blob: a8464ac0fe60e58d021f44689ef9c5f5bf90fa7b [file] [log] [blame]
//===- BalancedPartitioning.h ---------------------------------------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This file implements BalancedPartitioning, a recursive balanced graph
// partitioning algorithm.
//
// The algorithm is used to find an ordering of FunctionNodes while optimizing
// a specified objective. The algorithm uses recursive bisection; it starts
// with a collection of unordered FunctionNodes and tries to split them into
// two sets (buckets) of equal cardinality. Each bisection step is comprised of
// iterations that greedily swap the FunctionNodes between the two buckets while
// there is an improvement of the objective. Once the process converges, the
// problem is divided into two sub-problems of half the size, which are
// recursively applied for the two buckets. The final ordering of the
// FunctionNodes is obtained by concatenating the two (recursively computed)
// orderings.
//
// In order to speed up the computation, we limit the depth of the recursive
// tree by a specified constant (SplitDepth) and apply at most a constant
// number of greedy iterations per split (IterationsPerSplit). The worst-case
// time complexity of the implementation is bounded by O(M*log^2 N), where
// N is the number of FunctionNodes and M is the number of
// FunctionNode-UtilityNode edges; (assuming that any collection of D
// FunctionNodes contains O(D) UtilityNodes). Notice that the two different
// recursive sub-problems are independent and thus can be efficiently processed
// in parallel.
//
// Reference:
// * Optimizing Function Layout for Mobile Applications,
// https://arxiv.org/abs/2211.09285
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_SUPPORT_BALANCED_PARTITIONING_H
#define LLVM_SUPPORT_BALANCED_PARTITIONING_H
#include "raw_ostream.h"
#include "llvm/ADT/ArrayRef.h"
#include <atomic>
#include <condition_variable>
#include <mutex>
#include <random>
#include <vector>
namespace llvm {
class ThreadPool;
/// A function with a set of utility nodes where it is beneficial to order two
/// functions close together if they have similar utility nodes
class BPFunctionNode {
friend class BalancedPartitioning;
public:
using IDT = uint64_t;
using UtilityNodeT = uint32_t;
/// \param UtilityNodes the set of utility nodes (must be unique'd)
BPFunctionNode(IDT Id, ArrayRef<UtilityNodeT> UtilityNodes)
: Id(Id), UtilityNodes(UtilityNodes) {}
/// The ID of this node
IDT Id;
void dump(raw_ostream &OS) const;
protected:
/// The list of utility nodes associated with this node
SmallVector<UtilityNodeT, 4> UtilityNodes;
/// The bucket assigned by balanced partitioning
std::optional<unsigned> Bucket;
/// The index of the input order of the FunctionNodes
uint64_t InputOrderIndex = 0;
friend class BPFunctionNodeTest_Basic_Test;
friend class BalancedPartitioningTest_Basic_Test;
friend class BalancedPartitioningTest_Large_Test;
};
/// Algorithm parameters; default values are tuned on real-world binaries
struct BalancedPartitioningConfig {
/// The depth of the recursive bisection
unsigned SplitDepth = 18;
/// The maximum number of bp iterations per split
unsigned IterationsPerSplit = 40;
/// The probability for a vertex to skip a move from its current bucket to
/// another bucket; it often helps to escape from a local optima
float SkipProbability = 0.1f;
/// Recursive subtasks up to the given depth are added to the queue and
/// distributed among threads by ThreadPool; all subsequent calls are executed
/// on the same thread
unsigned TaskSplitDepth = 9;
};
class BalancedPartitioning {
public:
BalancedPartitioning(const BalancedPartitioningConfig &Config);
/// Run recursive graph partitioning that optimizes a given objective.
void run(std::vector<BPFunctionNode> &Nodes) const;
private:
struct UtilitySignature;
using SignaturesT = SmallVector<UtilitySignature, 4>;
using FunctionNodeRange =
iterator_range<std::vector<BPFunctionNode>::iterator>;
/// A special ThreadPool that allows for spawning new tasks after blocking on
/// wait(). BalancedPartitioning recursively spawns new threads inside other
/// threads, so we need to track how many active threads that could spawn more
/// threads.
struct BPThreadPool {
ThreadPool &TheThreadPool;
std::mutex mtx;
std::condition_variable cv;
/// The number of threads that could spawn more threads
std::atomic<int> NumActiveThreads = 0;
/// Only true when all threads are down spawning new threads
bool IsFinishedSpawning = false;
/// Asynchronous submission of the task to the pool
template <typename Func> void async(Func &&F);
/// Blocking wait for all threads to complete. Unlike ThreadPool, it is
/// acceptable for other threads to add more tasks while blocking on this
/// call.
void wait();
BPThreadPool(ThreadPool &TheThreadPool) : TheThreadPool(TheThreadPool) {}
};
/// Run a recursive bisection of a given list of FunctionNodes
/// \param RecDepth the current depth of recursion
/// \param RootBucket the initial bucket of the dataVertices
/// \param Offset the assigned buckets are the range [Offset, Offset +
/// Nodes.size()]
void bisect(const FunctionNodeRange Nodes, unsigned RecDepth,
unsigned RootBucket, unsigned Offset,
std::optional<BPThreadPool> &TP) const;
/// Run bisection iterations
void runIterations(const FunctionNodeRange Nodes, unsigned RecDepth,
unsigned LeftBucket, unsigned RightBucket,
std::mt19937 &RNG) const;
/// Run a bisection iteration to improve the optimization goal
/// \returns the total number of moved FunctionNodes
unsigned runIteration(const FunctionNodeRange Nodes, unsigned LeftBucket,
unsigned RightBucket, SignaturesT &Signatures,
std::mt19937 &RNG) const;
/// Try to move \p N from one bucket to another
/// \returns true iff \p N is moved
bool moveFunctionNode(BPFunctionNode &N, unsigned LeftBucket,
unsigned RightBucket, SignaturesT &Signatures,
std::mt19937 &RNG) const;
/// Split all the FunctionNodes into 2 buckets, StartBucket and StartBucket +
/// 1 The method is used for an initial assignment before a bisection step
void split(const FunctionNodeRange Nodes, unsigned StartBucket) const;
/// The cost of the uniform log-gap cost, assuming a utility node has \p X
/// FunctionNodes in the left bucket and \p Y FunctionNodes in the right one.
float logCost(unsigned X, unsigned Y) const;
float log2Cached(unsigned i) const;
const BalancedPartitioningConfig &Config;
/// Precomputed values of log2(x). Table size is small enough to fit in cache.
static constexpr unsigned LOG_CACHE_SIZE = 16384;
float Log2Cache[LOG_CACHE_SIZE];
/// The signature of a particular utility node used for the bisection step,
/// i.e., the number of \p FunctionNodes in each of the two buckets
struct UtilitySignature {
/// The number of \p FunctionNodes in the left bucket
unsigned LeftCount = 0;
/// The number of \p FunctionNodes in the right bucket
unsigned RightCount = 0;
/// The cached gain of moving a \p FunctionNode from the left bucket to the
/// right bucket
float CachedGainLR;
/// The cached gain of moving a \p FunctionNode from the right bucket to the
/// left bucket
float CachedGainRL;
/// Whether \p CachedGainLR and \p CachedGainRL are valid
bool CachedGainIsValid = false;
};
protected:
/// Compute the move gain for uniform log-gap cost
static float moveGain(const BPFunctionNode &N, bool FromLeftToRight,
const SignaturesT &Signatures);
friend class BalancedPartitioningTest_MoveGain_Test;
};
} // end namespace llvm
#endif // LLVM_SUPPORT_BALANCED_PARTITIONING_H