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monofonIC/include/grid_fft.hh
Oliver Hahn 80244b8b04 added more elegant Hessian convolution function
2019-05-12 18:28:37 +02:00

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#pragma once
#include <cmath>
#include <array>
#include <vector>
#include <vec3.hh>
#include <general.hh>
#include <bounding_box.hh>
enum space_t
{
kspace_id,
rspace_id
};
template< typename data_t >
class Grid_FFT;
template <typename array_type>
int get_task(ptrdiff_t index, const array_type &offsets, const array_type& sizes,
const int ntasks )
{
int itask = 0;
while (itask < ntasks - 1 && offsets[itask + 1] <= index)
++itask;
return itask;
}
// template <typename data_t, typename operator_t>
// void unpad(const Grid_FFT<data_t> &fp, Grid_FFT<data_t> &f, operator_t op );
template <typename data_t>
void pad_insert(const Grid_FFT<data_t> &f, Grid_FFT<data_t> &fp);
template <typename kdep_functor, typename data_t>
void pad_insertf( kdep_functor kfunc, Grid_FFT<data_t> &fp ){
assert( fp.space_ == kspace_id );
size_t dn[3] = {
fp.n_[0]/3,// fp.n_[0] - f.n_[0],
fp.n_[1]/3,// fp.n_[1] - f.n_[1],
fp.n_[2]/3// fp.n_[2] - f.n_[2],
};
const double rfac = std::pow(1.5,1.5);//std::sqrt(fp.n_[0] * fp.n_[1] * fp.n_[2]) / std::sqrt(f.n_[0] * f.n_[1] * f.n_[2]);
fp.zero();
#if !defined(USE_MPI) ////////////////////////////////////////////////////////////////////////////////////
//size_t nhalf[3] = {f.n_[0] / 2, f.n_[1] / 2, f.n_[2] / 2};
size_t nhalf[3] = {fp.n_[0] / 3, fp.n_[1] / 3, fp.n_[2] / 3};
for (size_t i = 0; i < 2*fp.size(0)/3; ++i)
{
size_t ip = (i > nhalf[0]) ? i + dn[0] : i;
for (size_t j = 0; j < 2*fp.size(1)/3; ++j)
{
size_t jp = (j > nhalf[1]) ? j + dn[1] : j;
for (size_t k = 0; k < 2*fp.size(2)/3; ++k)
{
size_t kp = (k > nhalf[2]) ? k + dn[2] : k;
// if( i==nhalf[0]||j==nhalf[1]||k==nhalf[2]) continue;
//fp.kelem(ip, jp, kp) = f.kelem(i, j, k) * rfac;
fp.kelem(ip, jp, kp) = kfunc(i, j, k) * rfac;
}
}
}
#else /// then USE_MPI is defined ////////////////////////////////////////////////////////////
throw std::runtime_error("need to implement buffering before sending for MPI");
MPI_Barrier(MPI_COMM_WORLD);
/////////////////////////////////////////////////////////////////////
size_t maxslicesz = fp.sizes_[1] * fp.sizes_[3] * 2;
std::vector<ccomplex_t> crecvbuf_(maxslicesz / 2, 0);
real_t *recvbuf_ = reinterpret_cast<real_t *>(&crecvbuf_[0]);
std::vector<ptrdiff_t>
offsets_(CONFIG::MPI_task_size, 0),
offsetsp_(CONFIG::MPI_task_size, 0),
sizes_(CONFIG::MPI_task_size, 0),
sizesp_(CONFIG::MPI_task_size, 0);
size_t tsize = f.size(0), tsizep = fp.size(0);
MPI_Allgather(&f.local_1_start_, 1, MPI_LONG_LONG, &offsets_[0], 1,
MPI_LONG_LONG, MPI_COMM_WORLD);
MPI_Allgather(&fp.local_1_start_, 1, MPI_LONG_LONG, &offsetsp_[0], 1,
MPI_LONG_LONG, MPI_COMM_WORLD);
MPI_Allgather(&tsize, 1, MPI_LONG_LONG, &sizes_[0], 1, MPI_LONG_LONG,
MPI_COMM_WORLD);
MPI_Allgather(&tsizep, 1, MPI_LONG_LONG, &sizesp_[0], 1, MPI_LONG_LONG,
MPI_COMM_WORLD);
/////////////////////////////////////////////////////////////////////
double tstart = get_wtime();
csoca::dlog << "[MPI] Started scatter for convolution" << std::endl;
//... collect offsets
assert(f.space_ == kspace_id);
size_t nf[3] = {f.size(0), f.size(1), f.size(2)};
size_t nfp[3] = {fp.size(0), fp.size(1), fp.size(2)};
size_t fny[3] = {f.n_[1] / 2, f.n_[0] / 2, f.n_[2] / 2};
//... local size must be divisible by 2, otherwise this gets too complicated
assert(f.n_[1] % 2 == 0);
size_t slicesz = f.size(1) * f.size(3); //*2;
// comunicate
if (typeid(data_t) == typeid(real_t))
slicesz *= 2; // then sizeof(real_t) gives only half of a complex
MPI_Datatype datatype =
(typeid(data_t) == typeid(float))
? MPI_FLOAT
: (typeid(data_t) == typeid(double))
? MPI_DOUBLE
: (typeid(data_t) == typeid(std::complex<float>))
? MPI_COMPLEX
: (typeid(data_t) == typeid(std::complex<double>))
? MPI_DOUBLE_COMPLEX
: MPI_INT;
MPI_Status status;
std::vector<MPI_Request> req;
MPI_Request temp_req;
for (size_t i = 0; i < nf[0]; ++i)
{
size_t iglobal = i + offsets_[CONFIG::MPI_task_rank];
if (iglobal < fny[0])
{
int sendto = get_task(iglobal, offsetsp_, sizesp_, CONFIG::MPI_task_size);
MPI_Isend(&f.kelem(i * slicesz), (int)slicesz, datatype, sendto,
(int)iglobal, MPI_COMM_WORLD, &temp_req);
req.push_back(temp_req);
// ofs << "task " << CONFIG::MPI_task_rank << " : added request No" << req.size()-1 << ":
// Isend #" << iglobal << " to task " << sendto << std::endl;
}
if (iglobal > fny[0])
{
int sendto = get_task(iglobal + fny[0], offsetsp_, sizesp_, CONFIG::MPI_task_size);
MPI_Isend(&f.kelem(i * slicesz), (int)slicesz, datatype, sendto,
(int)(iglobal + fny[0]), MPI_COMM_WORLD, &temp_req);
req.push_back(temp_req);
// ofs << "task " << CONFIG::MPI_task_rank << " : added request No" << req.size()-1 << ":
// Isend #" << iglobal+fny[0] << " to task " << sendto << std::endl;
}
}
for (size_t i = 0; i < nfp[0]; ++i)
{
size_t iglobal = i + offsetsp_[CONFIG::MPI_task_rank];
if (iglobal < fny[0] || iglobal > 2 * fny[0])
{
int recvfrom = 0;
if (iglobal <= fny[0])
recvfrom = get_task(iglobal, offsets_, sizes_, CONFIG::MPI_task_size);
else
recvfrom = get_task(iglobal - fny[0], offsets_, sizes_, CONFIG::MPI_task_size);
// ofs << "task " << CONFIG::MPI_task_rank << " : receive #" << iglobal << " from task "
// << recvfrom << std::endl;
MPI_Recv(&recvbuf_[0], (int)slicesz, datatype, recvfrom, (int)iglobal,
MPI_COMM_WORLD, &status);
// ofs << "---> ok! " << (bool)(status.Get_error()==MPI::SUCCESS) <<
// std::endl;
assert(status.MPI_ERROR == MPI_SUCCESS);
for (size_t j = 0; j < nf[1]; ++j)
{
if (j < fny[1])
{
size_t jp = j;
for (size_t k = 0; k < nf[2]; ++k)
{
// size_t kp = (k>fny[2])? k+fny[2] : k;
if (k < fny[2])
fp.kelem(i, jp, k) = crecvbuf_[j * f.sizes_[3] + k];
else if (k > fny[2])
fp.kelem(i, jp, k + fny[2]) = crecvbuf_[j * f.sizes_[3] + k];
}
}
else if (j > fny[1])
{
size_t jp = j + fny[1];
for (size_t k = 0; k < nf[2]; ++k)
{
// size_t kp = (k>fny[2])? k+fny[2] : k;
// fp.kelem(i,jp,kp) = crecvbuf_[j*f.sizes_[3]+k];
if (k < fny[2])
fp.kelem(i, jp, k) = crecvbuf_[j * f.sizes_[3] + k];
else if (k > fny[2])
fp.kelem(i, jp, k + fny[2]) = crecvbuf_[j * f.sizes_[3] + k];
}
}
}
}
}
for (size_t i = 0; i < req.size(); ++i)
{
// need to set status as wait does not necessarily modify it
// c.f. http://www.open-mpi.org/community/lists/devel/2007/04/1402.php
status.MPI_ERROR = MPI_SUCCESS;
// ofs << "task " << CONFIG::MPI_task_rank << " : checking request No" << i << std::endl;
MPI_Wait(&req[i], &status);
// ofs << "---> ok!" << std::endl;
assert(status.MPI_ERROR == MPI_SUCCESS);
}
// usleep(1000);
MPI_Barrier(MPI_COMM_WORLD);
// std::cerr << ">>>>> task " << CONFIG::MPI_task_rank << " all transfers completed! <<<<<"
// << std::endl; ofs << ">>>>> task " << CONFIG::MPI_task_rank << " all transfers completed!
// <<<<<" << std::endl;
csoca::dlog.Print("[MPI] Completed scatter for convolution, took %fs\n",
get_wtime() - tstart);
#endif /// end of ifdef/ifndef USE_MPI ///////////////////////////////////////////////////////////////
}
template <typename data_t>
class Grid_FFT
{
protected:
#if defined(USE_MPI)
const MPI_Datatype MPI_data_t_type = (typeid(data_t) == typeid(double)) ? MPI_DOUBLE
: (typeid(data_t) == typeid(float)) ? MPI_FLOAT
: (typeid(data_t) == typeid(std::complex<float>)) ? MPI_COMPLEX
: (typeid(data_t) == typeid(std::complex<double>)) ? MPI_DOUBLE_COMPLEX : MPI_INT;
#endif
public:
std::array<size_t, 3> n_, nhalf_;
std::array<size_t, 4> sizes_;
size_t npr_, npc_;
size_t ntot_;
std::array<real_t, 3> length_, kfac_, dx_;
space_t space_;
data_t *data_;
ccomplex_t *cdata_;
bounding_box<size_t> global_range_;
fftw_plan_t plan_, iplan_;
real_t fft_norm_fac_;
ptrdiff_t local_0_start_, local_1_start_;
ptrdiff_t local_0_size_, local_1_size_;
Grid_FFT(const std::array<size_t, 3> &N, const std::array<real_t, 3> &L, space_t initialspace = rspace_id)
: n_(N), length_(L), space_(initialspace), data_(nullptr), cdata_(nullptr) //, RV_(*this), KV_(*this)
{
for (int i = 0; i < 3; ++i)
{
kfac_[i] = 2.0 * M_PI / length_[i];
dx_[i] = length_[i] / n_[i];
}
//invalidated = true;
this->Setup();
}
Grid_FFT(const Grid_FFT<data_t> &g)
: n_(g.n_), length_(g.length_), space_(g.space_), data_(nullptr), cdata_(nullptr)
{
for (int i = 0; i < 3; ++i)
{
kfac_[i] = g.kfac_[i];
dx_[i] = g.dx_[i];
}
//invalidated = true;
this->Setup();
for (size_t i = 0; i < ntot_; ++i)
{
data_[i] = g.data_[i];
}
}
~Grid_FFT()
{
if (data_ != nullptr)
{
fftw_free(data_);
}
}
const Grid_FFT<data_t>* get_grid( size_t ilevel ) const { return this; }
bool is_in_mask( size_t ilevel, size_t i, size_t j, size_t k ) const { return true; }
bool is_refined( size_t ilevel, size_t i, size_t j, size_t k ) const { return false; }
size_t levelmin() const {return 7;}
size_t levelmax() const {return 7;}
void Setup();
size_t size(size_t i) const { return sizes_[i]; }
void zero()
{
for (size_t i = 0; i < ntot_; ++i)
data_[i] = 0.0;
}
data_t &relem(size_t i, size_t j, size_t k)
{
size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
return data_[idx];
}
const data_t &relem(size_t i, size_t j, size_t k) const
{
size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
return data_[idx];
}
ccomplex_t &kelem(size_t i, size_t j, size_t k)
{
size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
return cdata_[idx];
}
const ccomplex_t &kelem(size_t i, size_t j, size_t k) const
{
size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
return cdata_[idx];
}
ccomplex_t &kelem(size_t idx) { return cdata_[idx]; }
const ccomplex_t &kelem(size_t idx) const { return cdata_[idx]; }
data_t &relem(size_t idx) { return data_[idx]; }
const data_t &relem(size_t idx) const { return data_[idx]; }
size_t get_idx(size_t i, size_t j, size_t k) const
{
return (i * sizes_[1] + j) * sizes_[3] + k;
}
template <typename ft>
vec3<ft> get_r(const size_t &i, const size_t &j, const size_t &k) const
{
vec3<ft> rr;
#if defined(USE_MPI)
rr[0] = real_t(i + local_0_start_) * dx_[0];
#else
rr[0] = real_t(i) * dx_[0];
#endif
rr[1] = real_t(j) * dx_[1];
rr[2] = real_t(k) * dx_[2];
return rr;
}
void cell_pos( int ilevel, size_t i, size_t j, size_t k, double* x ) const {
x[0] = double(i)/size(0);
x[1] = double(j)/size(1);
x[2] = double(k)/size(2);
}
size_t count_leaf_cells( int, int ) const {
return n_[0]*n_[1]*n_[2];
}
template <typename ft>
vec3<ft> get_k(const size_t i, const size_t j, const size_t k) const
{
vec3<ft> kk;
#if defined(USE_MPI)
auto ip = i + local_1_start_;
kk[0] = (real_t(j) - real_t(j > nhalf_[0]) * n_[0]) * kfac_[0];
kk[1] = (real_t(ip) - real_t(ip > nhalf_[1]) * n_[1]) * kfac_[1];
#else
kk[0] = (real_t(i) - real_t(i > nhalf_[0]) * n_[0]) * kfac_[0];
kk[1] = (real_t(j) - real_t(j > nhalf_[1]) * n_[1]) * kfac_[1];
#endif
kk[2] = (real_t(k) - real_t(k > nhalf_[2]) * n_[2]) * kfac_[2];
return kk;
}
template <typename functional>
void apply_function_k(const functional &f)
{
#pragma omp parallel for
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
auto &elem = this->kelem(i, j, k);
elem = f(elem);
}
}
}
}
template <typename functional>
void apply_function_r(const functional &f)
{
#pragma omp parallel for
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
auto &elem = this->relem(i, j, k);
elem = f(elem);
}
}
}
}
double compute_2norm(void)
{
real_t sum1{0.0};
#pragma omp parallel for reduction(+ \
: sum1)
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
const auto re = std::real(this->relem(i, j, k));
const auto im = std::imag(this->relem(i, j, k));
sum1 += re * re + im * im;
}
}
}
sum1 /= sizes_[0] * sizes_[1] * sizes_[2];
return sum1;
}
double std(void)
{
real_t sum1{0.0}, sum2{0.0};
#pragma omp parallel for reduction(+ \
: sum1, sum2)
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
const auto elem = std::real(this->relem(i, j, k));
sum1 += elem;
sum2 += elem * elem;
}
}
}
sum1 /= sizes_[0] * sizes_[1] * sizes_[2];
sum2 /= sizes_[0] * sizes_[1] * sizes_[2];
return std::sqrt(sum2 - sum1 * sum1);
}
double mean(void)
{
real_t sum1{0.0};
#pragma omp parallel for reduction(+ \
: sum1)
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
const auto elem = std::real(this->relem(i, j, k));
sum1 += elem;
}
}
}
sum1 /= sizes_[0] * sizes_[1] * sizes_[2];
return sum1;
}
template <typename functional, typename grid_t>
void assign_function_of_grids_r(const functional &f, const grid_t &g)
{
assert(g.size(0) == size(0) && g.size(1) == size(1)); // && g.size(2) == size(2) );
#pragma omp parallel for
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
auto &elem = this->relem(i, j, k);
const auto &elemg = g.relem(i, j, k);
elem = f(elemg);
}
}
}
}
template <typename functional, typename grid1_t, typename grid2_t>
void assign_function_of_grids_r(const functional &f, const grid1_t &g1, const grid2_t &g2)
{
assert(g1.size(0) == size(0) && g1.size(1) == size(1)); // && g1.size(2) == size(2));
assert(g2.size(0) == size(0) && g2.size(1) == size(1)); // && g2.size(2) == size(2));
#pragma omp parallel for
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
//auto idx = this->get_idx(i,j,k);
auto &elem = this->relem(i, j, k);
const auto &elemg1 = g1.relem(i, j, k);
const auto &elemg2 = g2.relem(i, j, k);
elem = f(elemg1, elemg2);
}
}
}
}
template <typename functional, typename grid1_t, typename grid2_t, typename grid3_t>
void assign_function_of_grids_r(const functional &f, const grid1_t &g1, const grid2_t &g2, const grid3_t &g3)
{
assert(g1.size(0) == size(0) && g1.size(1) == size(1)); // && g1.size(2) == size(2));
assert(g2.size(0) == size(0) && g2.size(1) == size(1)); // && g2.size(2) == size(2));
assert(g3.size(0) == size(0) && g3.size(1) == size(1)); // && g3.size(2) == size(2));
#pragma omp parallel for
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
//auto idx = this->get_idx(i,j,k);
auto &elem = this->relem(i, j, k);
const auto &elemg1 = g1.relem(i, j, k);
const auto &elemg2 = g2.relem(i, j, k);
const auto &elemg3 = g3.relem(i, j, k);
elem = f(elemg1, elemg2, elemg3);
}
}
}
}
template <typename functional>
void apply_function_k_dep(const functional &f)
{
#pragma omp parallel for
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
auto &elem = this->kelem(i, j, k);
elem = f(elem, this->get_k<real_t>(i, j, k));
}
}
}
}
template <typename functional>
void apply_function_r_dep(const functional &f)
{
#pragma omp parallel for
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
auto &elem = this->relem(i, j, k);
elem = f(elem, this->get_r<real_t>(i, j, k));
}
}
}
}
void FourierTransformBackward(bool do_transform = true);
void FourierTransformForward(bool do_transform = true);
void ApplyNorm(void);
void FillRandomReal(unsigned long int seed = 123456ul);
void Write_to_HDF5(std::string fname, std::string datasetname);
void ComputePowerSpectrum(std::vector<double> &bin_k, std::vector<double> &bin_P, std::vector<double> &bin_eP, int nbins);
void Compute_PDF(std::string ofname, int nbins = 1000, double scale = 1.0, double rhomin = 1e-3, double rhomax = 1e3);
void zero_DC_mode(void)
{
if( space_ == kspace_id ){
#ifdef USE_MPI
if (CONFIG::MPI_task_rank == 0)
#endif
cdata_[0] = (data_t)0.0;
}else{
data_t sum = 0.0;
//#pragma omp parallel for reduction(+:sum)
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
sum += this->relem(i, j, k);
}
}
}
#if defined(USE_MPI)
data_t glob_sum = 0.0;
MPI_Allreduce(reinterpret_cast<void *>(&sum), reinterpret_cast<void *>(&globsum),
1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);
sum = glob_sum;
#endif
sum /= sizes_[0]*sizes_[1]*sizes_[2];
#pragma omp parallel for
for (size_t i = 0; i < sizes_[0]; ++i)
{
for (size_t j = 0; j < sizes_[1]; ++j)
{
for (size_t k = 0; k < sizes_[2]; ++k)
{
this->relem(i, j, k) -= sum;
}
}
}
}
}
};
template <typename data_t, typename operator_t>
void unpad(const Grid_FFT<data_t> &fp, Grid_FFT<data_t> &f, operator_t op )
{
// assert(fp.n_[0] == 3 * f.n_[0] / 2);
// assert(fp.n_[1] == 3 * f.n_[1] / 2);
// assert(fp.n_[2] == 3 * f.n_[2] / 2);
size_t dn[3] = {
fp.n_[0] - f.n_[0],
fp.n_[1] - f.n_[1],
fp.n_[2] - f.n_[2],
};
const double rfac = std::sqrt(fp.n_[0] * fp.n_[1] * fp.n_[2]) / std::sqrt(f.n_[0] * f.n_[1] * f.n_[2]);
#if !defined(USE_MPI) ////////////////////////////////////////////////////////////////////////////////////
size_t nhalf[3] = {f.n_[0] / 2, f.n_[1] / 2, f.n_[2] / 2};
for (size_t i = 0; i < f.size(0); ++i)
{
size_t ip = (i > nhalf[0]) ? i + dn[0] : i;
for (size_t j = 0; j < f.size(1); ++j)
{
size_t jp = (j > nhalf[1]) ? j + dn[1] : j;
for (size_t k = 0; k < f.size(2); ++k)
{
size_t kp = (k > nhalf[2]) ? k + dn[2] : k;
// if( i==nhalf[0]||j==nhalf[1]||k==nhalf[2]) continue;
f.kelem(i, j, k) = op(fp.kelem(ip, jp, kp) / rfac, f.kelem(i, j, k));
}
}
}
#else /// then USE_MPI is defined //////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////
size_t maxslicesz = fp.sizes_[1] * fp.sizes_[3] * 2;
std::vector<ccomplex_t> crecvbuf_(maxslicesz / 2,0);
real_t* recvbuf_ = reinterpret_cast<real_t *>(&crecvbuf_[0]);
std::vector<ptrdiff_t>
offsets_(CONFIG::MPI_task_size, 0),
offsetsp_(CONFIG::MPI_task_size, 0),
sizes_(CONFIG::MPI_task_size, 0),
sizesp_(CONFIG::MPI_task_size, 0);
size_t tsize = f.size(0), tsizep = fp.size(0);
MPI_Allgather(&f.local_1_start_, 1, MPI_LONG_LONG, &offsets_[0], 1,
MPI_LONG_LONG, MPI_COMM_WORLD);
MPI_Allgather(&fp.local_1_start_, 1, MPI_LONG_LONG, &offsetsp_[0], 1,
MPI_LONG_LONG, MPI_COMM_WORLD);
MPI_Allgather(&tsize, 1, MPI_LONG_LONG, &sizes_[0], 1, MPI_LONG_LONG,
MPI_COMM_WORLD);
MPI_Allgather(&tsizep, 1, MPI_LONG_LONG, &sizesp_[0], 1, MPI_LONG_LONG,
MPI_COMM_WORLD);
/////////////////////////////////////////////////////////////////////
double tstart = get_wtime();
csoca::ilog << "[MPI] Started gather for convolution";
MPI_Barrier(MPI_COMM_WORLD);
size_t nf[3] = {f.size(0), f.size(1), f.size(2)};
size_t nfp[4] = {fp.size(0), fp.size(1), fp.size(2), fp.size(3)};
size_t fny[3] = {f.n_[1] / 2, f.n_[0] / 2, f.n_[2] / 2};
size_t slicesz = fp.size(1) * fp.size(3);
if (typeid(data_t) == typeid(real_t))
slicesz *= 2; // then sizeof(real_t) gives only half of a complex
MPI_Datatype datatype =
(typeid(data_t) == typeid(float))
? MPI_FLOAT
: (typeid(data_t) == typeid(double))
? MPI_DOUBLE
: (typeid(data_t) == typeid(std::complex<float>))
? MPI_COMPLEX
: (typeid(data_t) == typeid(std::complex<double>))
? MPI_DOUBLE_COMPLEX
: MPI_INT;
MPI_Status status;
//... local size must be divisible by 2, otherwise this gets too complicated
// assert( tsize%2 == 0 );
f.zero();
std::vector<MPI_Request> req;
MPI_Request temp_req;
for (size_t i = 0; i < nfp[0]; ++i)
{
size_t iglobal = i + offsetsp_[CONFIG::MPI_task_rank];
//... sending
if (iglobal < fny[0])
{
int sendto = get_task(iglobal, offsets_, sizes_, CONFIG::MPI_task_size);
MPI_Isend(&fp.kelem(i * slicesz), (int)slicesz, datatype, sendto, (int)iglobal,
MPI_COMM_WORLD, &temp_req);
req.push_back(temp_req);
}
else if (iglobal > 2 * fny[0])
{
int sendto = get_task(iglobal - fny[0], offsets_, sizes_, CONFIG::MPI_task_size);
MPI_Isend(&fp.kelem(i * slicesz), (int)slicesz, datatype, sendto, (int)iglobal,
MPI_COMM_WORLD, &temp_req);
req.push_back(temp_req);
}
}
for (size_t i = 0; i < nf[0]; ++i)
{
size_t iglobal = i + offsets_[CONFIG::MPI_task_rank];
int recvfrom = 0;
if (iglobal < fny[0])
{
recvfrom = get_task(iglobal, offsetsp_, sizesp_, CONFIG::MPI_task_size);
MPI_Recv(&recvbuf_[0], (int)slicesz, datatype, recvfrom, (int)iglobal,
MPI_COMM_WORLD, &status);
}
else if (iglobal > fny[0])
{
recvfrom = get_task(iglobal + fny[0], offsetsp_, sizesp_, CONFIG::MPI_task_size);
MPI_Recv(&recvbuf_[0], (int)slicesz, datatype, recvfrom,
(int)(iglobal + fny[0]), MPI_COMM_WORLD, &status);
}
else
continue;
assert(status.MPI_ERROR == MPI_SUCCESS);
for (size_t j = 0; j < nf[1]; ++j)
{
if (j < fny[1])
{
size_t jp = j;
for (size_t k = 0; k < nf[2]; ++k)
{
// size_t kp = (k>fny[2])? k+fny[2] : k;
// f.kelem(i,j,k) = crecvbuf_[jp*nfp[3]+kp];
if (k < fny[2])
f.kelem(i, j, k) = op(crecvbuf_[jp * nfp[3] + k],f.kelem(i, j, k));
else if (k > fny[2])
f.kelem(i, j, k) = op(crecvbuf_[jp * nfp[3] + k + fny[2]], f.kelem(i, j, k));
}
}
if (j > fny[1])
{
size_t jp = j + fny[1];
for (size_t k = 0; k < nf[2]; ++k)
{
// size_t kp = (k>fny[2])? k+fny[2] : k;
// f.kelem(i,j,k) = crecvbuf_[jp*nfp[3]+kp];
if (k < fny[2])
f.kelem(i, j, k) = op(crecvbuf_[jp * nfp[3] + k], f.kelem(i, j, k));
else if (k > fny[2])
f.kelem(i, j, k) = op(crecvbuf_[jp * nfp[3] + k + fny[2]], f.kelem(i, j, k));
}
}
}
}
for (size_t i = 0; i < req.size(); ++i)
{
// need to preset status as wait does not necessarily modify it to reflect
// success c.f.
// http://www.open-mpi.org/community/lists/devel/2007/04/1402.php
status.MPI_ERROR = MPI_SUCCESS;
MPI_Wait(&req[i], &status);
assert(status.MPI_ERROR == MPI_SUCCESS);
}
MPI_Barrier(MPI_COMM_WORLD);
csoca::ilog.Print("[MPI] Completed gather for convolution, took %fs", get_wtime() - tstart);
#endif /// end of ifdef/ifndef USE_MPI //////////////////////////////////////////////////////////////
}
template< typename data_t >
class OrszagConvolver
{
protected:
Grid_FFT<data_t> *f1p_, *f2p_;
std::array<size_t,3> np_;
std::array<real_t,3> length_;
ccomplex_t *crecvbuf_;
real_t *recvbuf_;
ptrdiff_t *offsets_;
ptrdiff_t *offsetsp_;
ptrdiff_t *sizes_;
ptrdiff_t *sizesp_;
private:
int get_task( ptrdiff_t index, const ptrdiff_t *offsets, const ptrdiff_t *sizes, const int ntasks ) const
{
int itask = 0;
while( itask < ntasks-1 && offsets[itask+1] <= index ) ++itask;
return itask;
}
// void pad_insert( const Grid_FFT<data_t> & f, Grid_FFT<data_t> & fp );
// void unpad( const Grid_FFT<data_t> & fp, Grid_FFT< data_t > & f );
public:
OrszagConvolver( const std::array<size_t, 3> &N, const std::array<real_t, 3> &L )
: np_({3*N[0]/2,3*N[1]/2,3*N[2]/2}), length_(L)
{
//... create temporaries
f1p_ = new Grid_FFT<data_t>(np_, length_, kspace_id);
f2p_ = new Grid_FFT<data_t>(np_, length_, kspace_id);
#if defined(USE_MPI)
size_t maxslicesz = f1p_->sizes_[1] * f1p_->sizes_[3] * 2;
crecvbuf_ = new ccomplex_t[maxslicesz / 2];
recvbuf_ = reinterpret_cast<real_t *>(&crecvbuf_[0]);
int ntasks(MPI_Get_size());
offsets_ = new ptrdiff_t[ntasks];
offsetsp_ = new ptrdiff_t[ntasks];
sizes_ = new ptrdiff_t[ntasks];
sizesp_ = new ptrdiff_t[ntasks];
size_t tsize = N[0], tsizep = f1p_->size(0);
MPI_Allgather(&f.local_1_start_, 1, MPI_LONG_LONG, &offsets_[0], 1,
MPI_LONG_LONG, MPI_COMM_WORLD);
MPI_Allgather(&f1p_->local_1_start_, 1, MPI_LONG_LONG, &offsetsp_[0], 1,
MPI_LONG_LONG, MPI_COMM_WORLD);
MPI_Allgather(&tsize, 1, MPI_LONG_LONG, &sizes_[0], 1, MPI_LONG_LONG,
MPI_COMM_WORLD);
MPI_Allgather(&tsizep, 1, MPI_LONG_LONG, &sizesp_[0], 1, MPI_LONG_LONG,
MPI_COMM_WORLD);
#endif
}
~OrszagConvolver()
{
delete f1p_;
delete f2p_;
#if defined(USE_MPI)
delete[] crecvbuf_;
delete[] offsets_;
delete[] offsetsp_;
delete[] sizes_;
delete[] sizesp_;
#endif
}
template< typename opp >
void convolve_Hessians( Grid_FFT<data_t> & inl, const std::array<int,2>& d2l, Grid_FFT<data_t> & inr, const std::array<int,2>& d2r, Grid_FFT<data_t> & res, opp op ){
// transform to FS in case fields are not
inl.FourierTransformForward();
inr.FourierTransformForward();
// perform convolution of Hessians
this->convolve2__(
[&]( size_t i, size_t j, size_t k ) -> ccomplex_t{
auto kk = inl.template get_k<real_t>(i,j,k);
return -kk[d2l[0]] * kk[d2l[1]] * inl.kelem(i,j,k);// / phifac;
},
[&]( size_t i, size_t j, size_t k ){
auto kk = inr.template get_k<real_t>(i,j,k);
return -kk[d2r[0]] * kk[d2r[1]] * inr.kelem(i,j,k);// / phifac;
}, res, op );
}
template< typename kfunc1, typename kfunc2, typename opp >
void convolve2__( kfunc1 kf1, kfunc2 kf2, Grid_FFT<data_t> & res, opp op )
{
//... prepare data 1
f1p_->FourierTransformForward(false);
pad_insertf( kf1, *f1p_ );
//... prepare data 1
f2p_->FourierTransformForward(false);
pad_insertf( kf2, *f2p_ );
//... convolve
f1p_->FourierTransformBackward();
f2p_->FourierTransformBackward();
for (size_t i = 0; i < f1p_->ntot_; ++i){
(*f2p_).relem(i) *= (*f1p_).relem(i);
}
f2p_->FourierTransformForward();
//... copy data back
res.FourierTransformForward();
unpad(*f2p_, res, op);
}
//... inplace interface
template <typename opp>
void convolve2( Grid_FFT<data_t> & f1, Grid_FFT<data_t> & f2, Grid_FFT<data_t> & res, opp op)// = []( ccomplex_t convres, ccomplex_t res ) -> ccomplex_t{ return convres; } )
{
#if 1
// constexpr real_t fac{ std::pow(1.5,1.5) };
constexpr real_t fac{ 1.0 };
//... copy data 1
f1.FourierTransformForward();
f1p_->FourierTransformForward(false);
pad_insert(f1, *f1p_);
//... copy data 2
f2.FourierTransformForward();
f2p_->FourierTransformForward(false);
pad_insert(f2, *f2p_);
//... convolve
f1p_->FourierTransformBackward();
f2p_->FourierTransformBackward();
for (size_t i = 0; i < f1p_->ntot_; ++i){
(*f2p_).relem(i) *= fac * (*f1p_).relem(i);
}
f2p_->FourierTransformForward();
//... copy data back
res.FourierTransformForward();
unpad(*f2p_, res, op);
#else
res.FourierTransformBackward();
f1.FourierTransformBackward();
f2.FourierTransformBackward();
for (size_t i = 0; i < res.ntot_; ++i){
res.relem(i) = op(f1.relem(i)*f2.relem(i),res.relem(i));
}
#endif
}
//... inplace interface
/*void convolve3( const Grid_FFT<data_t> & f1, const Grid_FFT<data_t> & f2, const Grid_FFT<data_t> & f3, Grid_FFT<data_t> & res )
{
convolve2( f1, f2, res );
convolve2( res, f3, res );
}*/
};
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