748 lines
25 KiB
C++
748 lines
25 KiB
C++
//------------------------------------------------------------------------------
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/* vim: set ts=8 sw=8 sts=8 noexpandtab cindent: */
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//------------------------------------------------------------------------------
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/*
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LA: linear algebra C++ interface library
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Copyright (C) 2008 Jiri Pittner <jiri.pittner@jh-inst.cas.cz> or <jiri@pittnerovi.com>
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complex versions written by Roman Curik <roman.curik@jh-inst.cas.cz>
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include "smat.h"
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#include <stdlib.h>
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#include <stdio.h>
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#include <sys/types.h>
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#include <sys/stat.h>
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#include <fcntl.h>
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#include <errno.h>
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#include <unistd.h>
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namespace LA {
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/***************************************************************************//**
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* routine for raw output
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* @param[in] fd file descriptor for output
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* @param[in] dim number of elements intended for output
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* @param[in] transp reserved
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* @see NRMat<T>::get(), NRSMat<T>::copyonwrite()
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******************************************************************************/
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template <typename T>
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void NRSMat<T>::put(int fd, bool dim, bool transp) const {
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#ifdef CUDALA
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if(location != cpu){
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NRSMat<T> tmp= *this;
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tmp.moveto(cpu);
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tmp.put(fd,dim,transp);
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return;
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}
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#endif
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errno = 0;
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if(dim){
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if(sizeof(int) != write(fd,&nn,sizeof(int))) laerror("cannot write");
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if(sizeof(int) != write(fd,&nn,sizeof(int))) laerror("cannot write");
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}
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LA_traits<T>::multiput((size_t)nn*(nn+1)/2,fd,v,dim);
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}
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/***************************************************************************//**
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* routine for raw input
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* @param[in] fd file descriptor for input
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* @param[in] dim number of elements intended for input
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* @param[in] transp reserved
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* @see NRSMat<T>::put(), NRSMat<T>::copyonwrite()
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******************************************************************************/
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template <typename T>
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void NRSMat<T>::get(int fd, bool dim, bool transp) {
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#ifdef CUDALA
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if(location != cpu){
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NRSMat<T> tmp;
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tmp.moveto(cpu);
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tmp.get(fd,dim,transp);
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tmp.moveto(location);
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*this = tmp;
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return;
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}
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#endif
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int nn0[2]; //align at least 8-byte
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errno = 0;
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if(dim){
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if(2*sizeof(int) != read(fd,&nn0,2*sizeof(int))) laerror("cannot read");
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resize(nn0[0]);
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}else{
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copyonwrite();
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}
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LA_traits<T>::multiget((size_t)nn*(nn+1)/2,fd,v,dim);
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}
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/***************************************************************************//**
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* constructor symmetrizing given matrix \f$A\f$ of general type <code>T</code> yielding \f$(A+A^\mathrm{T})/2\f$
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* @param[in] rhs matrix \f$A\f$
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******************************************************************************/
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template <typename T>
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NRSMat<T>::NRSMat(const NRMat<T> &rhs) {
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NOT_GPU(rhs);
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nn = rhs.nrows();
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#ifdef DEBUG
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if(nn != rhs.ncols()) laerror("attempt to convert nonsquare NRMat<T> to NRSMat<T>");
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#endif
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#ifdef CUDALA
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location = rhs.getlocation();
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#endif
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count = new int;
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*count = 1;
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v = new T[NN2];
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int i, j, k(0);
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for(i=0; i<nn; i++){
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for(j=0; j<=i; j++){
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v[k++] = (rhs[i][j] + rhs[j][i])/((T)2);
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}
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}
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}
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/***************************************************************************//**
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* zero out this symmetric matrix of general type <code>T</code> and then set
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* the diagonal elements to prescribed value
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* @param[in] a scalar value to be assigned to the diagonal
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* @return reference to the modified matrix
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******************************************************************************/
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template <typename T>
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NRSMat<T> & NRSMat<T>::operator=(const T &a) {
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NOT_GPU(*this);
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copyonwrite();
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memset(v, 0, NN2*sizeof(T));
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for(register int i=0; i<nn; i++) v[(size_t)i*(i+1)/2 + i] = a;
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return *this;
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}
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/***************************************************************************//**
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* get or divide by the diagonal of real symmetric double-precision matrix
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* @param[in, out] r vector for storing the diagonal
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* @param[in] divide
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* \li \c false save the diagonal to vector r
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* \li \c true divide the vector r by the diagonal elements element-wise
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* @param[in] cache reserved
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* @return
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* \li <tt>divide == true</tt> NULL
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* \li <tt>divide == false</tt> pointer to the first element of r
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******************************************************************************/
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template <typename T>
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const T* NRSMat<T>::diagonalof(NRVec<T> &r, const bool divide, bool cache) const {
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#ifdef DEBUG
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if(r.size() != nn) laerror("incompatible vector in const T* NRSMat<T>::diagonalof(NRVec<T> &, const bool, bool)");
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#endif
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NOT_GPU(*this);
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SAME_LOC(*this, r);
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r.copyonwrite();
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if(divide){
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for(register int i=0; i<nn; i++){
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const T a = v[(size_t)i*(i+1)/2+i];
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if(a != 0.) r[i] /= a;
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}
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}else{
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for(register int i=0; i<nn; i++) r[i] = v[(size_t)i*(i+1)/2+i];
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}
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return divide?NULL:&r[0];
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}
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/***************************************************************************//**
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* implements unary minus operator for this symmetric
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* matrix of general type <code>T</code>
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* @return modified copy of this matrix
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******************************************************************************/
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template <typename T>
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const NRSMat<T> NRSMat<T>::operator-() const {
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NOT_GPU(*this);
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NRSMat<T> result(nn, getlocation());
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for(register size_t i = 0; i<NN2; i++) result.v[i]= -v[i];
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return result;
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}
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/***************************************************************************//**
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* implements unary minus operator for this real symmetric matrix
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* @return modified copy of this matrix
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******************************************************************************/
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template <>
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const NRSMat<double> NRSMat<double>::operator-() const {
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NRSMat<double> result(nn, getlocation());
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#ifdef CUDALA
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if(location == cpu){
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#endif
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memcpy(result.v, v, NN2*sizeof(double));
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cblas_dscal(NN2, -1., result.v, 1);
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#ifdef CUDALA
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}else{
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cublasDcopy(NN2, v, 1, result.v, 1);
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TEST_CUBLAS("cublasDcopy");
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cublasDscal(NN2, -1., result.v, 1);
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TEST_CUBLAS("cublasDscal");
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}
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#endif
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return result;
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}
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/***************************************************************************//**
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* implements unary minus operator for this hermitian matrix
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* @return modified copy of this matrix
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******************************************************************************/
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template <>
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const NRSMat<std::complex<double> > NRSMat<std::complex<double> >::operator-() const {
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NRSMat<std::complex<double> > result(nn, getlocation());
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#ifdef CUDALA
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if(location == cpu) {
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#endif
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memcpy(result.v, v, NN2*sizeof(std::complex<double>));
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cblas_zscal(NN2, &CMONE, result.v, 1);
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#ifdef CUDALA
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}else{
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cublasZcopy(NN2, (cuDoubleComplex*)v, 1, (cuDoubleComplex*)result.v, 1);
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TEST_CUBLAS("cublasZcopy");
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cublasZscal(NN2, CUMONE, (cuDoubleComplex*)result.v, 1);
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TEST_CUBLAS("cublasZscal");
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}
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#endif
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return result;
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}
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/***************************************************************************//**
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* @return the sum of the diagonal elements
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******************************************************************************/
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template <typename T>
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const T NRSMat<T>::trace() const {
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NOT_GPU(*this);
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T tmp = 0;
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for(register int i=0; i<nn; i++) tmp += v[(size_t)i*(i+1)/2+i];
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return tmp;
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}
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/***************************************************************************//**
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* fill this real symmetric matrix with
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* pseudorandom numbers generated from uniform distribution
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******************************************************************************/
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template<>
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void NRSMat<double>::randomize(const double &x) {
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NOT_GPU(*this);
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for(size_t i=0; i<NN2; ++i){
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v[i] = x*(2.*random()/(1.+RAND_MAX) -1.);
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}
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}
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/***************************************************************************//**
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* Fill this hermitian matrix with pseudorandom numbers generated from uniform
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* distribution. The real and imaginary parts are generated independently.
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******************************************************************************/
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template<>
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void NRSMat<std::complex<double> >::randomize(const double &x) {
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for(register size_t i=0; i<NN2; ++i) v[i].real(x*(2.*random()/(1. + RAND_MAX) -1.));
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for(register size_t i=0; i<NN2; ++i) v[i].imag(x*(2.*random()/(1. + RAND_MAX) -1.));
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for(register int i=0; i<nn; ++i){
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for(register int j=0; j<=i; ++j){
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if(i == j) v[i*(size_t)(i+1)/2+j].imag(0.); //hermitean
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}
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}
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}
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/***************************************************************************//**
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* routine for formatted output via lawritemat
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* @param[in] file pointer to <tt>FILE</tt> structure representing the output file
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* @param[in] format format specification in standard printf-like form
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* @param[in] modulo
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* @see lawritemat()
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******************************************************************************/
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template <typename T>
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void NRSMat<T>::fprintf(FILE *file, const char *format, const int modulo) const {
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NOT_GPU(*this);
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lawritemat(file, (const T *)(*this) ,nn, nn, format, 2, modulo, 1);
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}
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/***************************************************************************//**
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* routine for formatted input via fscanf
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* @param[in] f pointer to <tt>FILE</tt> structure representing the input file
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* @param[in] format format specification in standard printf-like form
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******************************************************************************/
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template <typename T>
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void NRSMat<T>::fscanf(FILE *f, const char *format) {
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int n, m;
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NOT_GPU(*this);
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if (::fscanf(f,"%d %d", &n, &m) != 2)
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laerror("cannot read matrix dimensions in NRSMat<T>::fscanf(FILE *, const char *)");
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if (n != m) laerror("different dimensions in NRSMat<T>::fscanf(FILE *, const char *)");
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resize(n);
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for (int i=0; i<n; i++)
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for (int j=0; j<n; j++)
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if (::fscanf(f,format,&((*this)(i,j))) != 1)
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laerror("NRSMat<T>::fscanf(FILE *, const char *) - unable to read matrix element");
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}
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//apply permutation
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template <typename T>
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const NRSMat<T> NRSMat<T>::permuted(const NRPerm<int> &p, const bool inverse) const
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{
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#ifdef DEBUG
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if(!p.is_valid()) laerror("invalid permutation of smatrix");
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#endif
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int n=p.size();
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if(n!=(*this).size()) laerror("incompatible permutation and smatrix");
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#ifdef CUDALA
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if(this->getlocation() != cpu || p.getlocation() != cpu ) laerror("permutations can be done only in CPU memory");
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#endif
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NRSMat<T> r(n);
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if(inverse) for(int i=1; i<=n; ++i) {int pi = p[i]-1; r(i-1,i-1) = (*this)(pi,pi);}
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else for(int i=1; i<=n; ++i) {int pi = p[i]-1; r(pi,pi) = (*this)(i-1,i-1);}
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return r;
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}
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/***************************************************************************//**
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* multiply this real double-precision symmetric matrix \f$S\f$ stored in packed form
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* with real double-precision dense matrix \f$A\f$
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* @param[in] rhs real double-precision matrix \f$A\f$
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* @return matrix produt \f$S\times{}A\f$
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******************************************************************************/
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template<>
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const NRMat<double> NRSMat<double>::operator*(const NRMat<double> &rhs) const {
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#ifdef DEBUG
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if(nn != rhs.nrows()) laerror("incompatible dimensions in NRMat<double> NRSMat<double>::operator*(const NRMat<double> &)");
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#endif
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SAME_LOC(*this, rhs);
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NRMat<double> result(nn, rhs.ncols(), getlocation());
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#ifdef CUDALA
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if(location == cpu){
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#endif
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for(register int k = 0; k<rhs.ncols(); k++){
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cblas_dspmv(CblasRowMajor, CblasLower, nn, 1.0, v, rhs[0] + k, rhs.ncols(), 0.0, result[0] + k, rhs.ncols());
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}
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#ifdef CUDALA
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}else{
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for(register int k = 0; k<rhs.ncols(); k++){
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cublasDspmv('U', nn, 1.0, v, rhs[0] + k, rhs.ncols(), 0.0, result[0] + k, rhs.ncols());
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TEST_CUBLAS("cublasDspmv");
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}
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}
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#endif
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return result;
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}
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/***************************************************************************//**
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* multiply this real double-precision symmetric matrix \f$S\f$ stored in packed form
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* with real double-precision dense matrix \f$A\f$
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* @param[in] rhs real double-precision matrix \f$A\f$
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* @return matrix produt \f$S\times{}A\f$
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******************************************************************************/
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template<>
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const NRMat<std::complex<double> >
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NRSMat<std::complex<double> >::operator*(const NRMat<std::complex<double> > &rhs) const {
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#ifdef DEBUG
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if (nn != rhs.nrows()) laerror("incompatible dimensions in NRSMat<std::complex<double> >::operator*(const NRMat<std::complex<double> > &)");
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#endif
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SAME_LOC(*this, rhs);
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NRMat<std::complex<double> > result(nn, rhs.ncols(), getlocation());
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#ifdef CUDALA
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if(location == cpu){
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#endif
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for(register int k=0; k<rhs.ncols(); k++){
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cblas_zhpmv(CblasRowMajor, CblasLower, nn, &CONE, v, rhs[0]+k, rhs.ncols(), &CZERO, result[0]+k, rhs.ncols());
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}
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#ifdef CUDALA
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}else{
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for(register int k = 0; k<rhs.ncols(); k++){
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cublasZhpmv('U', nn,
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CUONE, (cuDoubleComplex*)v, (cuDoubleComplex*)(rhs[0] + k), rhs.ncols(),
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CUZERO, (cuDoubleComplex*)(result[0] + k), rhs.ncols());
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TEST_CUBLAS("cublasDspmv");
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}
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}
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#endif
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return result;
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}
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/***************************************************************************//**
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* multiply this real double-precision symmetric matrix \f$S\f$ stored in packed form
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* with real double-precision symmetric matrix \f$T\f$
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* @return matrix produt \f$S\times{}T\f$ (not necessarily symmetric)
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******************************************************************************/
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template<>
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const NRMat<double> NRSMat<double>::operator*(const NRSMat<double> &rhs) const {
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#ifdef DEBUG
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if (nn != rhs.nn) laerror("incompatible dimensions in NRMat<double> NRSMat<double>::operator*(const NRSMat<double> &)");
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#endif
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NRMat<double> result(0.0, nn, nn);
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double *p, *q;
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p = v;
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for (int i=0; i<nn;i++) {
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q = rhs.v;
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for (int k=0; k<=i; k++) {
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cblas_daxpy(k+1, *p++, q, 1, result[i], 1);
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q += k+1;
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}
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}
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p = v;
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for (int i=0; i<nn;i++) {
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q = rhs.v+1;
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for (int j=1; j<nn; j++) {
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result[i][j] += cblas_ddot(i+1<j ? i+1 : j, p, 1, q, 1);
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q += j+1;
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}
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p += i+1;
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}
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p = v;
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q = rhs.v;
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for (int i=0; i<nn; i++) {
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cblas_dger(CblasRowMajor, i, i+1, 1., p, 1, q, 1, result, nn);
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p += i+1;
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q += i+1;
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}
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q = rhs.v+3;
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for (int j=2; j<nn; j++) {
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p = v+1;
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for (int i=1; i<j; i++) {
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cblas_daxpy(i, *++q, p, 1, result[0]+j, nn);
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p += i+1;
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}
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q += 2;
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}
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return result;
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}
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/***************************************************************************//**
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* multiply this complex double-precision symmetric matrix \f$G\f$ stored in packed form
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* with complex double-precision symmetric matrix \f$H\f$
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* @return matrix produt \f$G\times{}H\f$ (not necessarily symmetric)
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******************************************************************************/
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template<>
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const NRMat<std::complex<double> >
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NRSMat<std::complex<double> >::operator*(const NRSMat<std::complex<double> > &rhs) const {
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#ifdef DEBUG
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if (nn != rhs.nn) laerror("incompatible dimensions in NRSMat<std::complex<double> >::operator*(const NRSMat<std::complex<double> > &)");
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#endif
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SAME_LOC(*this, rhs);
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NRMat<std::complex<double> > result(nn, nn, getlocation());
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NRMat<std::complex<double> > rhsmat(rhs);
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result = *this * rhsmat;
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return result;
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}
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/***************************************************************************//**
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* compute inner product of this real symmetric matrix \f$A\f$ with given real symmetric matrix \f$B\f$
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* i.e. determine the value of
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* \f[\sum_{i,j}A_{i,j}B_{i,j}\f]
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* @param[in] rhs matrix \f$B\f$
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* @return computed inner product
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******************************************************************************/
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template<>
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const double NRSMat<double>::dot(const NRSMat<double> &rhs) const {
|
|
double ret(0.);
|
|
#ifdef DEBUG
|
|
if (nn != rhs.nn) laerror("incompatible dimensions in double NRSMat<double>::dot(const NRSMat<double> &)");
|
|
#endif
|
|
SAME_LOC(*this, rhs);
|
|
#ifdef CUDALA
|
|
if(location == cpu){
|
|
#endif
|
|
ret = cblas_ddot(NN2, v, 1, rhs.v, 1);
|
|
#ifdef CUDALA
|
|
}else{
|
|
ret = cublasDdot(NN2, v, 1, rhs.v, 1);
|
|
}
|
|
#endif
|
|
return ret;
|
|
}
|
|
|
|
|
|
/***************************************************************************//**
|
|
* compute inner product of this complex symmetric matrix \f$A\f$ with given complex symmetric matrix \f$B\f$
|
|
* i.e. determine the value of
|
|
* \f[\sum_{i,j}\overbar{A_{i,j}}B_{i,j}\f]
|
|
* @param[in] rhs matrix \f$B\f$
|
|
* @return computed inner product
|
|
******************************************************************************/
|
|
template<>
|
|
const std::complex<double> NRSMat<std::complex<double> >::dot(const NRSMat<std::complex<double> > &rhs) const {
|
|
#ifdef DEBUG
|
|
if (nn != rhs.nn) laerror("incompatible dimensions in std::complex<double> NRSMat<std::complex<double> >::dot(const NRSMat<std::complex<double> > &)");
|
|
#endif
|
|
std::complex<double> dot(0., 0.);
|
|
SAME_LOC(*this, rhs);
|
|
|
|
#ifdef CUDALA
|
|
if(location == cpu){
|
|
#endif
|
|
cblas_zdotc_sub(NN2, v, 1, rhs.v, 1, &dot);
|
|
#ifdef CUDALA
|
|
}else{
|
|
const cuDoubleComplex _dot = cublasZdotc(NN2, (cuDoubleComplex*)v, 1, (cuDoubleComplex*)(rhs.v), 1);
|
|
dot = std::complex<double>(cuCreal(_dot), cuCimag(_dot));
|
|
TEST_CUBLAS("cublasZdotc");
|
|
}
|
|
#endif
|
|
return dot;
|
|
}
|
|
|
|
|
|
/***************************************************************************//**
|
|
* compute inner product of this real double-precision symmetric matrix \f$S\f$ of order \f$n\f$
|
|
* with given real double-precision vector \f$\vec{v}\f$ of length \f$n(n+1)/2\f$
|
|
* @param[in] rhs real double-precision vector \f$\vec{v}\f$
|
|
* @return computed inner product
|
|
******************************************************************************/
|
|
template<>
|
|
const double NRSMat<double>::dot(const NRVec<double> &rhs) const {
|
|
double ret(0.0);
|
|
#ifdef DEBUG
|
|
if(NN2 != rhs.nn) laerror("incompatible dimensions in double NRSMat<double>::dot(const NRVec<double> &)");
|
|
#endif
|
|
SAME_LOC(*this, rhs);
|
|
#ifdef CUDALA
|
|
if(location == cpu){
|
|
#endif
|
|
ret = cblas_ddot(NN2, v, 1, rhs.v, 1);
|
|
#ifdef CUDALA
|
|
}else{
|
|
ret = cublasDdot(NN2, v, 1, rhs.v, 1);
|
|
TEST_CUBLAS("cublasDdot");
|
|
}
|
|
#endif
|
|
return ret;
|
|
}
|
|
|
|
|
|
/***************************************************************************//**
|
|
* compute inner product of this complex double-precision hermitian matrix \f$H\f$ of order \f$n\f$
|
|
* with given complex double-precision vector \f$\vec{v}\f$ of length \f$n(n+1)/2\f$
|
|
* @param[in] rhs complex double-precision vector \f$\vec{v}\f$
|
|
* @return computed inner product
|
|
******************************************************************************/
|
|
template<>
|
|
const std::complex<double>
|
|
NRSMat<std::complex<double> >::dot(const NRVec<std::complex<double> > &rhs) const {
|
|
#ifdef DEBUG
|
|
if(NN2 != rhs.nn) laerror("incompatible dimensions in std::complex<double> NRSMat<std::complex<double> >::dot(const NRVec<std::complex<double> > &)");
|
|
#endif
|
|
std::complex<double> dot(0., 0.);
|
|
SAME_LOC(*this, rhs);
|
|
#ifdef CUDALA
|
|
if(location == cpu){
|
|
#endif
|
|
cblas_zdotc_sub(NN2, v, 1, rhs.v, 1, &dot);
|
|
#ifdef CUDALA
|
|
}else{
|
|
const cuDoubleComplex _dot = cublasZdotc(NN2, (cuDoubleComplex*)v, 1, (cuDoubleComplex*)rhs.v, 1);
|
|
TEST_CUBLAS("cublasZdotc");
|
|
dot = std::complex<double>(cuCreal(_dot), cuCimag(_dot));
|
|
}
|
|
#endif
|
|
return dot;
|
|
}
|
|
|
|
/***************************************************************************//**
|
|
* compute the Frobenius norm of this real double-precision symmetric matrix
|
|
* @param[in] scalar subtract this scalar value from the diagonal elements before the norm computation
|
|
******************************************************************************/
|
|
template<>
|
|
const double NRSMat<double>::norm(const double scalar) const {
|
|
if(!scalar){
|
|
double ret(0.);
|
|
#ifdef CUDALA
|
|
if(location == cpu){
|
|
#endif
|
|
ret = cblas_dnrm2(NN2, v, 1);
|
|
#ifdef CUDALA
|
|
}else{
|
|
ret = cublasDnrm2(NN2, v, 1);
|
|
TEST_CUBLAS("cublasDnrm2");
|
|
}
|
|
#endif
|
|
return ret;
|
|
}
|
|
|
|
NOT_GPU(*this);
|
|
|
|
double sum(0.);
|
|
int k(0);
|
|
for(register int i=0; i<nn; ++i){
|
|
for(register int j=0; j<=i; ++j) {
|
|
register double tmp = v[k++];
|
|
if(i == j) tmp -= scalar;
|
|
sum += tmp*tmp;
|
|
}
|
|
}
|
|
return std::sqrt(sum);
|
|
}
|
|
|
|
/***************************************************************************//**
|
|
* compute the Frobenius norm of this complex double-precision hermitian matrix
|
|
* @param[in] scalar subtract this scalar value from the diagonal elements before the norm computation
|
|
******************************************************************************/
|
|
template<>
|
|
const double NRSMat< std::complex<double> >::norm(const std::complex<double> scalar) const {
|
|
if(!(scalar.real()) && !(scalar.imag())){
|
|
double ret(0.);
|
|
#ifdef CUDALA
|
|
if(location == cpu){
|
|
#endif
|
|
ret = cblas_dznrm2(NN2, v, 1);
|
|
#ifdef CUDALA
|
|
}else{
|
|
ret = cublasDznrm2(NN2, (cuDoubleComplex*)v, 1);
|
|
TEST_CUBLAS("cublasDznrm2");
|
|
}
|
|
#endif
|
|
return ret;
|
|
}
|
|
|
|
int k(0);
|
|
double sum(0.);
|
|
std::complex<double> tmp;
|
|
|
|
for(register int i=0; i<nn; ++i){
|
|
for(register int j=0; j<=i; ++j){
|
|
tmp = v[k++];
|
|
if (i == j) tmp -= scalar;
|
|
sum += tmp.real()*tmp.real() + tmp.imag()*tmp.imag();
|
|
}
|
|
}
|
|
return std::sqrt(sum);
|
|
}
|
|
|
|
|
|
/***************************************************************************//**
|
|
* for this real double-precision symmetric matrix \f$S\f$ stored in packed form,
|
|
* real scalar value \f$\alpha\f$ and real double-precision symmetric matrix \f$T\f$, compute
|
|
* \f[S \leftarrow \alpha T + S\f]
|
|
******************************************************************************/
|
|
template<>
|
|
void NRSMat<double>::axpy(const double alpha, const NRSMat<double> &x) {
|
|
#ifdef DEBUG
|
|
if(nn != x.nn) laerror("incompatible dimensions in void NRSMat<double>::axpy(const double, const NRSMat<double>&)");
|
|
#endif
|
|
SAME_LOC(*this, x);
|
|
copyonwrite();
|
|
#ifdef CUDALA
|
|
if(location == cpu){
|
|
#endif
|
|
cblas_daxpy(NN2, alpha, x.v, 1, v, 1);
|
|
#ifdef CUDALA
|
|
}else{
|
|
cublasDaxpy(NN2, alpha, x.v, 1, v, 1);
|
|
TEST_CUBLAS("cublasDaxpy");
|
|
}
|
|
#endif
|
|
}
|
|
|
|
|
|
/***************************************************************************//**
|
|
* for this complex double-precision hermitian matrix \f$H\f$ stored in packed form,
|
|
* complex scalar value \f$\alpha\f$ and complex double-precision hermitian matrix \f$G\f$, compute
|
|
* \f[H \leftarrow \alpha G + H\f]
|
|
******************************************************************************/
|
|
template<>
|
|
void NRSMat<std::complex<double> >::axpy(const std::complex<double> alpha, const NRSMat<std::complex<double> > & x) {
|
|
#ifdef DEBUG
|
|
if(nn != x.nn) laerror("incompatible dimensions in void NRSMat<std::complex<double> >::axpy(const std::complex<double> , const NRSMat<std::complex<double> >&)");
|
|
#endif
|
|
SAME_LOC(*this, x);
|
|
copyonwrite();
|
|
#ifdef CUDALA
|
|
if(location == cpu){
|
|
#endif
|
|
cblas_zaxpy(nn, &alpha, x.v, 1, v, 1);
|
|
#ifdef CUDALA
|
|
}else{
|
|
const cuDoubleComplex _alpha = make_cuDoubleComplex(alpha.real(), alpha.imag());
|
|
cublasZaxpy(NN2, _alpha, (cuDoubleComplex*)x.v, 1, (cuDoubleComplex*)v, 1);
|
|
TEST_CUBLAS("cublasZaxpy");
|
|
}
|
|
#endif
|
|
|
|
}
|
|
|
|
/***************************************************************************//**
|
|
* create hermitian matrix \f$H\f$ from given real double-precision symmetric
|
|
* matrix \f$S\f$
|
|
* @param[in] rhs real double-precision symmetric matrix \f$S\f$
|
|
* @param[in] imagpart flag determining whether \f$S\f$ should correspond to the real or imaginary part of \f$H\f$
|
|
******************************************************************************/
|
|
template<>
|
|
NRSMat<std::complex<double> >::NRSMat(const NRSMat<double> &rhs, bool imagpart): nn(rhs.nrows()), count(new int(1)) {
|
|
//inconsistent in general case?
|
|
const int nnp1 = nn*(nn + 1)/2;
|
|
#ifdef CUDALA
|
|
location = rhs.getlocation();
|
|
if(location == cpu){
|
|
#endif
|
|
v = new std::complex<double>[nnp1];
|
|
memset(v, 0, nnp1*sizeof(std::complex<double>));
|
|
cblas_dcopy(nnp1, &rhs(0, 0), 1, ((double *)v) + (imagpart?1:0), 2);
|
|
#ifdef CUDALA
|
|
}else{
|
|
v = (std::complex<double>*) gpualloc(nnp1*sizeof(std::complex<double>));
|
|
|
|
std::complex<double> *_val = gpuputcomplex(CZERO);
|
|
cublasZcopy(nnp1, (cuDoubleComplex*)_val, 0, (cuDoubleComplex*)v, 1);
|
|
TEST_CUBLAS("cublasZcopy");
|
|
gpufree(_val);
|
|
|
|
cublasDcopy(nnp1, (double*)(&rhs(0,0)), 1, ((double*)v) + (imagpart?1:0), 2);
|
|
TEST_CUBLAS("cublasDcopy");
|
|
}
|
|
#endif
|
|
}
|
|
|
|
/***************************************************************************//**
|
|
* forced instantization in the corresponding object file
|
|
******************************************************************************/
|
|
template class NRSMat<double>;
|
|
template class NRSMat<std::complex<double> >;
|
|
|
|
template class NRSMat<long long>;
|
|
template class NRSMat<long>;
|
|
template class NRSMat<int>;
|
|
template class NRSMat<short>;
|
|
template class NRSMat<char>;
|
|
template class NRSMat<unsigned char>;
|
|
template class NRSMat<unsigned short>;
|
|
template class NRSMat<unsigned int>;
|
|
template class NRSMat<unsigned long>;
|
|
template class NRSMat<unsigned long long>;
|
|
|
|
}//namespace
|