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/*******************************************************************************
********************************************************************************
schedule : a schedule is an ordered set of nodes of some directed graph.
It capture the idea of computing the graph in a certain order that preserves
the dependecies.
Created by Yann Orlarey on 17/03/2020.
Copyright © 2023 Yann Orlarey. All rights reserved.
*******************************************************************************
******************************************************************************/
#pragma once
#include <algorithm> // for std::find
#include <cassert>
#include <functional>
#include <iostream>
#include <list>
#include <map>
#include <set>
#include <sstream>
#include <string>
#include <vector>
#include "DirectedGraph.hh"
#include "DirectedGraphAlgorythm.hh"
/**
* @brief a schedule gives the computation order of the nodes of a DAG.
* A valid schedule is such if n->m in G, then order(n) > order(m), i.e. n
* must be computed after m because it depends on it.
*
* @tparam N
*/
template <typename N>
class schedule {
private:
std::vector<N> fElements; // ordered set of elements
std::map<N, int> fOrder; // order of each element (starting at 1, 0 indicates not in schedule)
public:
// number of elements in the schedule
[[nodiscard]] size_t size() const { return fElements.size(); }
// the vector of elements (for iterations)
[[nodiscard]] const std::vector<N>& elements() const { return fElements; }
// the order of an element in the schedule (starting from 1)
[[nodiscard]] int order(const N& n) const
{
auto it = fOrder.find(n);
return (it == fOrder.end()) ? 0 : it->second;
}
// append a new element to a schedule
schedule& append(const N& n)
{
if (fOrder[n] > 0) {
std::cerr << "WARNING, already scheduled" << '\n';
} else {
fElements.push_back(n);
fOrder[n] = int(fElements.size());
}
return *this;
}
// append all the elements of a schedule
schedule& append(const schedule<N>& S)
{
for (const N& n : S.elements()) {
append(n);
}
return *this;
}
// A schedule in reverse order
schedule reverse() const
{
schedule<N> S;
for (auto it = fElements.rbegin(); it != fElements.rend(); ++it) {
S.append(*it);
}
return S;
}
};
/**
* @brief print a schedule
*
* @tparam N
* @param file
* @param S the schedule
* @return std::ostream& the output stream
*/
template <typename N>
inline std::ostream& operator<<(std::ostream& file, const schedule<N>& S)
{
std::string sep = "";
file << "Schedule {";
for (const N& n : S.elements()) {
file << sep << S.order(n) << ":" << n;
sep = ", ";
}
return file << "}";
}
/**
* @brief Deep-first scheduling of a DAG G
*
* @tparam N the type of nodes of G
* @param G the graph we want to schedule
* @return schedule<N> the deep first schedule of G
*/
template <typename N>
inline schedule<N> dfschedule(const digraph<N>& G)
{
schedule<N> S;
std::set<N> V; // set of visited nodes
// recursive deep first visit (pseudo local function using a lambda)
std::function<void(const N&)> dfvisit = [&](const N& n) {
if (V.find(n) == V.end()) {
V.insert(n);
for (const auto& p : G.destinations(n)) {
dfvisit(p.first);
}
S.append(n);
}
};
for (const auto& n : roots(G)) {
dfvisit(n);
}
return S;
}
/**
* @brief Breadth-first scheduling of G
*
* @tparam N the type of the nodes of G
* @param G the graph we want to schedule
* @return schedule<N> the breadth first schedule of G
*/
template <typename N>
inline schedule<N> bfschedule(const digraph<N>& G)
{
std::vector<std::vector<N>> P = parallelize(G);
schedule<N> S;
for (uint64_t i = 0; i < P.size(); i++) {
for (const N& n : P[i]) {
S.append(n);
}
}
return S;
}
/**
* @brief special schedule for a DAG
*
* @tparam N
* @param G
* @return schedule<N>
*/
template <typename N>
inline schedule<N> spschedule(const digraph<N>& G)
{
std::set<N> V; // already scheduled nodes
schedule<N> S; // the final schedule
std::list<N> L = recschedule(G); // schedule list with duplicated
for (auto it = L.rbegin(); it != L.rend(); ++it) {
if (!V.contains(*it)) {
S.append(*it);
V.insert(*it);
}
}
return S;
}
/**
* @brief The 'cost' of a scheduling. The scheduling time distance
* between the nodes and its dependencies. This should be an indication
* of how hot the cache is kept by this scheduling. The less the cost
* is the better it is.
*
* @tparam N
* @param G
* @param S
* @return int
*/
template <typename N>
inline unsigned int schedulingcost(const digraph<N>& G, const schedule<N>& S)
{
unsigned int cost = 0;
for (const N& n : G.nodes()) {
unsigned int t1 = S.order(n);
for (const auto& c : G.destinations(n)) {
unsigned int t0 = S.order(c.first);
// assert(t1 > t0);
cost += (t1 - t0) * (t1 - t0); // We may have loops
}
}
return cost;
}
/**
* @brief Deep-first scheduling of a directed graph G with cycles
*
* @tparam N the type of nodes of G
* @param G the graph we want to schedule
* @return schedule<N> the deep first schedule of G
*/
template <typename N>
inline schedule<N> dfcyclesschedule(const digraph<N>& G)
{
digraph<digraph<N>> H = graph2dag(G);
schedule<digraph<N>> SH = dfschedule(H);
schedule<N> S;
for (const digraph<N>& n : SH.elements()) {
S.append(dfschedule(cut(n, 1)));
}
return S;
}
/**
* @brief Breadth-first scheduling of a directed graph G with cycles
*
* @tparam N the type of nodes of G
* @param G the graph we want to schedule
* @return schedule<N> the deep first schedule of G
*/
template <typename N>
inline schedule<N> bfcyclesschedule(const digraph<N>& G)
{
digraph<digraph<N>> H = graph2dag(G);
schedule<digraph<N>> SH = bfschedule(H);
schedule<N> S;
for (const digraph<N>& n : SH.elements()) {
S.append(dfschedule(cut(n, 1)));
}
return S;
}
/**
* @brief reverse breadth first schedule for a DAG
*
* @tparam N
* @param G
* @return schedule<N>
*/
template <typename N>
inline schedule<N> rbschedule(const digraph<N>& G)
{
std::vector<std::vector<N>> P = parallelize(reverse(G));
schedule<N> S;
for (uint64_t i = 0; i < P.size(); i++) {
for (const N& n : P[i]) {
S.append(n);
}
}
return S.reverse();
}
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