exchangeoperator.h

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#ifndef SRC_APPS_CHEM_EXCHANGEOPERATOR_H_
#define SRC_APPS_CHEM_EXCHANGEOPERATOR_H_
 
#include<madness.h>
#include<madness/world/cloud.h>
#include<madness/mra/macrotaskq.h>
#include<madness/chem/SCFOperators.h>
 
namespace madness {
 
// forward declaration
class SCF;
class Nemo;
 
 
template<typename T, std::size_t NDIM>
class Exchange<T,NDIM>::ExchangeImpl {
    typedef Function<T, NDIM> functionT;
    typedef std::vector<functionT> vecfuncT;
 
    static inline std::atomic<long> apply_timer;
    static inline std::atomic<long> mul2_timer;
    static inline std::atomic<long> mul1_timer; ///< timing
 
    static void reset_timer() {
        mul1_timer = 0l;
        mul2_timer = 0l;
        apply_timer = 0l;
    }
 
    static void print_timer(World& world) {
        double t1 = double(mul1_timer) * 0.001;
        double t2 = double(apply_timer) * 0.001;
        double t3 = double(mul2_timer) * 0.001;
        world.gop.sum(t1);
        world.gop.sum(t2);
        world.gop.sum(t3);
        if (world.rank() == 0) {
            printf(" cpu time spent in multiply1   %8.2fs\n", t1);
            printf(" cpu time spent in apply       %8.2fs\n", t2);
            printf(" cpu time spent in multiply2   %8.2fs\n", t3);
        }
    }
 
public:
 
    typedef Exchange<T,NDIM>::Algorithm Algorithm;
    Algorithm algorithm_ = multiworld_efficient;
 
    /// default ctor
    ExchangeImpl(World& world, const double lo, const double thresh) : world(world), lo(lo), thresh(thresh) {}
 
    /// ctor with a conventional calculation
    ExchangeImpl(World& world, const SCF *calc, const int ispin) ;
 
    /// ctor with a nemo calculation
    ExchangeImpl(World& world, const Nemo *nemo, const int ispin);
 
    /// set the bra and ket orbital spaces, and the occupation
 
    /// @param[in]  bra     bra space, must be provided as complex conjugate
    /// @param[in]  ket     ket space
    void set_bra_and_ket(const vecfuncT& bra, const vecfuncT& ket) {
        mo_bra = copy(world, bra);
        mo_ket = copy(world, ket);
    }
 
    std::string info() const {return "K";}
 
    static auto set_poisson(World& world, const double lo, const double econv = FunctionDefaults<3>::get_thresh()) {
        return std::shared_ptr<real_convolution_3d>(CoulombOperatorPtr(world, lo, econv));
    }
 
    /// apply the exchange operator on a vector of functions
 
    /// note that only one spin is used (either alpha or beta orbitals)
    /// @param[in]  vket       the orbitals |i> that the operator is applied on
    /// @return     a vector of orbitals  K| i>
    vecfuncT operator()(const vecfuncT& vket) const;
 
    bool is_symmetric() const { return symmetric_; }
 
    ExchangeImpl& set_taskq(std::shared_ptr<MacroTaskQ> taskq1) {
        this->taskq=taskq1;
        return *this;
    }
 
    ExchangeImpl& symmetric(const bool flag) {
        symmetric_ = flag;
        return *this;
    }
 
    ExchangeImpl& set_algorithm(const Algorithm& alg) {
        algorithm_ = alg;
        return *this;
    }
 
    ExchangeImpl& set_printlevel(const long& level) {
        printlevel=level;
        return *this;
    }
 
private:
 
    /// exchange using macrotasks, i.e. apply K on a function in individual worlds
    vecfuncT K_macrotask_efficient(const vecfuncT& vket, const double mul_tol = 0.0) const;
 
    /// computing the full square of the double sum (over vket and the K orbitals)
    vecfuncT K_small_memory(const vecfuncT& vket, const double mul_tol = 0.0) const;
 
    /// computing the upper triangle of the double sum (over vket and the K orbitals)
    vecfuncT K_large_memory(const vecfuncT& vket, const double mul_tol = 0.0) const;
 
    /// computing the upper triangle of the double sum (over vket and the K orbitals)
    static vecfuncT compute_K_tile(World& world, const vecfuncT& mo_bra, const vecfuncT& mo_ket,
                                   const vecfuncT& vket, std::shared_ptr<real_convolution_3d> poisson,
                                   const bool symmetric, const double mul_tol = 0.0);
 
    inline bool do_print_timings() const { return (world.rank() == 0) and (printlevel >= 3); }
 
    inline bool printdebug() const {return printlevel >= 10; }
 
    World& world;
    std::shared_ptr<MacroTaskQ> taskq;
    bool symmetric_ = false;      /// is the exchange matrix symmetric? K phi_i = \sum_k \phi_k \int \phi_k \phi_i
    vecfuncT mo_bra, mo_ket;    ///< MOs for bra and ket
    double lo = 1.e-4;
    double thresh = FunctionDefaults<NDIM>::get_thresh();
    long printlevel = 0;
    double mul_tol = 0.0;
 
    class MacroTaskExchangeSimple : public MacroTaskOperationBase {
 
        long nresult;
        double lo = 1.e-4;
        double mul_tol = 1.e-7;
        bool symmetric = false;
 
        /// custom partitioning for the exchange operator in exchangeoperator.h
 
        /// arguments are: result[i] += sum_k vket[k] \int 1/r vbra[k] f[i]
        /// with f and vbra being batched, result and vket being passed on as a whole
        class MacroTaskPartitionerExchange : public MacroTaskPartitioner {
        public:
            MacroTaskPartitionerExchange(const bool symmetric) : symmetric(symmetric) {
                max_batch_size=30;
            }
 
            bool symmetric = false;
 
            partitionT do_partitioning(const std::size_t& vsize1, const std::size_t& vsize2,
                                       const std::string policy) const override {
 
                partitionT partition1 = do_1d_partition(vsize1, policy);
                partitionT partition2 = do_1d_partition(vsize2, policy);
                partitionT result;
                for (auto i = partition1.begin(); i != partition1.end(); ++i) {
                    if (symmetric) {
                        for (auto j = i; j != partition1.end(); ++j) {
                            Batch batch(i->first.input[0], j->first.input[0], _);
                            double priority=compute_priority(batch);
                            result.push_back(std::make_pair(batch,priority));
                        }
                    } else {
                        for (auto j = partition2.begin(); j != partition2.end(); ++j) {
                            Batch batch(i->first.input[0], j->first.input[0], _);
                            double priority=compute_priority(batch);
                            result.push_back(std::make_pair(batch,priority));
                        }
                    }
                }
                return result;
            }
 
            /// compute the priority of this task for non-dumb scheduling
 
            /// \return the priority as double number (no limits)
            double compute_priority(const Batch& batch) const override {
                MADNESS_CHECK(batch.input.size() == 2);   // must be quadratic batches
                long nrow = batch.input[0].size();
                long ncol = batch.input[1].size();
                return double(nrow * ncol);
            }
        };
 
    public:
        MacroTaskExchangeSimple(const long nresult, const double lo, const double mul_tol, const bool symmetric)
                : nresult(nresult), lo(lo), mul_tol(mul_tol), symmetric(symmetric) {
            partitioner.reset(new MacroTaskPartitionerExchange(symmetric));
        }
 
 
        // you need to define the exact argument(s) of operator() as tuple
        typedef std::tuple<const std::vector<Function<T, NDIM>>&,
                const std::vector<Function<T, NDIM>>&,
                const std::vector<Function<T, NDIM>>&> argtupleT;
 
        using resultT = std::vector<Function<T, NDIM>>;
 
        // you need to define an empty constructor for the result
        // resultT must implement operator+=(const resultT&)
        resultT allocator(World& world, const argtupleT& argtuple) const {
            std::size_t n = std::get<0>(argtuple).size();
            resultT result = zero_functions_compressed<T, NDIM>(world, n);
            return result;
        }
 
        std::vector<Function<T, NDIM>>
        operator()(const std::vector<Function<T, NDIM>>& vf_batch,     // will be batched (column)
                   const std::vector<Function<T, NDIM>>& bra_batch,    // will be batched (row)
                   const std::vector<Function<T, NDIM>>& vket) {       // will not be batched
 
            World& world = vf_batch.front().world();
            resultT Kf = zero_functions_compressed<T, NDIM>(world, nresult);
 
            bool diagonal_block = batch.input[0] == batch.input[1];
            auto& bra_range = batch.input[1];    // corresponds to vbra
            auto& vf_range = batch.input[0];       // corresponds to vf_batch
 
            if (vf_range.is_full_size()) vf_range.end = vf_batch.size();
            if (bra_range.is_full_size()) bra_range.end = bra_batch.size();
 
            MADNESS_CHECK(vf_range.end <= nresult);
            if (symmetric) MADNESS_CHECK(bra_range.end <= nresult);
 
            if (symmetric and diagonal_block) {
                auto ket_batch = bra_range.copy_batch(vket);
                vecfuncT resultcolumn = compute_diagonal_batch_in_symmetric_matrix(world, ket_batch, bra_batch,
                                                                                   vf_batch);
 
                for (int i = vf_range.begin; i < vf_range.end; ++i)
                    Kf[i] += resultcolumn[i - vf_range.begin];
 
            } else if (symmetric and not diagonal_block) {
                auto[resultcolumn, resultrow]=compute_offdiagonal_batch_in_symmetric_matrix(world, vket, bra_batch,
                                                                                            vf_batch);
 
                for (int i = bra_range.begin; i < bra_range.end; ++i)
                    Kf[i] += resultcolumn[i - bra_range.begin];
                for (int i = vf_range.begin; i < vf_range.end; ++i)
                    Kf[i] += resultrow[i - vf_range.begin];
            } else {
                auto ket_batch = bra_range.copy_batch(vket);
                vecfuncT resultcolumn = compute_batch_in_asymmetric_matrix(world, ket_batch, bra_batch, vf_batch);
                for (int i = vf_range.begin; i < vf_range.end; ++i)
                    Kf[i] += resultcolumn[i - vf_range.begin];
            }
            return Kf;
        }
 
        /// compute a batch of the exchange matrix, with identical ranges, exploiting the matrix symmetry
 
        /// \param subworld     the world we're computing in
        /// \param cloud        where to store the results
        /// \param bra_batch    the bra batch of orbitals (including the nuclear correlation factor square)
        /// \param ket_batch    the ket batch of orbitals, i.e. the orbitals to premultiply with
        /// \param vf_batch     the argument of the exchange operator
        vecfuncT compute_diagonal_batch_in_symmetric_matrix(World& subworld,
                                                            const vecfuncT& ket_batch,      // is batched
                                                            const vecfuncT& bra_batch,      // is batched
                                                            const vecfuncT& vf_batch        // is batched
        ) const {
            double mul_tol = 0.0;
            double symmetric = true;
            auto poisson = Exchange<double, 3>::ExchangeImpl::set_poisson(subworld, lo);
            return Exchange<T, NDIM>::ExchangeImpl::compute_K_tile(subworld, bra_batch, ket_batch, vf_batch, poisson, symmetric,
                                                     mul_tol);
        }
 
        /// compute a batch of the exchange matrix, with non-identical ranges
 
        /// \param subworld     the world we're computing in
        /// \param cloud        where to store the results
        /// \param bra_batch    the bra batch of orbitals (including the nuclear correlation factor square)
        /// \param ket_batch    the ket batch of orbitals, i.e. the orbitals to premultiply with
        /// \param vf_batch     the argument of the exchange operator
        vecfuncT compute_batch_in_asymmetric_matrix(World& subworld,
                                                    const vecfuncT& ket_batch,
                                                    const vecfuncT& bra_batch,
                                                    const vecfuncT& vf_batch) const {
            double mul_tol = 0.0;
            double symmetric = false;
            auto poisson = Exchange<double, 3>::ExchangeImpl::set_poisson(subworld, lo);
            return Exchange<T, NDIM>::ExchangeImpl::compute_K_tile(subworld, bra_batch, ket_batch, vf_batch, poisson, symmetric,
                                                     mul_tol);
        }
 
        /// compute a batch of the exchange matrix, with non-identical ranges
 
        /// \param subworld     the world we're computing in
        /// \param cloud        where to store the results
        /// \param bra_batch    the bra batch of orbitals (including the nuclear correlation factor square)
        /// \param ket_batch    the ket batch of orbitals, i.e. the orbitals to premultiply with
        /// \param vf_batch     the argument of the exchange operator
        std::pair<vecfuncT, vecfuncT> compute_offdiagonal_batch_in_symmetric_matrix(World& subworld,
                                                                                    const vecfuncT& ket, // not batched
                                                                                    const vecfuncT& bra_batch, // batched
                                                                                    const vecfuncT& vf_batch) const; // batched
 
    };
 
};
 
} /* namespace madness */
 
#endif /* SRC_APPS_CHEM_EXCHANGEOPERATOR_H_ */