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Merged
pelesh merged 5 commits into from
Dec 13, 2023
Merged

Refactor handlers #110

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749ae81
Only pick between host and device in handlers.
pelesh Dec 12, 2023
f3a2caa
Use HOST/DEVICE in handler calls instead of cpu/cuda/hip.
pelesh Dec 12, 2023
15ebaa7
Coding style fixes and minor cleanup in LinSolverIterativeRandFGMRES.
pelesh Dec 12, 2023
be6a19c
Use char instead of std::string for transpose parameter.
pelesh Dec 12, 2023
10ea360
Clean up access to workspace pointers in handlers.
pelesh Dec 12, 2023
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14 changes: 7 additions & 7 deletions examples/r_KLU_GLU.cpp
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Expand Up @@ -141,22 +141,22 @@ int main(int argc, char *argv[])

// Estimate solution error
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);
real_type bnorm = sqrt(vector_handler->dot(vec_r, vec_r, "cuda"));
matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
real_type bnorm = sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE));
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);


matrix_handler->matrixInfNorm(A, &norm_A, "cuda");
norm_x = vector_handler->infNorm(vec_x, "cuda");
norm_r = vector_handler->infNorm(vec_r, "cuda");
matrix_handler->matrixInfNorm(A, &norm_A, ReSolve::memory::DEVICE);
norm_x = vector_handler->infNorm(vec_x, ReSolve::memory::DEVICE);
norm_r = vector_handler->infNorm(vec_r, ReSolve::memory::DEVICE);
std::cout << "\t Matrix inf norm: " << std::scientific << std::setprecision(16) << norm_A<<"\n"
<< "\t Residual inf norm: " << norm_r <<"\n"
<< "\t Solution inf norm: " << norm_x <<"\n"
<< "\t Norm of scaled residuals: "<< norm_r / (norm_A * norm_x) << "\n";

std::cout << "\t 2-Norm of the residual: "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cuda"))/bnorm << "\n";
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE))/bnorm << "\n";

} // for (int i = 0; i < numSystems; ++i)

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6 changes: 3 additions & 3 deletions examples/r_KLU_GLU_matrix_values_update.cpp
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Expand Up @@ -153,12 +153,12 @@ int main(int argc, char *argv[])
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);


matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);

std::cout << "\t 2-Norm of the residual: "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cuda")) << "\n";
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE)) << "\n";


}
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12 changes: 6 additions & 6 deletions examples/r_KLU_KLU.cpp
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Expand Up @@ -134,16 +134,16 @@ int main(int argc, char *argv[])
}
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::HOST);

matrix_handler->setValuesChanged(true, "cpu");
matrix_handler->setValuesChanged(true, ReSolve::memory::HOST);

matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE, "csr", "cpu");
norm_r = vector_handler->infNorm(vec_r, "cpu");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE, "csr", ReSolve::memory::HOST);
norm_r = vector_handler->infNorm(vec_r, ReSolve::memory::HOST);

std::cout << "\t2-Norm of the residual: "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cpu")) << "\n";
matrix_handler->matrixInfNorm(A, &norm_A, "cpu");
norm_x = vector_handler->infNorm(vec_x, "cpu");
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::HOST)) << "\n";
matrix_handler->matrixInfNorm(A, &norm_A, ReSolve::memory::HOST);
norm_x = vector_handler->infNorm(vec_x, ReSolve::memory::HOST);
std::cout << "\tMatrix inf norm: " << std::scientific << std::setprecision(16) << norm_A<<"\n"
<< "\tResidual inf norm: " << norm_r <<"\n"
<< "\tSolution inf norm: " << norm_x <<"\n"
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6 changes: 3 additions & 3 deletions examples/r_KLU_KLU_standalone.cpp
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Expand Up @@ -97,13 +97,13 @@ int main(int argc, char *argv[])
std::cout << "KLU solve status: " << status << std::endl;
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::HOST);

matrix_handler->setValuesChanged(true, "cpu");
matrix_handler->setValuesChanged(true, ReSolve::memory::HOST);

matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE, "csr", "cpu");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE, "csr", ReSolve::memory::HOST);

std::cout << "\t 2-Norm of the residual: "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cpu")) << "\n";
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::HOST)) << "\n";



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26 changes: 13 additions & 13 deletions examples/r_KLU_cusolverrf_redo_factorization.cpp
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Expand Up @@ -116,11 +116,11 @@ int main(int argc, char *argv[] )

//Now convert to CSR.
if (i < 2) {
matrix_handler->coo2csr(A_coo, A, "cpu");
matrix_handler->coo2csr(A_coo, A, ReSolve::memory::HOST);
vec_rhs->update(rhs, ReSolve::memory::HOST, ReSolve::memory::HOST);
vec_rhs->setDataUpdated(ReSolve::memory::HOST);
} else {
matrix_handler->coo2csr(A_coo, A, "cuda");
matrix_handler->coo2csr(A_coo, A, ReSolve::memory::DEVICE);
vec_rhs->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);
}
std::cout<<"COO to CSR completed. Expanded NNZ: "<< A->getNnzExpanded()<<std::endl;
Expand All @@ -138,8 +138,8 @@ int main(int argc, char *argv[] )
U_csc = (ReSolve::matrix::Csc*) KLU->getUFactor();
ReSolve::matrix::Csr* L = new ReSolve::matrix::Csr(L_csc->getNumRows(), L_csc->getNumColumns(), L_csc->getNnz());
ReSolve::matrix::Csr* U = new ReSolve::matrix::Csr(U_csc->getNumRows(), U_csc->getNumColumns(), U_csc->getNnz());
matrix_handler->csc2csr(L_csc,L, "cuda");
matrix_handler->csc2csr(U_csc,U, "cuda");
matrix_handler->csc2csr(L_csc,L, ReSolve::memory::DEVICE);
matrix_handler->csc2csr(U_csc,U, ReSolve::memory::DEVICE);
if (L == nullptr) {
std::cout << "ERROR\n";
}
Expand All @@ -159,11 +159,11 @@ int main(int argc, char *argv[] )
}
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);

matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);

matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
res_nrm = sqrt(vector_handler->dot(vec_r, vec_r, "cuda"));
b_nrm = sqrt(vector_handler->dot(vec_rhs, vec_rhs, "cuda"));
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);
res_nrm = sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE));
b_nrm = sqrt(vector_handler->dot(vec_rhs, vec_rhs, ReSolve::memory::DEVICE));
std::cout << "\t2-Norm of the residual: "
<< std::scientific << std::setprecision(16)
<< res_nrm/b_nrm << "\n";
Expand All @@ -184,10 +184,10 @@ int main(int argc, char *argv[] )
vec_rhs->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);

matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);

matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
res_nrm = sqrt(vector_handler->dot(vec_r, vec_r, "cuda"));
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);
res_nrm = sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE));

std::cout <<"\t New residual norm: "
<< std::scientific << std::setprecision(16)
Expand All @@ -199,8 +199,8 @@ int main(int argc, char *argv[] )

ReSolve::matrix::Csr* L = new ReSolve::matrix::Csr(L_csc->getNumRows(), L_csc->getNumColumns(), L_csc->getNnz());
ReSolve::matrix::Csr* U = new ReSolve::matrix::Csr(U_csc->getNumRows(), U_csc->getNumColumns(), U_csc->getNnz());
matrix_handler->csc2csr(L_csc, L, "cuda");
matrix_handler->csc2csr(U_csc, U, "cuda");
matrix_handler->csc2csr(L_csc, L, ReSolve::memory::DEVICE);
matrix_handler->csc2csr(U_csc, U, ReSolve::memory::DEVICE);

P = KLU->getPOrdering();
Q = KLU->getQOrdering();
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10 changes: 5 additions & 5 deletions examples/r_KLU_rf.cpp
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Expand Up @@ -129,8 +129,8 @@ int main(int argc, char *argv[] )
ReSolve::matrix::Csc* U_csc = (ReSolve::matrix::Csc*) KLU->getUFactor();
ReSolve::matrix::Csr* L = new ReSolve::matrix::Csr(L_csc->getNumRows(), L_csc->getNumColumns(), L_csc->getNnz());
ReSolve::matrix::Csr* U = new ReSolve::matrix::Csr(U_csc->getNumRows(), U_csc->getNumColumns(), U_csc->getNnz());
matrix_handler->csc2csr(L_csc,L, "cuda");
matrix_handler->csc2csr(U_csc,U, "cuda");
matrix_handler->csc2csr(L_csc,L, ReSolve::memory::DEVICE);
matrix_handler->csc2csr(U_csc,U, ReSolve::memory::DEVICE);
if (L == nullptr) {printf("ERROR");}
index_type* P = KLU->getPOrdering();
index_type* Q = KLU->getQOrdering();
Expand All @@ -152,13 +152,13 @@ int main(int argc, char *argv[] )
}
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);

matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);

matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);

std::cout << "\t 2-Norm of the residual: "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cuda")) << "\n";
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE)) << "\n";

} // for (int i = 0; i < numSystems; ++i)

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36 changes: 18 additions & 18 deletions examples/r_KLU_rf_FGMRES.cpp
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Expand Up @@ -124,37 +124,37 @@ int main(int argc, char *argv[])
real_type norm_b;
if (i < 2){
KLU->setup(A);
matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);
status = KLU->analyze();
std::cout<<"KLU analysis status: "<<status<<std::endl;
status = KLU->factorize();
std::cout<<"KLU factorization status: "<<status<<std::endl;
status = KLU->solve(vec_rhs, vec_x);
std::cout<<"KLU solve status: "<<status<<std::endl;
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);
norm_b = vector_handler->dot(vec_r, vec_r, "cuda");
norm_b = vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE);
norm_b = sqrt(norm_b);
matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);

matrix_handler->matrixInfNorm(A, &norm_A, "cuda");
norm_x = vector_handler->infNorm(vec_x, "cuda");
norm_r = vector_handler->infNorm(vec_r, "cuda");
matrix_handler->matrixInfNorm(A, &norm_A, ReSolve::memory::DEVICE);
norm_x = vector_handler->infNorm(vec_x, ReSolve::memory::DEVICE);
norm_r = vector_handler->infNorm(vec_r, ReSolve::memory::DEVICE);
std::cout << "\t Matrix inf norm: " << std::scientific << std::setprecision(16) << norm_A<<"\n"
<< "\t Residual inf norm: " << norm_r <<"\n"
<< "\t Solution inf norm: " << norm_x <<"\n"
<< "\t Norm of scaled residuals: "<< norm_r / (norm_A * norm_x) << "\n";

std::cout << "\t2-Norm of the residual: "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cuda"))/norm_b << "\n";
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE))/norm_b << "\n";
if (i == 1) {
ReSolve::matrix::Csc* L_csc = (ReSolve::matrix::Csc*) KLU->getLFactor();
ReSolve::matrix::Csc* U_csc = (ReSolve::matrix::Csc*) KLU->getUFactor();
ReSolve::matrix::Csr* L = new ReSolve::matrix::Csr(L_csc->getNumRows(), L_csc->getNumColumns(), L_csc->getNnz());
ReSolve::matrix::Csr* U = new ReSolve::matrix::Csr(U_csc->getNumRows(), U_csc->getNumColumns(), U_csc->getNnz());
matrix_handler->csc2csr(L_csc,L, "cuda");
matrix_handler->csc2csr(U_csc,U, "cuda");
matrix_handler->csc2csr(L_csc,L, ReSolve::memory::DEVICE);
matrix_handler->csc2csr(U_csc,U, ReSolve::memory::DEVICE);
if (L == nullptr) {
std::cout << "ERROR\n";
}
Expand All @@ -174,28 +174,28 @@ int main(int argc, char *argv[])
std::cout<<"CUSOLVER RF solve status: "<<status<<std::endl;

vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);
norm_b = vector_handler->dot(vec_r, vec_r, "cuda");
norm_b = vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE);
norm_b = sqrt(norm_b);

//matrix_handler->setValuesChanged(true, "cuda");
//matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);
FGMRES->resetMatrix(A);
FGMRES->setupPreconditioner("LU", Rf);

matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);

matrix_handler->matrixInfNorm(A, &norm_A, "cuda");
norm_x = vector_handler->infNorm(vec_x, "cuda");
norm_r = vector_handler->infNorm(vec_r, "cuda");
matrix_handler->matrixInfNorm(A, &norm_A, ReSolve::memory::DEVICE);
norm_x = vector_handler->infNorm(vec_x, ReSolve::memory::DEVICE);
norm_r = vector_handler->infNorm(vec_r, ReSolve::memory::DEVICE);
std::cout << "\t Matrix inf norm: " << std::scientific << std::setprecision(16) << norm_A<<"\n"
<< "\t Residual inf norm: " << norm_r <<"\n"
<< "\t Solution inf norm: " << norm_x <<"\n"
<< "\t Norm of scaled residuals: "<< norm_r / (norm_A * norm_x) << "\n";

std::cout << "\t 2-Norm of the residual (before IR): "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cuda"))/norm_b << "\n";
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE))/norm_b << "\n";

matrix_handler->matrixInfNorm(A, &norm_A, "cuda");
matrix_handler->matrixInfNorm(A, &norm_A, ReSolve::memory::DEVICE);
vec_rhs->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);

if(!std::isnan(norm_r) && !std::isinf(norm_r)) {
Expand Down
26 changes: 13 additions & 13 deletions examples/r_KLU_rf_FGMRES_reuse_factorization.cpp
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Expand Up @@ -125,29 +125,29 @@ int main(int argc, char *argv[])
real_type norm_b;
if (i < 2){
KLU->setup(A);
matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);
status = KLU->analyze();
std::cout<<"KLU analysis status: "<<status<<std::endl;
status = KLU->factorize();
std::cout<<"KLU factorization status: "<<status<<std::endl;
status = KLU->solve(vec_rhs, vec_x);
std::cout<<"KLU solve status: "<<status<<std::endl;
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);
norm_b = vector_handler->dot(vec_r, vec_r, "cuda");
norm_b = vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE);
norm_b = sqrt(norm_b);
matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);
std::cout << "\t 2-Norm of the residual : "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cuda"))/norm_b << "\n";
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE))/norm_b << "\n";
if (i == 1) {
ReSolve::matrix::Csc* L_csc = (ReSolve::matrix::Csc*) KLU->getLFactor();
ReSolve::matrix::Csc* U_csc = (ReSolve::matrix::Csc*) KLU->getUFactor();
ReSolve::matrix::Csr* L = new ReSolve::matrix::Csr(L_csc->getNumRows(), L_csc->getNumColumns(), L_csc->getNnz());
ReSolve::matrix::Csr* U = new ReSolve::matrix::Csr(U_csc->getNumRows(), U_csc->getNumColumns(), U_csc->getNnz());

matrix_handler->csc2csr(L_csc,L, "cuda");
matrix_handler->csc2csr(U_csc,U, "cuda");
matrix_handler->csc2csr(L_csc,L, ReSolve::memory::DEVICE);
matrix_handler->csc2csr(U_csc,U, ReSolve::memory::DEVICE);
if (L == nullptr) {
std::cout << "ERROR\n";
}
Expand All @@ -173,25 +173,25 @@ int main(int argc, char *argv[])
FGMRES->setupPreconditioner("LU", Rf);
}
//if (i%2!=0) vec_x->setToZero(ReSolve::memory::DEVICE);
real_type norm_x = vector_handler->dot(vec_x, vec_x, "cuda");
real_type norm_x = vector_handler->dot(vec_x, vec_x, ReSolve::memory::DEVICE);
std::cout << "Norm of x (before solve): "
<< std::scientific << std::setprecision(16)
<< sqrt(norm_x) << "\n";
std::cout<<"CUSOLVER RF solve status: "<<status<<std::endl;

vec_rhs->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);
vec_r->update(rhs, ReSolve::memory::HOST, ReSolve::memory::DEVICE);
norm_b = vector_handler->dot(vec_r, vec_r, "cuda");
norm_b = vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE);
norm_b = sqrt(norm_b);

matrix_handler->setValuesChanged(true, "cuda");
matrix_handler->setValuesChanged(true, ReSolve::memory::DEVICE);
FGMRES->resetMatrix(A);

matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", "cuda");
matrix_handler->matvec(A, vec_x, vec_r, &ONE, &MINUSONE,"csr", ReSolve::memory::DEVICE);

std::cout << "\t 2-Norm of the residual (before IR): "
<< std::scientific << std::setprecision(16)
<< sqrt(vector_handler->dot(vec_r, vec_r, "cuda"))/norm_b << "\n";
<< sqrt(vector_handler->dot(vec_r, vec_r, ReSolve::memory::DEVICE))/norm_b << "\n";
std::cout << "\t 2-Norm of the RIGHT HAND SIDE: "
<< std::scientific << std::setprecision(16)
<< norm_b << "\n";
Expand All @@ -205,7 +205,7 @@ int main(int argc, char *argv[])
<< " final nrm: "
<< FGMRES->getFinalResidualNorm()/norm_b
<< " iter: " << FGMRES->getNumIter() << "\n";
norm_x = vector_handler->dot(vec_x, vec_x, "cuda");
norm_x = vector_handler->dot(vec_x, vec_x, ReSolve::memory::DEVICE);
std::cout << "Norm of x (after IR): "
<< std::scientific << std::setprecision(16)
<< sqrt(norm_x) << "\n";
Expand Down
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