Immediate
/// members that represent sub-loops will already have been visited and
/// packaged into a pseudo-node.
///
/// Distributing mass in a loop is a reverse-post-order traversal through
/// the loop. Start by assigning full mass to the Loop header. For each
/// node in the loop:
///
/// - Fetch and categorize the weight distribution for its successors.
/// If this is a packaged-subloop, the weight distribution is stored
/// in \a LoopData::Exits. Otherwise, fetch it from
/// BranchProbabilityInfo.
///
/// - Each successor is categorized as \a Weight::Local, a local edge
/// within the current loop, \a Weight::Backedge, a backedge to the
/// loop header, or \a Weight::Exit, any successor outside the loop.
/// The weight, the successor, and its category are stored in \a
/// Distribution. There can be multiple edges to each successor.
///
/// - If there's a backedge to a non-header, there's an irreducible SCC.
/// The usual flow is temporarily aborted. \a
/// computeIrreducibleMass() finds the irreducible SCCs within the
/// loop, packages them up, and restarts the flow.
///
/// - Normalize the distribution: scale weights down so that their sum
/// is 32-bits, and coalesce multiple edges to the same node.
///
/// - Distribute the mass accordingly, dithering to minimize mass loss,
/// as described in \a distributeMass().
///
/// Finally, calculate the loop scale from the accumulated backedge mass.
///
/// 3. Distribute mass in the function (\a computeMassInFunction()).
///
/// Finally, distribute mass through the DAG resulting from packaging all
/// loops in the function. This uses the same algorithm as distributing
/// mass in a loop, except that there are no exit or backedge edges.
///
/// 4. Unpackage loops (\a unwrapLoops()).
///
/// Initialize each block's frequency to a floating point representation of
/// its mass.
///
/// Visit loops top-down, scaling the frequencies of its immediate members
/// by the loop's pseudo-node's frequency.
///
/// 5. Convert frequencies to a 64-bit range (\a finalizeMetrics()).
///
/// Using the min and max frequencies as a guide, translate floating point
/// frequencies to an appropriate range in uint64_t.
///
/// It has some known flaws.
///
/// - Loop scale is limited to 4096 per loop (2^12) to avoid exhausting
/// BlockFrequency's 64-bit integer precision.
///
/// - The model of irreducible control flow is a rough approximation.
///
/// Modelling irreducible control flow exactly involves setting up and
/// solving a group of infinite geometric series. Such precision is
/// unlikely to be worthwhile, since most of our algorithms give up on
/// irreducible control flow anyway.
///
/// Nevertheless, we might find that we need to get closer. Here's a sort
/// of TODO list for the model with diminishing returns, to be completed as
/// necessary.
///
/// - The headers for the \a LoopData representing an irreducible SCC
/// include non-entry blocks. When these extra blocks exist, they
/// indicate a self-contained irreducible sub-SCC. We could treat them
/// as sub-loops, rather than arbitrarily shoving the problematic
/// blocks into the headers of the main irreducible SCC.
///
/// - Backedge frequencies are assumed to be evenly split between the
/// headers of a given irreducible SCC. Instead, we could track the
/// backedge mass separately for each header, and adjust their relative
/// frequencies.
///
/// - Entry frequencies are assumed to be evenly split between the
/// headers of a given irreducible SCC, which is the only option if we
/// need to compute mass in the SCC before its parent loop. Instead,
/// we could partially compute mass in the parent loop, and stop when
/// we get to the SCC. Here, we have the correct ratio of entry
/// masses, which we can use to adjust their relative frequencies.
/// Compute mass in the SCC, and then continue propagation in the
/// parent.
///
/// - We can propagate mass iteratively through the SCC, for some fixed
/// number of iterations. Each iteration starts by assigning the entry
/// blocks their backedge mass from the prior iteration. The final
/// mass for each block (and each exit, and the total backedge mass
/// used for computing loop scale) is the sum of all iterations.
/// (Running this until fixed point would "solve" the geometric
/// series by simulation.)
template <class BT> class BlockFrequencyInfoImpl : BlockFrequencyInfoImplBase {
typedef typename bfi_detail::TypeMap<BT>::BlockT BlockT;
typedef typename bfi_detail::TypeMap<BT>::FunctionT FunctionT;
typedef typename bfi_detail::TypeMap<BT>::BranchProbabilityInfoT
BranchProbabilityInfoT;
typedef typename bfi_detail::TypeMap<BT>::LoopT LoopT;
typedef typename bfi_detail::TypeMap<BT>::LoopInfoT LoopInfoT;
// This is part of a workaround for a GCC 4.7 crash on lambdas.
friend struct bfi_detail::BlockEdgesAdder<BT>;
typedef GraphTraits<const BlockT *> Successor;
typedef GraphTraits<Inverse<const BlockT *>> Predecessor;
const BranchProbabilityInfoT *BPI;
const LoopInfoT *LI;
const FunctionT *F;
// All blocks in reverse postorder.
std::vector<const BlockT *> RPOT;
DenseMap<const BlockT *, BlockNode> Nodes;
typedef typename std::vector<const BlockT *>::const_iterator rpot_iterator;
rpot_iterator rpot_begin() const { return RPOT.begin(); }
rpot_iterator rpot_end() const { return RPOT.end(); }
size_t getIndex(const rpot_iterator &I) const { return I - rpot_begin(); }
BlockNode getNode(const rpot_iterator &I) const {
return BlockNode(getIndex(I));
}
BlockNode getNode(const BlockT *BB) const { return Nodes.lookup(BB); }
const BlockT *getBlock(const BlockNode &Node) const {
assert(Node.Index < RPOT.size());
return RPOT[Node.Index];
}
/// \brief Run (and save) a post-order traversal.
///
/// Saves a reverse post-order traversal of all the nodes in \a F.
void initializeRPOT();
/// \brief Initialize loop data.
///
/// Build up \a Loops using \a LoopInfo. \a LoopInfo gives us a mapping from
/// each block to the deepest loop it's in, but we need the inverse. For each
/// loop, we store in reverse post-order its "immediate" members, defined as
/// the header, the headers of immediate sub-loops, and all other blocks in
/// the loop that are not in sub-loops.
void initializeLoops();
/// \brief Propagate to a block's successors.
///
/// In the context of distributing mass through \c OuterLoop, divide the mass
/// currently assigned to \c Node between its successors.
///
/// \return \c true unless there's an irreducible backedge.
bool propagateMassToSuccessors(LoopData *OuterLoop, const BlockNode &Node);
/// \brief Compute mass in a particular loop.
///
/// Assign mass to \c Loop's header, and then for each block in \c Loop in
/// reverse post-order, distribute mass to its successors. Only visits nodes
/// that have not been packaged into sub-loops.
///
/// \pre \a computeMassInLoop() has been called for each subloop of \c Loop.
/// \return \c true unless there's an irreducible backedge.
bool computeMassInLoop(LoopData &Loop);
/// \brief Try to compute mass in the top-level function.
///
/// Assign mass to the entry block, and then for each block in reverse
/// post-order, distribute mass to its successors. Skips nodes that have
/// been packaged into loops.
///
/// \pre \a computeMassInLoops() has been called.
/// \return \c true unless there's an irreducible backedge.
bool tryToComputeMassInFunction();
/// \brief Compute mass in (and package up) irreducible SCCs.
///
/// Find the irreducible SCCs in \c OuterLoop, add them to \a Loops (in front
/// of \c Insert), and call \a computeMassInLoop() on each of them.
///
/// If \c OuterLoop is \c nullptr, it refers to the top-level function.
///
/// \pre \a computeMassInLoop() has been called for each subloop of \c
/// OuterLoop.
/// \pre \c Insert points at the the last loop successfully processed by \a
/// computeMassInLoop().
/// \pre \c OuterLoop has irreducible SCCs.
void computeIrreducibleMass(LoopData *OuterLoop,
std::list<LoopData>::iterator Insert);
/// \brief Compute mass in all loops.
///
/// For each loop bottom-up, call \a computeMassInLoop().
///
/// \a computeMassInLoop() aborts (and returns \c false) on loops that
/// contain a irreducible sub-SCCs. Use \a computeIrreducibleMass() and then
/// re-enter \a computeMassInLoop().
///
/// \post \a computeMassInLoop() has returned \c true for every loop.
void computeMassInLoops();
/// \brief Compute mass in the top-level function.
///
/// Uses \a tryToComputeMassInFunction() and \a computeIrreducibleMass() to
/// compute mass in the top-level function.
///
/// \post \a tryToComputeMassInFunction() has returned \c true.
void computeMassInFunction();
std::string getBlockName(const BlockNode &Node) const override {
return bfi_detail::getBlockName(getBlock(Node));
}
public:
const FunctionT *getFunction() const { return F; }
void doFunction(const FunctionT *F, const BranchProbabilityInfoT *BPI,
const LoopInfoT *LI);
BlockFrequencyInfoImpl() : BPI(nullptr), LI(nullptr), F(nullptr) {}
using BlockFrequencyInfoImplBase::getEntryFreq;
BlockFrequency getBlockFreq(const BlockT *BB) const {
return BlockFrequencyInfoImplBase::getBlockFreq(getNode(BB));
}
Float getFloatingBlockFreq(const BlockT *BB) const {
return BlockFrequencyInfoImplBase::getFloatingBlockFreq(getNode(BB));
}
/// \brief Print the frequencies for the current function.
///
/// Prints the frequencies for the blocks in the current function.
///
/// Blocks are printed in the natural iteration order of the function, rather
/// than reverse post-order. This provides two advantages: writing -analyze
/// tests is easier (since blocks come out in source order), and even
/// unreachable blocks are printed.
///
/// \a BlockFrequencyInfoImplBase::print() only knows reverse post-order, so
/// we need to override it here.
raw_ostream &print(raw_ostream &OS) const override;
using BlockFrequencyInfoImplBase::dump;
using BlockFrequencyInfoImplBase::printBlockFreq;
raw_ostream &printBlockFreq(raw_ostream &OS, const BlockT *BB) const {
return BlockFrequencyInfoImplBase::printBlockFreq(OS, getNode(BB));
}
};
template <class BT>
void BlockFrequencyInfoImpl<BT>::doFunction(const FunctionT *F,
const BranchProbabilityInfoT *BPI,
const LoopInfoT *LI) {
// Save the parameters.
this->BPI = BPI;
this->LI = LI;
this->F = F;
// Clean up left-over data structures.
BlockFrequencyInfoImplBase::clear();
RPOT.clear();
Nodes.clear();
// Initialize.
DEBUG(dbgs() << "\nblock-frequency: " << F->getName() << "\n================="
<< std::string(F->getName().size(), '=') << "\n");
initializeRPOT();
initializeLoops();
// Visit loops in post-order to find thelocal mass distribution, and then do
// the full function.
computeMassInLoops();
computeMassInFunction();
unwrapLoops();
finalizeMetrics();
}
template <class BT> void BlockFrequencyInfoImpl<BT>::initializeRPOT() {
const BlockT *Entry = F->begin();
RPOT.reserve(F->size());
std::copy(po_begin(Entry), po_end(Entry), std::back_inserter(RPOT));
std::reverse(RPOT.begin(), RPOT.end());
assert(RPOT.size() - 1 <= BlockNode::getMaxIndex() &&
"More nodes in function than Block Frequency Info supports");
DEBUG(dbgs() << "reverse-post-order-traversal\n");
for (rpot_iterator I = rpot_begin(), E = rpot_end(); I != E; ++I) {
BlockNode Node = getNode(I);
DEBUG(dbgs() << " - " << getIndex(I) << ": " << getBlockName(Node) << "\n");
Nodes[*I] = Node;
}
Working.reserve(RPOT.size());
for (size_t Index = 0; Index < RPOT.size(); ++Index)
Working.emplace_back(Index);
Freqs.resize(RPOT.size());
}
template <class BT> void BlockFrequencyInfoImpl<BT>::initializeLoops() {
DEBUG(dbgs() << "loop-detection\n");
if (LI->empty())
return;
// Visit loops top down and assign them an index.
std::deque<std::pair<const LoopT *, LoopData *>> Q;
for (const LoopT *L : *LI)
Q.emplace_back(L, nullptr);
while (!Q.empty()) {
const LoopT *Loop = Q.front().first;
LoopData *Parent = Q.front().second;
Q.pop_front();
BlockNode Header = getNode(Loop->getHeader());
assert(Header.isValid());
Loops.emplace_back(Parent, Header);
Working[Header.Index].Loop = &Loops.back();
DEBUG(dbgs() << " - loop = " << getBlockName(Header) << "\n");
for (const LoopT *L : *Loop)
Q.emplace_back(L, &Loops.back());
}
// Visit nodes in reverse post-order and add them to their deepest containing
// loop.
for (size_t Index = 0; Index < RPOT.size(); ++Index) {
// Loop headers have already been mostly mapped.
if (Working[Index].isLoopHeader()) {
LoopData *ContainingLoop = Working[Index].getContainingLoop();
if (ContainingLoop)
ContainingLoop->Nodes.push_back(Index);
continue;
}
const LoopT *Loop = LI->getLoopFor(RPOT[Index]);
if (!Loop)
continue;
// Add this node to its containing loop's member list.
BlockNode Header = getNode(Loop->getHeader());
assert(Header.isValid());
const auto &HeaderData = Working[Header.Index];
assert(HeaderData.isLoopHeader());
Working[Index].Loop = HeaderData.Loop;
HeaderData.Loop->Nodes.push_back(Index);
DEBUG(dbgs() << " - loop = " << getBlockName(Header)
<< ": member = " << getBlockName(Index) << "\n");
}
}
template <class BT> void BlockFrequencyInfoImpl<BT>::computeMassInLoops() {
// Visit loops with the deepest first, and the top-level loops last.
for (auto L = Loops.rbegin(), E = Loops.rend(); L != E; ++L) {
if (computeMassInLoop(*L))
continue;
auto Next = std::next(L);
computeIrreducibleMass(&*L, L.base());
L = std::prev(Next);
if (computeMassInLoop(*L))
continue;
llvm_unreachable("unhandled irreducible control flow");
}
}
template <class BT>
bool BlockFrequencyInfoImpl<BT>::computeMassInLoop(LoopData &Loop) {
// Compute mass in loop.
DEBUG(dbgs() << "compute-mass-in-loop: " << getLoopName(Loop) << "\n");
if (Loop.isIrreducible()) {
BlockMass Remaining = BlockMass::getFull();
for (uint32_t H = 0; H < Loop.NumHeaders; ++H) {
auto &Mass = Working[Loop.Nodes[H].Index].getMass();
Mass = Remaining * BranchProbability(1, Loop.NumHeaders - H);
Remaining -= Mass;
}
for (const BlockNode &M : Loop.Nodes)
if (!propagateMassToSuccessors(&Loop, M))
llvm_unreachable("unhandled irreducible control flow");
} else {
Working[Loop.getHeader().Index].getMass() = BlockMass::getFull();
if (!propagateMassToSuccessors(&Loop, Loop.getHeader()))
llvm_unreachable("irreducible control flow to loop header!?");
for (const BlockNode &M : Loop.members())
if (!propagateMassToSuccessors(&Loop, M))
// Irreducible backedge.
return false;
}
computeLoopScale(Loop);
packageLoop(Loop);
return true;
}
template <class BT>
bool BlockFrequencyInfoImpl<BT>::tryToComputeMassInFunction() {
// Compute mass in function.
DEBUG(dbgs() << "compute-mass-in-function\n");
assert(!Working.empty() && "no blocks in function");
assert(!Working[0].isLoopHeader() && "entry block is a loop header");
Working[0].getMass() = BlockMass::getFull();
for (rpot_iterator I = rpot_begin(), IE = rpot_end(); I != IE; ++I) {
// Check for nodes that have been packaged.
BlockNode Node = getNode(I);
if (Working[Node.Index].isPackaged())
continue;
if (!propagateMassToSuccessors(nullptr, Node))
return false;
}
return true;
}
template <class BT> void BlockFrequencyInfoImpl<BT>::computeMassInFunction() {
if (tryToComputeMassInFunction())
return;
computeIrreducibleMass(nullptr, Loops.begin());
if (tryToComputeMassInFunction())
return;
llvm_unreachable("unhandled irreducible control flow");
}
/// \note This should be a lambda, but that crashes GCC 4.7.
namespace bfi_detail {
template <class BT> struct BlockEdgesAdder {
typedef BT BlockT;
typedef BlockFrequencyInfoImplBase::LoopData LoopData;
typedef GraphTraits<const BlockT *> Successor;
const BlockFrequencyInfoImpl<BT> &BFI;
explicit BlockEdgesAdder(const BlockFrequencyInfoImpl<BT> &BFI)
: BFI(BFI) {}
void operator()(IrreducibleGraph &G, IrreducibleGraph::IrrNode &Irr,
const LoopData *OuterLoop) {
const BlockT *BB = BFI.RPOT[Irr.Node.Index];
for (auto I = Successor::child_begin(BB), E = Successor::child_end(BB);
I != E; ++I)
G.addEdge(Irr, BFI.getNode(*I), OuterLoop);
}
};
}
template <class BT>
void BlockFrequencyInfoImpl<BT>::computeIrreducibleMass(
LoopData *OuterLoop, std::list<LoopData>::iterator Insert) {
DEBUG(dbgs() << "analyze-irreducible-in-";
if (OuterLoop) dbgs() << "loop: " << getLoopName(*OuterLoop) << "\n";
else dbgs() << "function\n");
using namespace bfi_detail;
// Ideally, addBlockEdges() would be declared here as a lambda, but that
// crashes GCC 4.7.
BlockEdgesAdder<BT> addBlockEdges(*this);
IrreducibleGraph G(*this, OuterLoop, addBlockEdges);
for (auto &L : analyzeIrreducible(G, OuterLoop, Insert))
computeMassInLoop(L);
if (!OuterLoop)
return;
updateLoopWithIrreducible(*OuterLoop);
}
template <class BT>
bool
BlockFrequencyInfoImpl<BT>::propagateMassToSuccessors(LoopData *OuterLoop,
const BlockNode &Node) {
DEBUG(dbgs() << " - node: " << getBlockName(Node) << "\n");
// Calculate probability for successors.
Distribution Dist;
if (auto *Loop = Working[Node.Index].getPackagedLoop()) {
assert(Loop != OuterLoop && "Cannot propagate mass in a packaged loop");
if (!addLoopSuccessorsToDist(OuterLoop, *Loop, Dist))
// Irreducible backedge.
return false;
} else {
const BlockT *BB = getBlock(Node);
for (auto SI = Successor::child_begin(BB), SE = Successor::child_end(BB);
SI != SE; ++SI)
// Do not dereference SI, or getEdgeWeight() is linear in the number of
// successors.
if (!addToDist(Dist, OuterLoop, Node, getNode(*SI),
BPI->getEdgeWeight(BB, SI)))
// Irreducible backedge.
return false;
}
// Distribute mass to successors, saving exit and backedge data in the
// loop header.
distributeMass(Node, OuterLoop, Dist);
return true;
}
template <class BT>
raw_ostream &BlockFrequencyInfoImpl<BT>::print(raw_ostream &OS) const {
if (!F)
return OS;
OS << "block-frequency-info: " << F->getName() << "\n";
for (const BlockT &BB : *F)
OS << " - " << bfi_detail::getBlockName(&BB)
<< ": float = " << getFloatingBlockFreq(&BB)
<< ", int = " << getBlockFreq(&BB).getFrequency() << "\n";
// Add an extra newline for readability.
OS << "\n";
return OS;
}
}
#undef DEBUG_TYPE
#endif