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