mirror of
https://github.com/cosmo-sims/monofonIC.git
synced 2024-09-19 17:03:45 +02:00
792 lines
30 KiB
C++
792 lines
30 KiB
C++
#pragma once
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#include <array>
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#include <general.hh>
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#include <grid_fft.hh>
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template< typename data_t, typename derived_t >
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class BaseConvolver
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{
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protected:
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std::array<size_t,3> np_;
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std::array<real_t,3> length_;
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public:
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BaseConvolver( const std::array<size_t, 3> &N, const std::array<real_t, 3> &L )
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: np_( N ), length_( L ) {}
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virtual ~BaseConvolver() {}
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// implements convolution of two Fourier-space fields
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template< typename kfunc1, typename kfunc2, typename opp >
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void convolve2( kfunc1 kf1, kfunc2 kf2, opp op ) {}
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// implements convolution of three Fourier-space fields
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template< typename kfunc1, typename kfunc2, typename kfunc3, typename opp >
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void convolve3( kfunc1 kf1, kfunc2 kf2, kfunc3 kf3, opp op ) {}
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public:
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template< typename opp >
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void convolve_Gradient_and_Hessian( Grid_FFT<data_t> & inl, const std::array<int,1>& d1l,
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Grid_FFT<data_t> & inr, const std::array<int,2>& d2r,
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opp output_op ){
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t&>(*this).convolve2(
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[&]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inl.template get_k<real_t>(i,j,k);
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return ccomplex_t(0.0,kk[d1l[0]]) * inl.kelem(i,j,k);
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},
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[&]( size_t i, size_t j, size_t k ){
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auto kk = inr.template get_k<real_t>(i,j,k);
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return -kk[d2r[0]] * kk[d2r[1]] * inr.kelem(i,j,k);
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}, output_op );
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}
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template< typename opp >
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void convolve_Hessians( Grid_FFT<data_t> & inl, const std::array<int,2>& d2l,
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Grid_FFT<data_t> & inr, const std::array<int,2>& d2r,
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opp output_op ){
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t&>(*this).convolve2(
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[&]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inl.template get_k<real_t>(i,j,k);
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return -kk[d2l[0]] * kk[d2l[1]] * inl.kelem(i,j,k);
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},
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[&]( size_t i, size_t j, size_t k ){
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auto kk = inr.template get_k<real_t>(i,j,k);
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return -kk[d2r[0]] * kk[d2r[1]] * inr.kelem(i,j,k);
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}, output_op );
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}
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template< typename opp >
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void convolve_Hessians( Grid_FFT<data_t> & inl, const std::array<int,2>& d2l,
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Grid_FFT<data_t> & inm, const std::array<int,2>& d2m,
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Grid_FFT<data_t> & inr, const std::array<int,2>& d2r,
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opp output_op )
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inm.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t&>(*this).convolve3(
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[&inl,&d2l]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inl.template get_k<real_t>(i,j,k);
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return -kk[d2l[0]] * kk[d2l[1]] * inl.kelem(i,j,k);
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},
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[&inm,&d2m]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inm.template get_k<real_t>(i,j,k);
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return -kk[d2m[0]] * kk[d2m[1]] * inm.kelem(i,j,k);
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},
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[&inr,&d2r]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inr.template get_k<real_t>(i,j,k);
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return -kk[d2r[0]] * kk[d2r[1]] * inr.kelem(i,j,k);
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}, output_op );
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}
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template< typename opp >
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void convolve_SumOfHessians( Grid_FFT<data_t> & inl, const std::array<int,2>& d2l,
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Grid_FFT<data_t> & inr, const std::array<int,2>& d2r1, const std::array<int,2>& d2r2,
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opp output_op )
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t&>(*this).convolve2(
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[&inl,&d2l]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inl.template get_k<real_t>(i,j,k);
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return -kk[d2l[0]] * kk[d2l[1]] * inl.kelem(i,j,k);
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},
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[&inr,&d2r1,&d2r2]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inr.template get_k<real_t>(i,j,k);
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return (-kk[d2r1[0]] * kk[d2r1[1]] -kk[d2r2[0]] * kk[d2r2[1]]) * inr.kelem(i,j,k);
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}, output_op );
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}
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template< typename opp >
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void convolve_DifferenceOfHessians( Grid_FFT<data_t> & inl, const std::array<int,2>& d2l,
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Grid_FFT<data_t> & inr, const std::array<int,2>& d2r1, const std::array<int,2>& d2r2,
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opp output_op )
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t&>(*this).convolve2(
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[&inl,&d2l]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inl.template get_k<real_t>(i,j,k);
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return -kk[d2l[0]] * kk[d2l[1]] * inl.kelem(i,j,k);
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},
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[&inr,&d2r1,&d2r2]( size_t i, size_t j, size_t k ) -> ccomplex_t{
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auto kk = inr.template get_k<real_t>(i,j,k);
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return (-kk[d2r1[0]] * kk[d2r1[1]] + kk[d2r2[0]] * kk[d2r2[1]]) * inr.kelem(i,j,k);
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}, output_op );
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}
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};
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//! naive convolution class, disrespecting aliasing
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template< typename data_t >
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class NaiveConvolver : public BaseConvolver<data_t, NaiveConvolver<data_t>>
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{
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protected:
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Grid_FFT<data_t> *fbuf1_, *fbuf2_;
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using BaseConvolver<data_t, NaiveConvolver<data_t>>::np_;
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using BaseConvolver<data_t, NaiveConvolver<data_t>>::length_;
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public:
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NaiveConvolver( const std::array<size_t, 3> &N, const std::array<real_t, 3> &L )
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: BaseConvolver<data_t, NaiveConvolver<data_t>>( N, L )
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{
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fbuf1_ = new Grid_FFT<data_t>(N, length_, kspace_id);
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fbuf2_ = new Grid_FFT<data_t>(N, length_, kspace_id);
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}
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~NaiveConvolver()
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{
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delete fbuf1_;
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delete fbuf2_;
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}
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template< typename kfunc1, typename kfunc2, typename opp >
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void convolve2( kfunc1 kf1, kfunc2 kf2, opp output_op )
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{
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//... prepare data 1
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fbuf1_->FourierTransformForward(false);
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this->copy_in( kf1, *fbuf1_ );
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//... prepare data 2
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fbuf2_->FourierTransformForward(false);
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this->copy_in( kf2, *fbuf2_ );
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//... convolve
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fbuf1_->FourierTransformBackward();
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fbuf2_->FourierTransformBackward();
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf1_->ntot_; ++i){
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(*fbuf2_).relem(i) *= (*fbuf1_).relem(i);
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}
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fbuf2_->FourierTransformForward();
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//... copy data back
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf2_->ntot_; ++i ){
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output_op(i,(*fbuf2_)[i]);
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}
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}
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template< typename kfunc1, typename kfunc2, typename kfunc3, typename opp >
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void convolve3( kfunc1 kf1, kfunc2 kf2, kfunc3 kf3, opp output_op )
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{
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//... prepare data 1
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fbuf1_->FourierTransformForward(false);
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this->copy_in( kf1, *fbuf1_ );
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//... prepare data 2
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fbuf2_->FourierTransformForward(false);
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this->copy_in( kf2, *fbuf2_ );
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//... convolve
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fbuf1_->FourierTransformBackward();
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fbuf2_->FourierTransformBackward();
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf1_->ntot_; ++i){
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(*fbuf2_).relem(i) *= (*fbuf1_).relem(i);
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}
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//... prepare data 2
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fbuf1_->FourierTransformForward(false);
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this->copy_in( kf3, *fbuf1_ );
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//... convolve
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fbuf1_->FourierTransformBackward();
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf1_->ntot_; ++i){
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(*fbuf2_).relem(i) *= (*fbuf1_).relem(i);
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}
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fbuf2_->FourierTransformForward();
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//... copy data back
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf2_->ntot_; ++i ){
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output_op(i,(*fbuf2_)[i]);
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}
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}
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private:
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template< typename kfunc >
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void copy_in( kfunc kf, Grid_FFT<data_t>& g )
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{
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#pragma omp parallel for
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for (size_t i = 0; i < g.size(0); ++i){
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for (size_t j = 0; j < g.size(1); ++j){
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for (size_t k = 0; k < g.size(2); ++k){
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g.kelem(i, j, k) = kf(i, j, k);
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}
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}
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}
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}
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};
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//! convolution class, respecting Orszag's 3/2 rule
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template< typename data_t >
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class OrszagConvolver : public BaseConvolver<data_t, OrszagConvolver<data_t>>
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{
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private:
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Grid_FFT<data_t> *f1p_, *f2p_;
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Grid_FFT<data_t> *fbuf_, *fbuf2_;
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using BaseConvolver<data_t, OrszagConvolver<data_t>>::np_;
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using BaseConvolver<data_t, OrszagConvolver<data_t>>::length_;
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ccomplex_t *crecvbuf_;
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real_t *recvbuf_;
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size_t maxslicesz_;
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std::vector<ptrdiff_t> offsets_, offsetsp_;
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std::vector<size_t> sizes_, sizesp_;
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int get_task(ptrdiff_t index, const std::vector<ptrdiff_t>& offsets, const std::vector<size_t>& sizes, const int ntasks )
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{
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int itask = 0;
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while (itask < ntasks - 1 && offsets[itask + 1] <= index) ++itask;
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return itask;
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}
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public:
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OrszagConvolver( const std::array<size_t, 3> &N, const std::array<real_t, 3> &L )
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: BaseConvolver<data_t,OrszagConvolver<data_t>>( {3*N[0]/2,3*N[1]/2,3*N[2]/2}, L )
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//: np_({3*N[0]/2,3*N[1]/2,3*N[2]/2}), length_(L)
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{
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//... create temporaries
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f1p_ = new Grid_FFT<data_t>(np_, length_, kspace_id);
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f2p_ = new Grid_FFT<data_t>(np_, length_, kspace_id);
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fbuf_ = new Grid_FFT<data_t>(N, length_, kspace_id); // needed for MPI, or for triple conv.
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fbuf2_ = new Grid_FFT<data_t>(N, length_, kspace_id); // needed for MPI, or for triple conv.
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#if defined(USE_MPI)
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maxslicesz_ = f1p_->sizes_[1] * f1p_->sizes_[3] * 2;
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crecvbuf_ = new ccomplex_t[maxslicesz_ / 2];
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recvbuf_ = reinterpret_cast<real_t *>(&crecvbuf_[0]);
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int ntasks(MPI_Get_size());
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offsets_.assign(ntasks,0);
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offsetsp_.assign(ntasks,0);
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sizes_.assign(ntasks,0);
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sizesp_.assign(ntasks,0);
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size_t tsize = N[0], tsizep = f1p_->size(0);
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MPI_Allgather(&fbuf_->local_1_start_, 1, MPI_LONG_LONG, &offsets_[0], 1,
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MPI_LONG_LONG, MPI_COMM_WORLD);
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MPI_Allgather(&f1p_->local_1_start_, 1, MPI_LONG_LONG, &offsetsp_[0], 1,
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MPI_LONG_LONG, MPI_COMM_WORLD);
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MPI_Allgather(&tsize, 1, MPI_LONG_LONG, &sizes_[0], 1, MPI_LONG_LONG,
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MPI_COMM_WORLD);
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MPI_Allgather(&tsizep, 1, MPI_LONG_LONG, &sizesp_[0], 1, MPI_LONG_LONG,
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MPI_COMM_WORLD);
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#endif
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}
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~OrszagConvolver()
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{
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delete f1p_;
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delete f2p_;
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delete fbuf_;
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delete fbuf2_;
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#if defined(USE_MPI)
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delete[] crecvbuf_;
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#endif
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}
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template< typename kfunc1, typename kfunc2, typename opp >
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void convolve2( kfunc1 kf1, kfunc2 kf2, opp output_op )
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{
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//... prepare data 1
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f1p_->FourierTransformForward(false);
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this->pad_insert( kf1, *f1p_ );
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//... prepare data 2
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f2p_->FourierTransformForward(false);
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this->pad_insert( kf2, *f2p_ );
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//... convolve
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f1p_->FourierTransformBackward();
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f2p_->FourierTransformBackward();
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#pragma omp parallel for
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for (size_t i = 0; i < f1p_->ntot_; ++i){
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(*f2p_).relem(i) *= (*f1p_).relem(i);
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}
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f2p_->FourierTransformForward();
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//... copy data back
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unpad(*f2p_, output_op);
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}
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template< typename kfunc1, typename kfunc2, typename kfunc3, typename opp >
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void convolve3( kfunc1 kf1, kfunc2 kf2, kfunc3 kf3, opp output_op )
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{
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auto assign_to = [](auto &g){return [&](auto i, auto v){ g[i] = v; };};
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#warning double check if fbuf_ can be used here, or fbuf2, in case remove fbuf2
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fbuf_->FourierTransformForward(false);
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// convolve kf1 and kf2, store result in fbuf_
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convolve2( kf1, kf2, assign_to(*fbuf_) );
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//... prepare data 1
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f1p_->FourierTransformForward(false);
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// pad result from fbuf_ to f1p_, fbuf_ is now unused
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this->pad_insert( [&]( size_t i, size_t j, size_t k )->ccomplex_t{return fbuf_->kelem(i,j,k);}, *f1p_ );
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//... prepare data 2
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f2p_->FourierTransformForward(false);
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this->pad_insert( kf3, *f2p_ );
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//... convolve
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f1p_->FourierTransformBackward();
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f2p_->FourierTransformBackward();
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#pragma omp parallel for
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for (size_t i = 0; i < f1p_->ntot_; ++i){
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(*f2p_).relem(i) *= (*f1p_).relem(i);
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}
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f2p_->FourierTransformForward();
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//... copy data back
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unpad(*f2p_, output_op);
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}
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// template< typename opp >
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// void test_pad_unpad( Grid_FFT<data_t> & in, Grid_FFT<data_t> & res, opp op )
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// {
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// //... prepare data 1
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// f1p_->FourierTransformForward(false);
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// this->pad_insert( [&in]( size_t i, size_t j, size_t k ){return in.kelem(i,j,k);}, *f1p_ );
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// f1p_->FourierTransformBackward();
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// f1p_->FourierTransformForward();
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// res.FourierTransformForward();
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// unpad(*f1p_, res, op);
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// }
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private:
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template <typename kdep_functor>
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void pad_insert( kdep_functor kfunc, Grid_FFT<data_t> &fp ){
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assert( fp.space_ == kspace_id );
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const double rfac = std::pow(1.5,1.5);
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fp.zero();
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#if !defined(USE_MPI) ////////////////////////////////////////////////////////////////////////////////////
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size_t nhalf[3] = {fp.n_[0] / 3, fp.n_[1] / 3, fp.n_[2] / 3};
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#pragma omp parallel for
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for (size_t i = 0; i < 2*fp.size(0)/3; ++i)
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{
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size_t ip = (i > nhalf[0]) ? i + nhalf[0] : i;
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for (size_t j = 0; j < 2*fp.size(1)/3; ++j)
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{
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size_t jp = (j > nhalf[1]) ? j + nhalf[1] : j;
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for (size_t k = 0; k < 2*fp.size(2)/3; ++k)
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{
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size_t kp = (k > nhalf[2]) ? k + nhalf[2] : k;
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// if( i==nhalf[0]||j==nhalf[1]||k==nhalf[2]) continue;
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fp.kelem(ip, jp, kp) = kfunc(i, j, k) * rfac;
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}
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}
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}
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#else /// then USE_MPI is defined ////////////////////////////////////////////////////////////
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MPI_Barrier(MPI_COMM_WORLD);
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fbuf_->FourierTransformForward(false);
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/////////////////////////////////////////////////////////////////////
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double tstart = get_wtime();
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csoca::dlog << "[MPI] Started scatter for convolution" << std::endl;
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//... collect offsets
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assert(fbuf_->space_ == kspace_id);
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size_t nf[3] = {fbuf_->size(0), fbuf_->size(1), fbuf_->size(2)};
|
|
size_t nfp[3] = {fp.size(0), fp.size(1), fp.size(2)};
|
|
size_t fny[3] = {fbuf_->n_[1] / 2, fbuf_->n_[0] / 2, fbuf_->n_[2] / 2};
|
|
|
|
//... local size must be divisible by 2, otherwise this gets too complicated
|
|
assert(fbuf_->n_[1] % 2 == 0);
|
|
size_t slicesz = fbuf_->size(1) * fbuf_->size(3);
|
|
|
|
MPI_Datatype datatype =
|
|
(typeid(data_t) == typeid(float)) ? MPI_COMPLEX :
|
|
(typeid(data_t) == typeid(double)) ? MPI_DOUBLE_COMPLEX : MPI_BYTE;
|
|
|
|
|
|
// fill MPI send buffer with results of kfunc
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < fbuf_->size(0); ++i)
|
|
{
|
|
for (size_t j = 0; j < fbuf_->size(1); ++j)
|
|
{
|
|
for (size_t k = 0; k < fbuf_->size(2); ++k)
|
|
{
|
|
fbuf_->kelem(i, j, k) = kfunc(i, j, k) * rfac;
|
|
}
|
|
}
|
|
}
|
|
|
|
MPI_Status status;
|
|
|
|
std::vector<MPI_Request> req;
|
|
MPI_Request temp_req;
|
|
|
|
// send data from buffer
|
|
for (size_t i = 0; i < nf[0]; ++i)
|
|
{
|
|
size_t iglobal = i + offsets_[CONFIG::MPI_task_rank];
|
|
|
|
if (iglobal <= fny[0] )//fny[0])
|
|
{
|
|
int sendto = get_task(iglobal, offsetsp_, sizesp_, CONFIG::MPI_task_size);
|
|
MPI_Isend(&fbuf_->kelem(i * slicesz), (int)slicesz, datatype, sendto,
|
|
(int)iglobal, MPI_COMM_WORLD, &temp_req);
|
|
req.push_back(temp_req);
|
|
// std::cout << "task " << CONFIG::MPI_task_rank << " : added request No" << req.size()-1 << ": Isend #" << iglobal << " to task " << sendto << ", size = " << slicesz << std::endl;
|
|
}
|
|
if (iglobal >= fny[0]) //fny[0])
|
|
{
|
|
int sendto = get_task(iglobal + fny[0], offsetsp_, sizesp_, CONFIG::MPI_task_size);
|
|
MPI_Isend(&fbuf_->kelem(i * slicesz), (int)slicesz, datatype, sendto,
|
|
(int)(iglobal + fny[0]), MPI_COMM_WORLD, &temp_req);
|
|
req.push_back(temp_req);
|
|
// std::cout << "task " << CONFIG::MPI_task_rank << " : added request No" << req.size()-1 << ": Isend #" << iglobal+fny[0] << " to task " << sendto << ", size = " << slicesz<< 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);
|
|
|
|
// std::cout << "task " << CONFIG::MPI_task_rank << " : receive #" << iglobal << " from task "
|
|
// << recvfrom << ", size = " << slicesz << ", " << crecvbuf_ << ", " << datatype << std::endl;
|
|
status.MPI_ERROR = MPI_SUCCESS;
|
|
|
|
MPI_Recv(&recvbuf_[0], (int)slicesz, datatype, recvfrom, (int)iglobal,
|
|
MPI_COMM_WORLD, &status);
|
|
// std::cout << "---> ok! " << (bool)(status.MPI_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)
|
|
{
|
|
if( typeid(data_t)==typeid(real_t) ){
|
|
fp.kelem(i, jp, k) = crecvbuf_[j * fbuf_->sizes_[3] + k];
|
|
}else{
|
|
if (k <= fny[2])
|
|
fp.kelem(i, jp, k) = crecvbuf_[j * fbuf_->sizes_[3] + k];
|
|
if (k >= fny[2])
|
|
fp.kelem(i, jp, k + nf[2]/2) = crecvbuf_[j * fbuf_->sizes_[3] + k];
|
|
}
|
|
|
|
}
|
|
}
|
|
|
|
if (j >= fny[1])
|
|
{
|
|
size_t jp = j + fny[1];
|
|
for (size_t k = 0; k < nf[2]; ++k)
|
|
{
|
|
if( typeid(data_t)==typeid(real_t) ){
|
|
fp.kelem(i, jp, k) = crecvbuf_[j * fbuf_->sizes_[3] + k];
|
|
}else{
|
|
if (k <= fny[2])
|
|
fp.kelem(i, jp, k) = crecvbuf_[j * fbuf_->sizes_[3] + k];
|
|
if (k >= fny[2])
|
|
fp.kelem(i, jp, k + fny[2]) = crecvbuf_[j * fbuf_->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;
|
|
// std::cout << "task " << CONFIG::MPI_task_rank << " : checking request No" << i << std::endl;
|
|
MPI_Wait(&req[i], &status);
|
|
// std::cout << "---> 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 operator_t>
|
|
void unpad(const Grid_FFT<data_t> &fp, operator_t output_op )
|
|
{
|
|
const double rfac = std::sqrt(fp.n_[0] * fp.n_[1] * fp.n_[2]) / std::sqrt(fbuf_->n_[0] * fbuf_->n_[1] * fbuf_->n_[2]);
|
|
|
|
// make sure we're in Fourier space...
|
|
assert( fp.space_ == kspace_id );
|
|
|
|
|
|
#if !defined(USE_MPI) ////////////////////////////////////////////////////////////////////////////////////
|
|
fbuf_->FourierTransformForward(false);
|
|
size_t nhalf[3] = {fbuf_->n_[0] / 2, fbuf_->n_[1] / 2, fbuf_->n_[2] / 2};
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < fbuf_->size(0); ++i)
|
|
{
|
|
size_t ip = (i > nhalf[0]) ? i + nhalf[0] : i;
|
|
for (size_t j = 0; j < fbuf_->size(1); ++j)
|
|
{
|
|
size_t jp = (j > nhalf[1]) ? j + nhalf[1] : j;
|
|
for (size_t k = 0; k < fbuf_->size(2); ++k)
|
|
{
|
|
size_t kp = (k > nhalf[2]) ? k + nhalf[2] : k;
|
|
// if( i==nhalf[0]||j==nhalf[1]||k==nhalf[2]) continue;
|
|
fbuf_->kelem(i, j, k) = fp.kelem(ip, jp, kp) / rfac;
|
|
}
|
|
}
|
|
}
|
|
|
|
//... copy data back
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < fbuf_->ntot_; ++i ){
|
|
output_op(i,(*fbuf_)[i]);
|
|
}
|
|
|
|
#else /// then USE_MPI is defined //////////////////////////////////////////////////////////////
|
|
|
|
/////////////////////////////////////////////////////////////////////
|
|
|
|
double tstart = get_wtime();
|
|
|
|
csoca::dlog << "[MPI] Started gather for convolution";
|
|
|
|
MPI_Barrier(MPI_COMM_WORLD);
|
|
|
|
size_t nf[3] = {fbuf_->size(0), fbuf_->size(1), fbuf_->size(2)};
|
|
size_t nfp[4] = {fp.size(0), fp.size(1), fp.size(2), fp.size(3)};
|
|
size_t fny[3] = {fbuf_->n_[1] / 2, fbuf_->n_[0] / 2, fbuf_->n_[2] / 2};
|
|
|
|
size_t slicesz = fp.size(1) * fp.size(3);
|
|
|
|
MPI_Datatype datatype =
|
|
(typeid(data_t) == typeid(float)) ? MPI_COMPLEX :
|
|
(typeid(data_t) == typeid(double)) ? MPI_DOUBLE_COMPLEX : MPI_BYTE;
|
|
|
|
MPI_Status status;
|
|
|
|
//... local size must be divisible by 2, otherwise this gets too complicated
|
|
// assert( tsize%2 == 0 );
|
|
|
|
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);
|
|
}
|
|
}
|
|
|
|
fbuf_->zero();
|
|
|
|
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])
|
|
{
|
|
real_t wi = (iglobal == fny[0])? 0.5 : 1.0;
|
|
|
|
recvfrom = get_task(iglobal, offsetsp_, sizesp_, CONFIG::MPI_task_size);
|
|
MPI_Recv(&recvbuf_[0], (int)slicesz, datatype, recvfrom, (int)iglobal,
|
|
MPI_COMM_WORLD, &status);
|
|
|
|
for (size_t j = 0; j < nf[1]; ++j)
|
|
{
|
|
real_t wj = (j==fny[1])? 0.5 : 1.0;
|
|
if (j <= fny[1])
|
|
{
|
|
size_t jp = j;
|
|
for (size_t k = 0; k < nf[2]; ++k)
|
|
{
|
|
if( typeid(data_t)==typeid(real_t) ){
|
|
real_t w = wi*wj;
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k]/rfac;
|
|
}else{
|
|
real_t wk = (k==fny[2])? 0.5 : 1.0;
|
|
real_t w = wi*wj*wk;
|
|
if (k <= fny[2])
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k]/rfac;
|
|
if (k >= fny[2])
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k + fny[2]]/rfac;
|
|
if( w<1.0 ){
|
|
fbuf_->kelem(i, j, k) = std::real(fbuf_->kelem(i, j, k));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
if (j >= fny[1])
|
|
{
|
|
size_t jp = j + fny[1];
|
|
for (size_t k = 0; k < nf[2]; ++k)
|
|
{
|
|
if( typeid(data_t)==typeid(real_t) ){
|
|
real_t w = wi*wj;
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k]/rfac;
|
|
}else{
|
|
real_t wk = (k==fny[2])? 0.5 : 1.0;
|
|
real_t w = wi*wj*wk;
|
|
if (k <= fny[2])
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k]/rfac;
|
|
if (k >= fny[2])
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k + fny[2]]/rfac;
|
|
if( w<1.0 ){
|
|
fbuf_->kelem(i, j, k) = std::real(fbuf_->kelem(i, j, k));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
if (iglobal >= fny[0])
|
|
{
|
|
real_t wi = (iglobal == fny[0])? 0.5 : 1.0;
|
|
|
|
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);
|
|
|
|
for (size_t j = 0; j < nf[1]; ++j)
|
|
{
|
|
real_t wj = (j==fny[1])? 0.5 : 1.0;
|
|
if (j <= fny[1])
|
|
{
|
|
size_t jp = j;
|
|
for (size_t k = 0; k < nf[2]; ++k)
|
|
{
|
|
if( typeid(data_t)==typeid(real_t) ){
|
|
real_t w = wi*wj;
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k]/rfac;
|
|
}else{
|
|
real_t wk = (k==fny[2])? 0.5 : 1.0;
|
|
real_t w = wi*wj*wk;
|
|
if (k <= fny[2])
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k]/rfac;
|
|
if (k >= fny[2])
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k + fny[2]]/rfac;
|
|
if( w<1.0 ){
|
|
fbuf_->kelem(i, j, k) = std::real(fbuf_->kelem(i, j, k));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
if (j >= fny[1])
|
|
{
|
|
size_t jp = j + fny[1];
|
|
for (size_t k = 0; k < nf[2]; ++k)
|
|
{
|
|
if( typeid(data_t)==typeid(real_t) ){
|
|
real_t w = wi*wj;
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k]/rfac;
|
|
}else{
|
|
real_t wk = (k==fny[2])? 0.5 : 1.0;
|
|
real_t w = wi*wj*wk;
|
|
if (k <= fny[2])
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k]/rfac;
|
|
if (k >= fny[2])
|
|
fbuf_->kelem(i, j, k) += w*crecvbuf_[jp * nfp[3] + k + fny[2]]/rfac;
|
|
if( w<1.0 ){
|
|
fbuf_->kelem(i, j, k) = std::real(fbuf_->kelem(i, j, k));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
//... copy data back
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < fbuf_->ntot_; ++i ){
|
|
output_op(i,(*fbuf_)[i]);
|
|
}
|
|
|
|
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::dlog.Print("[MPI] Completed gather for convolution, took %fs", get_wtime() - tstart);
|
|
|
|
#endif /// end of ifdef/ifndef USE_MPI //////////////////////////////////////////////////////////////
|
|
}
|
|
|
|
|
|
};
|