macrotaskq.h

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/**
 \file macrotaskq.h
 \brief Declares the \c macrotaskq and MacroTaskBase classes
 \ingroup mra
 
 A MacroTaskq executes tasks on World objects, e.g. differentiation of a function or other
 arithmetic. Complex algorithms can be implemented.
 
 The universe world is split into subworlds, each of them executing macrotasks of the task queue.
 This improves locality and speedups for large number of compute nodes, by reducing communications
 within worlds.
 
 The user defines a macrotask (an example is found in test_vectormacrotask.cc), the tasks are
 lightweight and carry only bookkeeping information, actual input and output are stored in a
 cloud (see cloud.h)
 
 The user-defined macrotask is derived from MacroTaskIntermediate and must implement the run()
 method. A heterogeneous task queue is possible.
 
 The result of a macrotask is an object that lives in the universe and that is accessible from all
 subworlds. The result is accumulated in the universe and must therefore be a WorldObject. Currently we
 have implemented
  - Function<T,NDIM>
  - std::vector<Function<T,NDIM>> (a vector of Function<T,NDIM>)
  - ScalarResultImpl<T> (a scalar value)
  - std::vector<std::shared_ptr<ScalarResultImpl<T>>> (a vector of scalar values), shared_ptr for technical reasons
 
  - std::tuple<std::vector<XXX>, std::vector<YYY>> (a tuple of n vectors of WorldObjects: XXX, YYY, .. = {Function, ScalarResultImpl, ...})
 
 
 TODO: priority q
 TODO: task submission from inside task (serialize task instead of replicate)
 TODO: update documentation
 TODO: consider serializing task member variables
 
*/
 
 
 
#ifndef SRC_MADNESS_MRA_MACROTASKQ_H_
#define SRC_MADNESS_MRA_MACROTASKQ_H_
 
#include <madness/world/cloud.h>
#include <madness/world/world.h>
#include <madness/mra/macrotaskpartitioner.h>
 
namespace madness {
 
/// helper class for returning the result of a task, which is not a madness Function, but a simple scalar
 
/// the result value is accumulated via gaxpy in universe rank=0, after completion of the taskq the final
/// value can be obtained via get(), which includes a broadcast of the final value to all processes
template<typename T>
class ScalarResultImpl : public WorldObject<ScalarResultImpl<T>> {
public:
    typedef T value_type;
    ScalarResultImpl(World &world) : WorldObject<ScalarResultImpl<T>>(world) {
        this->process_pending();
    }
 
    /// Disable the default copy constructor
    ScalarResultImpl(const ScalarResultImpl& other) = delete;
    // ScalarResultImpl<T>(ScalarResultImpl<T>&& ) = default;
 
    /// disable assignment operator
    ScalarResultImpl<T>& operator=(const ScalarResultImpl<T>& other) = delete;
 
    ~ScalarResultImpl() {
        // print("calling destructor of ScalarResultImpl",this->id());
        // std::cout << std::flush;
    }
 
    /// simple assignment of the scalar value
    ScalarResultImpl<T>& operator=(const T& x) {
        value = x;
        return *this;
    }
 
    ScalarResultImpl<T>& operator+= (const T& x) {
        gaxpy(1.0, x, 1.0,true);
        return *this;
    }
 
    /// accumulate, optional fence
    void gaxpy(const double a, const T& right, double b, const bool fence=true) {
        if (this->get_world().rank()==0) {
            value =a*value + b * right;
        }
        else this->send(0, &ScalarResultImpl<T>::gaxpy, a, right, b, fence);
    }
 
    template<typename Archive>
    void serialize(Archive &ar) {
        ar & value;
    }
 
    /// after completion of the taskq get the final value
    T get() {
        this->get_world().gop.broadcast_serializable(*this, 0);
        return value;
    }
 
    /// get the local value of this rank, which might differ for different ranks
    /// for the final value use get()
    T get_local() const {
        return value;
    }
 
private:
    /// the scalar value
    T value=T();
};
 
template<typename T=double>
class ScalarResult {
public:
    typedef ScalarResultImpl<T> implT;
    std::shared_ptr<implT> impl;
 
    ScalarResult() = default;
    ScalarResult(World &world) : impl(new implT(world)) {}
    ScalarResult(const std::shared_ptr<implT>& impl) : impl(impl) {}
    ScalarResult& operator=(const T& x) {
        *(this->impl) = x;
        return *this;
    }
 
    std::shared_ptr<implT> get_impl() const {
        return impl;
    }
 
    void set_impl(const std::shared_ptr<implT>& newimpl) {
        impl=newimpl;
    }
 
    uniqueidT id() const {
        return impl->id();
    }
 
    /// accumulate, optional fence
    void gaxpy(const double a, const T& right, double b, const bool fence=true) {
        impl->gaxpy(a,right,b,fence);
    }
 
    template<typename Archive>
    void serialize(Archive &ar) {
        ar & impl;
    }
 
    /// after completion of the taskq get the final value
    T get() {
        return impl->get();
    }
 
    /// after completion of the taskq get the final value
    T get_local() const {
        return impl->get_local();
    }
 
};
 
/// helper function to create a vector of ScalarResultImpl, circumventing problems with the constructors
template<typename T>
std::vector<ScalarResult<T>> scalar_result_vector(World& world, std::size_t n)  {
    std::vector<ScalarResult<T>> v;
    for (std::size_t i=0; i<n; ++i) v.emplace_back(ScalarResult<T>(world));
    return v;
}
 
 
// type traits to check if a template parameter is a WorldContainer
template<typename>
struct is_scalar_result_ptr : std::false_type {};
 
template <typename T>
struct is_scalar_result_ptr<std::shared_ptr<madness::ScalarResultImpl<T>>> : std::true_type {};
 
template<typename>
struct is_scalar_result_ptr_vector : std::false_type {
};
 
template<typename T>
struct is_scalar_result_ptr_vector<std::vector<std::shared_ptr<typename madness::ScalarResultImpl<T>>>> : std::true_type {
};
 
// type traits to check if a template parameter is a WorldContainer
template<typename>
struct is_scalar_result : std::false_type {};
 
template <typename T>
struct is_scalar_result<madness::ScalarResult<T>> : std::true_type {};
 
template<typename>
struct is_scalar_result_impl : std::false_type {};
 
template <typename T>
struct is_scalar_result<madness::ScalarResultImpl<T>> : std::true_type {};
 
template<typename>
struct is_scalar_result_vector : std::false_type {
};
 
template<typename T>
struct is_scalar_result_vector<std::vector<typename madness::ScalarResult<T>>> : std::true_type {
};
 
/// check if type is a valid task result: it must be a WorldObject and must implement gaxpy
template <typename T>
inline constexpr bool is_valid_task_result_v =
                      is_madness_function<T>::value             // Function<T,NDIM>
                      || is_madness_function_vector<T>::value   // std::vector<Function<T,NDIM>>
                      || is_scalar_result<T>::value         // ScalarResultImpl<T>
                      || is_scalar_result_vector<T>::value  // std::vector<std::shared_ptr<ScalarResultImpl<T>>>
                      || is_scalar_result_ptr<T>::value         // ScalarResultImpl<T>
                      || is_scalar_result_ptr_vector<T>::value; // std::vector<std::shared_ptr<ScalarResultImpl<T>>>
 
 
template<typename> struct is_tuple : std::false_type { };
template<typename ...T> struct is_tuple<std::tuple<T...>> : std::true_type { };
 
/// given a tuple check recursively if all elements are valid task results
template<typename tupleT, std::size_t I>
constexpr bool check_tuple_is_valid_task_result() {
 
    typedef decay_tuple <tupleT> argtupleT;   // removes const, &, etc
 
    if constexpr(I >= std::tuple_size_v<tupleT>) {
        // Last case, if nothing is left to iterate, then exit the function
        return true;
    } else {
        using typeT = typename std::tuple_element<I, argtupleT>::type;// use decay types for determining a vector
        if constexpr (not is_valid_task_result_v<typeT>) {
            return false;
        } else {
            // Going for next element.
            return check_tuple_is_valid_task_result<tupleT,I+1>();
        }
    }
}
 
 
 
/// the result type of a macrotask must implement gaxpy
template<typename T>
void gaxpy(const double a, ScalarResult<T>& left, const double b, const T& right, const bool fence=true) {
    left.gaxpy(a, right, b, fence);
}
 
template <class Archive, typename T>
struct madness::archive::ArchiveStoreImpl<Archive, std::shared_ptr<ScalarResultImpl<T>>> {
    static void store(const Archive& ar, const std::shared_ptr<ScalarResultImpl<T>>& ptr) {
        bool exists=(ptr) ? true : false;
        ar & exists;
        if (exists) ar & ptr->id();
    }
};
 
 
template <class Archive, typename T>
struct madness::archive::ArchiveLoadImpl<Archive, std::shared_ptr<ScalarResultImpl<T>>> {
    static void load(const Archive& ar, std::shared_ptr<ScalarResultImpl<T>>& ptr) {
        bool exists=false;
        ar & exists;
        if (exists) {
            uniqueidT id;
            ar & id;
            World* world = World::world_from_id(id.get_world_id());
            MADNESS_ASSERT(world);
            auto ptr_opt = (world->ptr_from_id<  ScalarResultImpl<T> >(id));
            if (!ptr_opt)
            MADNESS_EXCEPTION("ScalarResultImpl: remote operation attempting to use a locally uninitialized object",0);
            ptr.reset(ptr_opt.value(), [] (ScalarResultImpl<T> *p_) -> void {}); // disable destruction
            if (!ptr)
            MADNESS_EXCEPTION("ScalarResultImpl<T> operation attempting to use an unregistered object",0);
        } else {
            ptr=nullptr;
        }
    }
};
 
 
/// base class
class MacroTaskBase {
public:
 
    typedef std::vector<std::shared_ptr<MacroTaskBase> > taskqT;
 
    MacroTaskBase() {}
    virtual ~MacroTaskBase() {};
 
    double priority=1.0;
    enum Status {Running, Waiting, Complete, Unknown} stat=Unknown;
 
    void set_complete() {stat=Complete;}
    void set_running() {stat=Running;}
    void set_waiting() {stat=Waiting;}
 
    bool is_complete() const {return stat==Complete;}
    bool is_running() const {return stat==Running;}
    bool is_waiting() const {return stat==Waiting;}
 
    virtual void run(World& world, Cloud& cloud, taskqT& taskq, const long element, const bool debug) = 0;
    virtual void cleanup() = 0;     // clear static data (presumably persistent input data)
 
    virtual void print_me(std::string s="") const {
        printf("this is task with priority %4.1f\n",priority);
    }
    virtual void print_me_as_table(std::string s="") const {
        print("nothing to print");
    }
    std::string print_priority_and_status_to_string() const {
        std::stringstream ss;
        ss << std::setw(5) << this->get_priority() << "  " <<this->stat;
        return ss.str();
    }
 
    double get_priority() const {return priority;}
    void set_priority(const double p) {priority=p;}
 
    friend std::ostream& operator<<(std::ostream& os, const MacroTaskBase::Status s) {
        if (s==MacroTaskBase::Status::Running) os << "Running";
        if (s==MacroTaskBase::Status::Waiting) os << "Waiting";
        if (s==MacroTaskBase::Status::Complete) os << "Complete";
        if (s==MacroTaskBase::Status::Unknown) os << "Unknown";
        return os;
    }
};
 
 
template<typename macrotaskT>
class MacroTaskIntermediate : public MacroTaskBase {
 
public:
 
    MacroTaskIntermediate() {}
 
    ~MacroTaskIntermediate() {}
 
    void cleanup() {};
};
 
 
 
class MacroTaskQ : public WorldObject< MacroTaskQ> {
 
    World& universe;
    std::shared_ptr<World> subworld_ptr;
    MacroTaskBase::taskqT taskq;
    std::mutex taskq_mutex;
    long printlevel=0;
    long nsubworld=1;
    std::shared_ptr< WorldDCPmapInterface< Key<1> > > pmap1;
    std::shared_ptr< WorldDCPmapInterface< Key<2> > > pmap2;
    std::shared_ptr< WorldDCPmapInterface< Key<3> > > pmap3;
    std::shared_ptr< WorldDCPmapInterface< Key<4> > > pmap4;
    std::shared_ptr< WorldDCPmapInterface< Key<5> > > pmap5;
    std::shared_ptr< WorldDCPmapInterface< Key<6> > > pmap6;
 
    bool printdebug() const {return printlevel>=10;}
    bool printprogress() const {return (printlevel>=3) and (not (printdebug()));}
    bool printtimings() const {return universe.rank()==0 and printlevel>=3;}
 
public:
 
    madness::Cloud cloud;
    World& get_subworld() {return *subworld_ptr;}
    long get_nsubworld() const {return nsubworld;}
    void set_printlevel(const long p) {printlevel=p;}
 
    /// create an empty taskq and initialize the subworlds
    MacroTaskQ(World& universe, int nworld, const long printlevel=0)
      : WorldObject<MacroTaskQ>(universe)
      , universe(universe)
      , taskq()
      , printlevel(printlevel)
      , nsubworld(nworld)
      , cloud(universe)
        {
 
        subworld_ptr=create_worlds(universe,nworld);
        this->process_pending();
    }
 
    ~MacroTaskQ() {}
 
    /// for each process create a world using a communicator shared with other processes by round-robin
    /// copy-paste from test_world.cc
static std::shared_ptr<World> create_worlds(World& universe, const std::size_t nsubworld) {
 
        int color = universe.rank() % nsubworld;
        SafeMPI::Intracomm comm = universe.mpi.comm().Split(color, universe.rank() / nsubworld);
 
        std::shared_ptr<World> all_worlds;
        all_worlds.reset(new World(comm));
 
        universe.gop.fence();
        return all_worlds;
    }
 
    /// run all tasks
    void run_all() {
 
        if (printdebug()) print_taskq();
        if (printtimings()) {
            print("number of tasks in taskq",taskq.size());
            print("redirecting output to files task.#####");
        }
 
        double cpu0=cpu_time();
        cloud.replicate();
        universe.gop.fence();
        double cpu1=cpu_time();
        if (printtimings()) print("cloud replication wall time",cpu1-cpu0);
        if (printdebug()) cloud.print_size(universe);
        universe.gop.set_forbid_fence(true); // make sure there are no hidden universe fences
        pmap1=FunctionDefaults<1>::get_pmap();
        pmap2=FunctionDefaults<2>::get_pmap();
        pmap3=FunctionDefaults<3>::get_pmap();
        pmap4=FunctionDefaults<4>::get_pmap();
        pmap5=FunctionDefaults<5>::get_pmap();
        pmap6=FunctionDefaults<6>::get_pmap();
        set_pmap(get_subworld());
 
        double cpu00=cpu_time();
 
        World& subworld=get_subworld();
//      if (printdebug()) print("I am subworld",subworld.id());
        double tasktime=0.0;
        if (printprogress() and universe.rank()==0) std::cout << "progress in percent: " << std::flush;
        while (true) {
            long element=get_scheduled_task_number(subworld);
            double cpu0=cpu_time();
            if (element<0) break;
            std::shared_ptr<MacroTaskBase> task=taskq[element];
            if (printdebug()) print("starting task no",element, "in subworld",subworld.id(),"at time",wall_time());
 
            task->run(subworld,cloud, taskq, element, printdebug());
 
            double cpu1=cpu_time();
            set_complete(element);
            tasktime+=(cpu1-cpu0);
            if (printdebug()) printf("completed task %3ld after %6.1fs at time %6.1fs\n",element,cpu1-cpu0,wall_time());
 
            // print progress
            const std::size_t ntask=taskq.size();
            // return percentile of ntask for element
            auto in_percentile = [&ntask](const long element) {
                return std::floor(element/(0.1*(ntask+1)));
            };
            auto is_first_in_percentile = [&](const long element) {
                return (in_percentile(element)!=in_percentile(element-1));
            };
            if (printprogress() and is_first_in_percentile(element)) {
                std::cout << int(in_percentile(element)*10) << " " << std::flush;
            }
        }
        universe.gop.set_forbid_fence(false);
        universe.gop.fence();
        universe.gop.sum(tasktime);
        if (printprogress() and universe.rank()==0) std::cout << std::endl;
        double cpu11=cpu_time();
        if (printlevel>=3) cloud.print_timings(universe);
        if (printtimings()) {
            printf("completed taskqueue after    %4.1fs at time %4.1fs\n", cpu11 - cpu00, wall_time());
            printf(" total cpu time / per world  %4.1fs %4.1fs\n", tasktime, tasktime / universe.size());
        }
 
        // cleanup task-persistent input data
        for (auto& task : taskq) task->cleanup();
        cloud.clear_cache(subworld);
        cloud.clear();
        subworld.gop.fence();
        subworld.gop.fence();
        universe.gop.fence();
        FunctionDefaults<1>::set_pmap(pmap1);
        FunctionDefaults<2>::set_pmap(pmap2);
        FunctionDefaults<3>::set_pmap(pmap3);
        FunctionDefaults<4>::set_pmap(pmap4);
        FunctionDefaults<5>::set_pmap(pmap5);
        FunctionDefaults<6>::set_pmap(pmap6);
        universe.gop.fence();
    }
 
    void add_tasks(MacroTaskBase::taskqT& vtask) {
        for (const auto& t : vtask) {
            if (universe.rank()==0) t->set_waiting();
            add_replicated_task(t);
        }
    }
 
    void print_taskq() const {
        universe.gop.fence();
        if (universe.rank()==0) {
            print("\ntaskq on universe rank",universe.rank());
            print("total number of tasks: ",taskq.size());
            print(" task                                   batch                 priority  status");
            for (const auto& t : taskq) t->print_me_as_table();
        }
        universe.gop.fence();
    }
 
private:
    void add_replicated_task(const std::shared_ptr<MacroTaskBase>& task) {
        taskq.push_back(task);
    }
 
    /// scheduler is located on universe.rank==0
    long get_scheduled_task_number(World& subworld) {
        long number=0;
        if (subworld.rank()==0) {
          Future<long> r = this->send(ProcessID(0), &MacroTaskQ::get_scheduled_task_number_local);
          number=r.get();
        }
        subworld.gop.broadcast_serializable(number, 0);
        subworld.gop.fence();
        return number;
 
    }
 
    long get_scheduled_task_number_local() {
        MADNESS_ASSERT(universe.rank()==0);
        std::lock_guard<std::mutex> lock(taskq_mutex);
 
        auto is_Waiting = [](const std::shared_ptr<MacroTaskBase>& mtb_ptr) {return mtb_ptr->is_waiting();};
        auto it=std::find_if(taskq.begin(),taskq.end(),is_Waiting);
        if (it!=taskq.end()) {
            it->get()->set_running();
            long element=it-taskq.begin();
            return element;
        }
//      print("could not find task to schedule");
        return -1;
    }
 
    /// scheduler is located on rank==0
    void set_complete(const long task_number) const {
        this->task(ProcessID(0), &MacroTaskQ::set_complete_local, task_number);
    }
 
    /// scheduler is located on rank==0
    void set_complete_local(const long task_number) const {
        MADNESS_ASSERT(universe.rank()==0);
        taskq[task_number]->set_complete();
    }
 
public:
    void static set_pmap(World& world) {
        FunctionDefaults<1>::set_default_pmap(world);
        FunctionDefaults<2>::set_default_pmap(world);
        FunctionDefaults<3>::set_default_pmap(world);
        FunctionDefaults<4>::set_default_pmap(world);
        FunctionDefaults<5>::set_default_pmap(world);
        FunctionDefaults<6>::set_default_pmap(world);
    }
private:
    std::size_t size() const {
        return taskq.size();
    }
 
};
 
 
 
 
template<typename taskT>
class MacroTask {
    using partitionT = MacroTaskPartitioner::partitionT;
 
    template<typename Q>
    struct is_vector : std::false_type {
    };
    template<typename Q>
    struct is_vector<std::vector<Q>> : std::true_type {
    };
 
    typedef typename taskT::resultT resultT;
    typedef typename taskT::argtupleT argtupleT;
    typedef Cloud::recordlistT recordlistT;
    taskT task;
    bool debug=false;
 
    /// RAII class to redirect cout to a file
    struct io_redirect {
        std::streambuf* stream_buffer_cout;
        std::ofstream ofile;
        bool debug=false;
 
        io_redirect(const long task_number, std::string filename, bool debug=false) : debug(debug) {
                    constexpr std::size_t bufsize=256;
                    char cfilename[bufsize];
            std::snprintf(cfilename,bufsize,"%s.%5.5ld",filename.c_str(),task_number);
            ofile=std::ofstream(cfilename);
            if (debug) std::cout << "redirecting to file " << cfilename << std::endl;
            stream_buffer_cout = std::cout.rdbuf(ofile.rdbuf());
            std::cout.sync_with_stdio(true);
        }
 
        ~io_redirect() {
            std::cout.rdbuf(stream_buffer_cout);
            ofile.close();
            std::cout.sync_with_stdio(true);
            if (debug) std::cout << "redirecting back to cout" << std::endl;
        }
    };
 
 
public:
 
    /// constructor takes the actual task
    MacroTask(World &world, taskT &task, std::shared_ptr<MacroTaskQ> taskq_ptr = 0)
            : task(task), world(world), taskq_ptr(taskq_ptr) {
        if (taskq_ptr) {
            // for the time being this condition must hold because tasks are
            // constructed as replicated objects and are not broadcast to other processes
            MADNESS_CHECK(world.id()==taskq_ptr->get_world().id());
        }
    }
 
    void set_debug(const bool value) {
        debug=value;
    }
 
 
    /// this mimicks the original call to the task functor, called from the universe
 
    /// store all input to the cloud, create output Function<T,NDIM> in the universe,
    /// create the batched task and shove it into the taskq. Possibly execute the taskq.
    template<typename ... Ts>
    resultT operator()(const Ts &... args) {
 
        const bool immediate_execution = (not taskq_ptr);
        if (not taskq_ptr) taskq_ptr.reset(new MacroTaskQ(world, world.size()));
        if (debug) taskq_ptr->set_printlevel(20);
 
        auto argtuple = std::tie(args...);
        static_assert(std::is_same<decltype(argtuple), argtupleT>::value, "type or number of arguments incorrect");
 
        // partition the argument vector into batches
        auto partitioner=task.partitioner;
        if (not partitioner) partitioner.reset(new MacroTaskPartitioner);
        partitioner->set_nsubworld(world.size());
        partitionT partition = partitioner->partition_tasks(argtuple);
 
        // store input and output: output being a pointer to a universe function (vector)
        recordlistT inputrecords = taskq_ptr->cloud.store(world, argtuple);
        resultT result = task.allocator(world, argtuple);
        auto outputrecords =prepare_output_records(taskq_ptr->cloud, result);
 
        // create tasks and add them to the taskq
        MacroTaskBase::taskqT vtask;
        for (const auto& batch_prio : partition) {
            vtask.push_back(
                    std::shared_ptr<MacroTaskBase>(new MacroTaskInternal(task, batch_prio, inputrecords, outputrecords)));
        }
        taskq_ptr->add_tasks(vtask);
 
        if (immediate_execution) taskq_ptr->run_all();
 
        return result;
    }
 
//private:
 
    World &world;
    std::shared_ptr<MacroTaskQ> taskq_ptr;
private:
 
 
    /// store *pointers* to the result WorldObject in the cloud and return the recordlist
    recordlistT prepare_output_records(Cloud &cloud, resultT& result) {
        if constexpr (is_tuple<resultT>::value) {
            static_assert(check_tuple_is_valid_task_result<resultT,0>(),
                            "tuple has invalid result type in prepare_output_records");
        } else {
            static_assert(is_valid_task_result_v<resultT>, "unknown result type in prepare_output_records");
        }
 
        if (debug) print("storing pointers to output in cloud");
        // store an element of the tuple only
        auto store_output_records = [&](const auto& result) {
            recordlistT outputrecords;
            typedef std::decay_t<decltype(result)> argT;
            if constexpr (is_madness_function<argT>::value) {
                outputrecords += cloud.store(world, result.get_impl().get()); // store pointer to FunctionImpl
            } else if constexpr (is_madness_function_vector<argT>::value) {
                outputrecords += cloud.store(world, get_impl(result));
            } else if constexpr (is_scalar_result<argT>::value) {
                outputrecords += cloud.store(world, result.get_impl());               // store pointer to ScalarResultImpl
            } else if constexpr (is_vector<argT>::value) {
                if (is_scalar_result<typename argT::value_type>::value) {
                    // argT = std::vector<ScalarResult<T>>
                    std::vector<std::shared_ptr<typename argT::value_type::implT>> v;
                    for (const auto& ptr : result) v.push_back(ptr.get_impl());
                    outputrecords+=cloud.store(world,v);
                } else {
                    MADNESS_EXCEPTION("\n\n  unknown vector result type in prepare_input ", 1);
                }
            } else {
                MADNESS_EXCEPTION("should not be here",1);
            }
            return outputrecords;
        };
 
        recordlistT outputrecords;
        if constexpr (is_tuple<resultT>::value) {
            // loop over tuple elements -- args is the individual tuple element
            std::apply([&](auto &&... args) {
                (( outputrecords+=store_output_records(args) ), ...);
            }, result);
        } else {
            outputrecords=store_output_records(result);
        }
        return outputrecords;
    }
 
 
    class MacroTaskInternal : public MacroTaskIntermediate<MacroTask> {
 
        typedef decay_tuple<typename taskT::argtupleT> argtupleT;   // removes const, &, etc
        typedef typename taskT::resultT resultT;
        recordlistT inputrecords;
        recordlistT outputrecords;
    public:
        taskT task;
        std::string get_name() const {
            if (task.name=="unknown_task") return typeid(task).name();
            return task.name;
        }
 
        MacroTaskInternal(const taskT &task, const std::pair<Batch,double> &batch_prio,
                          const recordlistT &inputrecords, const recordlistT &outputrecords)
      : inputrecords(inputrecords), outputrecords(outputrecords), task(task) {
            if constexpr (is_tuple<resultT>::value) {
                static_assert(check_tuple_is_valid_task_result<resultT,0>(),
                                "tuple has invalid result type in prepare_output_records");
            } else {
                static_assert(is_valid_task_result_v<resultT>, "unknown result type in prepare_output_records");
            }
            this->task.batch=batch_prio.first;
            this->priority=batch_prio.second;
        }
 
 
        void print_me(std::string s="") const override {
            print("this is task",get_name(),"with batch", task.batch,"priority",this->get_priority());
        }
 
        void print_me_as_table(std::string s="") const override {
            std::stringstream ss;
            std::string name=get_name();
            std::size_t namesize=std::min(std::size_t(28),name.size());
            name += std::string(28-namesize,' ');
 
            std::stringstream ssbatch;
            ssbatch << task.batch;
            std::string strbatch=ssbatch.str();
            int nspaces=std::max(int(0),35-int(ssbatch.str().size()));
            strbatch+=std::string(nspaces,' ');
 
            ss  << name
                << std::setw(10) << strbatch
                << this->print_priority_and_status_to_string();
            print(ss.str());
        }
 
        /// loop over the tuple elements of both tuples and execute the operation op on each element pair
        template<typename tupleT, typename tupleR, typename opT, std::size_t I=0>
        void binary_tuple_loop(tupleT& tuple1, tupleR& tuple2, opT& op) const {
            if constexpr(I < std::tuple_size_v<tupleT>) {
                auto& element1=std::get<I>(tuple1);
                auto& element2=std::get<I>(tuple2);
                op(element1,element2);
                binary_tuple_loop<tupleT, tupleR, opT, I+1>(tuple1,tuple2,op);
            }
        }
 
        template<typename tupleT, typename opT, std::size_t I=0>
        void unary_tuple_loop(tupleT& tuple, opT& op) const {
            if constexpr(I < std::tuple_size_v<tupleT>) {
                auto& element1=std::get<I>(tuple);
                op(element1);
                unary_tuple_loop<tupleT,opT, I+1>(tuple,op);
            }
        }
 
        /// accumulate the result of the task into the final result living in the universe
        template<typename resultT1, std::size_t I=0>
        typename std::enable_if<is_tuple<resultT1>::value, void>::type
        accumulate_into_final_result(World &subworld, resultT1 &final_result, const resultT1 &tmp_result, const argtupleT& argtuple) {
            if constexpr(I < std::tuple_size_v<resultT1>) {
                using elementT = typename std::tuple_element<I, resultT>::type;// use decay types for determining a vector
                auto element_final=std::get<I>(final_result);
                auto element_tmp=std::get<I>(tmp_result);
                accumulate_into_final_result<elementT>(subworld, element_final, element_tmp, argtuple);
                accumulate_into_final_result<resultT1,I+1>(subworld, final_result, tmp_result, argtuple);
            }
        }
 
        /// accumulate the result of the task into the final result living in the universe
        template<typename resultT1>
        typename std::enable_if<not is_tuple<resultT1>::value, void>::type
        accumulate_into_final_result(World &subworld, resultT1 &result, const resultT1 &result_tmp, const argtupleT& argtuple) {
                if constexpr (is_madness_function<resultT1>::value) {
                    // gaxpy can be done in reconstructed or compressed mode
                    TreeState operating_state=result_tmp.get_impl()->get_tensor_type()==TT_FULL ? compressed : reconstructed;
                    result_tmp.change_tree_state(operating_state);
                    gaxpy(1.0,result,1.0, result_tmp);
                } else if constexpr(is_madness_function_vector<resultT1>::value) {
                    TreeState operating_state=result_tmp[0].get_impl()->get_tensor_type()==TT_FULL ? compressed : reconstructed;
                    change_tree_state(result_tmp,operating_state);
                    // compress(subworld, result_tmp);
                    // resultT1 tmp1=task.allocator(subworld,argtuple);
                    // tmp1=task.batch.template insert_result_batch(tmp1,result_tmp);
                    gaxpy(1.0,result,1.0,result_tmp,false);
                    // was using operator+=, but this requires a fence, which is not allowed here..
                    // result += tmp1;
                } else if constexpr (is_scalar_result<resultT1>::value) {
                    gaxpy(1.0, result, 1.0, result_tmp.get_local(), false);
                } else if constexpr (is_scalar_result_vector<resultT1>::value) {
                    // resultT1 tmp1=task.allocator(subworld,argtuple);
                    // tmp1=task.batch.template insert_result_batch(tmp1,result_tmp);
                    std::size_t sz=result.size();
                    for (int i=0; i<sz; ++i) {
                        gaxpy(1.0, result[i], 1.0, result_tmp[i].get_local(), false);
                    }
                }
 
        }
 
 
        void run(World &subworld, Cloud &cloud, MacroTaskBase::taskqT &taskq, const long element, const bool debug) override {
            io_redirect io(element,get_name()+"_task",debug);
            const argtupleT argtuple = cloud.load<argtupleT>(subworld, inputrecords);
            const argtupleT batched_argtuple = task.batch.template copy_input_batch(argtuple);
            try {
                print("starting task no",element, ", '",get_name(),"', in subworld",subworld.id(),"at time",wall_time());
                double cpu0=cpu_time();
                resultT result_batch = std::apply(task, batched_argtuple);      // lives in the subworld, is a batch of the full vector (if applicable)
                double cpu1=cpu_time();
                constexpr std::size_t bufsize=256;
                char buffer[bufsize];
                std::snprintf(buffer,bufsize,"completed task %3ld after %6.1fs at time %6.1fs\n",element,cpu1-cpu0,wall_time());
                print(std::string(buffer));
 
                // move the result from the batch to the final result, all still in subworld
                auto insert_batch = [&](auto& element1, auto& element2) {
                    typedef std::decay_t<decltype(element1)> decay_type;;
                    if constexpr (is_vector<decay_type>::value) {
                        element1=task.batch.template insert_result_batch(element1,element2);
                    } else {
                        std::swap(element1,element2);
                    }
                };
                resultT result_subworld=task.allocator(subworld,argtuple);
                if constexpr (is_tuple<resultT>::value) {
                    binary_tuple_loop(result_subworld, result_batch, insert_batch);
                } else {
                    insert_batch(result_subworld,result_batch);
                }
 
                // accumulate the subworld-local results into the final, universe result
                resultT result_universe=get_output(subworld, cloud);       // lives in the universe
 
                accumulate_into_final_result<resultT>(subworld, result_universe, result_subworld, argtuple);
 
            } catch (std::exception& e) {
                print("failing task no",element,"in subworld",subworld.id(),"at time",wall_time());
                print(e.what());
                print_me_as_table();
                print("\n\n");
                MADNESS_EXCEPTION("failing task",1);
            }
 
        };
 
        // this is called after all tasks have been executed and the taskq has ended
        void cleanup() override {
                // resultT result_universe=get_output(subworld, cloud);       // lives in the universe
 
        }
 
        template<typename T, std::size_t NDIM>
        static Function<T,NDIM> pointer2WorldObject(const std::shared_ptr<FunctionImpl<T,NDIM>> impl) {
            Function<T,NDIM> result;
            result.set_impl(impl);
            return result;
        }
 
        template<typename T, std::size_t NDIM>
        static std::vector<Function<T,NDIM>> pointer2WorldObject(const std::vector<std::shared_ptr<FunctionImpl<T,NDIM>>> v_impl) {
            std::vector<Function<T,NDIM>> vresult;
            vresult.resize(v_impl.size());
            set_impl(vresult,v_impl);
            return vresult;
        }
 
        template<typename T>
        static ScalarResult<T> pointer2WorldObject(const std::shared_ptr<ScalarResultImpl<T>> sr_impl) {
            return ScalarResult(sr_impl);
        }
 
        template<typename T>
        static std::vector<ScalarResult<T>> pointer2WorldObject(const std::vector<std::shared_ptr<ScalarResultImpl<T>>> v_sr_impl) {
            std::vector<ScalarResult<T>> vresult(v_sr_impl.size());
            for (auto i=0; i<v_sr_impl.size(); ++i) {
                vresult[i].set_impl(v_sr_impl[i]);
            }
            return vresult;
        }
 
        /// return the WorldObjects or the result functions living in the universe
 
        /// read the pointers to the universe WorldObjects from the cloud,
        /// convert them to actual WorldObjects and return them
        resultT get_output(World &subworld, Cloud &cloud) {
            resultT result;
 
            // save outputrecords, because they will be consumed by the cloud
            auto outputrecords1 = this->outputrecords;
 
            // turn an element of the tuple of pointers into an element of the tuple of WorldObjects
            auto doit = [&](auto& element) {
                typedef std::decay_t<decltype(element)> elementT;
 
                // load the elements from the cloud -- they contain pointers to WorldObjects
                if constexpr (is_madness_function_vector<elementT>::value) {
                    typedef typename elementT::value_type::implT implT;
                    auto ptr_element = cloud.consuming_load<std::vector<std::shared_ptr<implT>>>(
                        subworld, outputrecords1);
                    element = pointer2WorldObject(ptr_element);
                }
                else if constexpr (is_madness_function<elementT>::value) {
                    typedef typename elementT::implT implT;
                    auto ptr_element = cloud.consuming_load<std::shared_ptr<implT>>(subworld, outputrecords1);
                    element = pointer2WorldObject(ptr_element);
                }
                else if constexpr (is_scalar_result_vector<elementT>::value) {  // std::vector<ScalarResult<T>>
                    typedef typename elementT::value_type ScalarResultT;
                    typedef typename ScalarResultT::implT implT;
                    typedef std::vector<std::shared_ptr<implT>> vptrT;
                    auto ptr_element = cloud.consuming_load<vptrT>(subworld, outputrecords1);
                    element = pointer2WorldObject(ptr_element);
                }
                else if constexpr (is_scalar_result<elementT>::value) {
                    // elementT is a ScalarResultImpl<T>
                    // in cloud we store a std::shared_ptr<ScalarResultImpl<T>>
                    auto ptr_element = cloud.consuming_load<std::shared_ptr<typename elementT::implT>>(subworld, outputrecords1);
                    element = pointer2WorldObject(ptr_element);
                }
                else {
                    MADNESS_EXCEPTION("confused about the type of the result", 1);
                }
            };
            if constexpr (is_tuple<resultT>::value) {
                static_assert(check_tuple_is_valid_task_result<resultT, 0>(),
                              "invalid tuple task result -- must be vectors of functions");
                static_assert(is_tuple<resultT>::value, "is a tuple");
 
                // loop over all tuple elements
                //  1. load the pointers to the WorldObjects living in the universe
                //  2. create WorldObjects from the pointers and copy them into the tuple of type resultT
 
                // turn the tuple of pointers into a tuple of WorldObjects
                unary_tuple_loop(result,doit);
 
 
            } else {
                doit(result);
 
            }
            return result;
        }
 
    };
 
};
 
class MacroTaskOperationBase {
public:
    Batch batch;
    std::string name="unknown_task";
    std::shared_ptr<MacroTaskPartitioner> partitioner=0;
    MacroTaskOperationBase() : batch(Batch(_, _, _)), partitioner(new MacroTaskPartitioner) {}
};
 
 
} /* namespace madness */
 
#endif /* SRC_MADNESS_MRA_MACROTASKQ_H_ */