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@ -1,502 +0,0 @@
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16
COPYING.README
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@ -2,17 +2,5 @@ Eigen is primarily MPL2 licensed. See COPYING.MPL2 and these links:
http://www.mozilla.org/MPL/2.0/
http://www.mozilla.org/MPL/2.0/FAQ.html
Some files contain third-party code under BSD or LGPL licenses, whence the other
COPYING.* files here.
All the LGPL code is either LGPL 2.1-only, or LGPL 2.1-or-later.
For this reason, the COPYING.LGPL file contains the LGPL 2.1 text.
If you want to guarantee that the Eigen code that you are #including is licensed
under the MPL2 and possibly more permissive licenses (like BSD), #define this
preprocessor symbol:
EIGEN_MPL2_ONLY
For example, with most compilers, you could add this to your project CXXFLAGS:
-DEIGEN_MPL2_ONLY
This will cause a compilation error to be generated if you #include any code that is
LGPL licensed.
Some files contain third-party code under BSD or other MPL2-compatible licenses,
whence the other COPYING.* files here.

3
Eigen/src/Core/util/NonMPL2.h
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@ -1,3 +0,0 @@
#ifdef EIGEN_MPL2_ONLY
#error Including non-MPL2 code in EIGEN_MPL2_ONLY mode
#endif

3
Eigen/src/IterativeLinearSolvers/IncompleteCholesky.h
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@ -26,8 +26,7 @@ namespace Eigen {
* \tparam Scalar the scalar type of the input matrices
* \tparam UpLo_ The triangular part that will be used for the computations. It can be Lower
* or Upper. Default is Lower.
* \tparam OrderingType_ The ordering method to use, either AMDOrdering<> or NaturalOrdering<>. Default is AMDOrdering<int>,
* unless EIGEN_MPL2_ONLY is defined, in which case the default is NaturalOrdering<int>.
* \tparam OrderingType_ The ordering method to use, either AMDOrdering<> or NaturalOrdering<>. Default is AMDOrdering<int>.
*
* \implsparsesolverconcept
*

4
bench/tensors/README
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@ -17,10 +17,10 @@ following commands:
2. bash eigen_sycl_bench.sh
To compile the floating point GPU benchmarks using Intel DPCPP compiler
/path/to/dpcpp/bin/clang+ -DSYCL_COMPILER_IS_DPCPP -DNDEBUG -DEIGEN_MPL2_ONLY -DEIGEN_USE_SYCL=1 -I ../../ -O3 -DNDEBUG -fsycl -fsycl-targets="supported backend in DPCPP. i.e. spir64 or nvptx64-nvidia-cuda" -std=c++17 tensor_benchmarks_sycl.cc benchmark_main.cc -lpthread -o eigen_dpcpp_sycl
/path/to/dpcpp/bin/clang+ -DSYCL_COMPILER_IS_DPCPP -DNDEBUG -DEIGEN_USE_SYCL=1 -I ../../ -O3 -DNDEBUG -fsycl -fsycl-targets="supported backend in DPCPP. i.e. spir64 or nvptx64-nvidia-cuda" -std=c++17 tensor_benchmarks_sycl.cc benchmark_main.cc -lpthread -o eigen_dpcpp_sycl
Last but not least, we also provide a suite of benchmarks to measure the scalability of the contraction code on CPU. To compile these benchmarks, call
g++ contraction_benchmarks_cpu.cc benchmark_main.cc -I ../../ -std=c++11 -O3 -DNDEBUG -pthread -mavx -o benchmarks_cpu
To compile the contraction with DPCPP:
/path/to/dpcpp/bin/clang++ -DSYCL_COMPILER_IS_DPCPP -DNDEBUG -DEIGEN_MPL2_ONLY -DEIGEN_USE_SYCL=1 -I ../../ -O3 -DNDEBUG -fsycl -fsycl-targets="supported backend in DPCPP. i.e. spir64 or nvptx64-nvidia-cuda" -std=c++17 tensor_contract_sycl_bench.cc -lpthread -o eigen_dpcpp_contract
/path/to/dpcpp/bin/clang++ -DSYCL_COMPILER_IS_DPCPP -DNDEBUG -DEIGEN_USE_SYCL=1 -I ../../ -O3 -DNDEBUG -fsycl -fsycl-targets="supported backend in DPCPP. i.e. spir64 or nvptx64-nvidia-cuda" -std=c++17 tensor_contract_sycl_bench.cc -lpthread -o eigen_dpcpp_contract

1
bench/tensors/eigen_sycl_bench.sh
View File

@ -10,7 +10,6 @@ benchmark_main.cc \
-march=native \
-O3 \
-DNDEBUG \
-DEIGEN_MPL2_ONLY \
-DEIGEN_USE_SYCL=1 \
-DEIGEN_SYCL_LOCAL_MEM=1 \
-no-serial-memop \

2
bench/tensors/eigen_sycl_bench_contract.sh
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@ -1,7 +1,7 @@
rm -f tensor_contract_sycl_bench
: "${COMPUTECPP_PACKAGE_ROOT_DIR:?Need to set COMPUTECPP_PACKAGE_ROOT_DIR}"
echo "COMPUTECPP_PACKAGE_ROOT_DIR is set to: "$COMPUTECPP_PACKAGE_ROOT_DIR
${COMPUTECPP_PACKAGE_ROOT_DIR}/bin/compute++ tensor_contract_sycl_bench.cc -I ../../ -I ${COMPUTECPP_PACKAGE_ROOT_DIR}/include/ -std=c++11 -O3 -DNDEBUG -DEIGEN_MPL2_ONLY -DEIGEN_USE_SYCL=1 -no-serial-memop -mllvm -inline-threshold=10000 -fsycl-ih-last -sycl-driver -Xclang -cl-mad-enable -lOpenCL -lComputeCpp -lpthread -o tensor_contract_sycl_bench ${@:1}
${COMPUTECPP_PACKAGE_ROOT_DIR}/bin/compute++ tensor_contract_sycl_bench.cc -I ../../ -I ${COMPUTECPP_PACKAGE_ROOT_DIR}/include/ -std=c++11 -O3 -DNDEBUG -DEIGEN_USE_SYCL=1 -no-serial-memop -mllvm -inline-threshold=10000 -fsycl-ih-last -sycl-driver -Xclang -cl-mad-enable -lOpenCL -lComputeCpp -lpthread -o tensor_contract_sycl_bench ${@:1}
export LD_LIBRARY_PATH=${COMPUTECPP_PACKAGE_ROOT_DIR}/lib:$LD_LIBRARY_PATH
./tensor_contract_sycl_bench

3
doc/PreprocessorDirectives.dox
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@ -78,9 +78,6 @@ run time. However, these assertions do cost time and can thus be turned off.
- \b eigen_assert - macro with one argument that is used inside %Eigen for assertions. By default, it is
basically defined to be \c assert, which aborts the program if the assertion is violated. Redefine this
macro if you want to do something else, like throwing an exception.
- \b EIGEN_MPL2_ONLY - disable non MPL2 compatible features, or in other words disable the features which
are still under the LGPL.
\section TopicPreprocessorDirectivesPerformance Alignment, vectorization and performance tweaking

1
test/CMakeLists.txt
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@ -299,7 +299,6 @@ ei_add_test(special_numbers)
ei_add_test(rvalue_types)
ei_add_test(dense_storage)
ei_add_test(ctorleak)
ei_add_test(mpl2only)
ei_add_test(inplace_decomposition)
ei_add_test(half_float)
ei_add_test(bfloat16_float)

24
test/mpl2only.cpp
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@ -1,24 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_MPL2_ONLY
#define EIGEN_MPL2_ONLY
#endif
#include <Eigen/Dense>
#include <Eigen/SparseCore>
#include <Eigen/SparseLU>
#include <Eigen/SparseQR>
#include <Eigen/Sparse>
#include <Eigen/IterativeLinearSolvers>
#include <Eigen/Eigen>
int main()
{
return 0;
}

6
unsupported/Eigen/IterativeSolvers
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@ -19,7 +19,6 @@
* \defgroup IterativeLinearSolvers_Module Iterative Solvers module
* This module aims to provide various iterative linear and non linear solver algorithms.
* It currently provides:
* - a constrained conjugate gradient
* - a Householder GMRES implementation
* - an IDR(s) implementation
* - a BiCGSTAB(L) implementation
@ -79,11 +78,6 @@
#include "../../Eigen/src/Core/util/DisableStupidWarnings.h"
#ifndef EIGEN_MPL2_ONLY
#include "src/IterativeSolvers/IterationController.h"
#include "src/IterativeSolvers/ConstrainedConjGrad.h"
#endif
#include "src/IterativeSolvers/IncompleteLU.h"
#include "src/IterativeSolvers/GMRES.h"
#include "src/IterativeSolvers/DGMRES.h"

189
unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h
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@ -1,189 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
/* NOTE The functions of this file have been adapted from the GMM++ library */
//========================================================================
//
// Copyright (C) 2002-2007 Yves Renard
//
// This file is a part of GETFEM++
//
// Getfem++ is free software; you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as
// published by the Free Software Foundation; version 2.1 of the License.
//
// 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 Lesser General Public License for more details.
// You should have received a copy of the GNU Lesser General Public
// License along with this program; if not, write to the Free Software
// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301,
// USA.
//
//========================================================================
#include "../../../../Eigen/src/Core/util/NonMPL2.h"
#ifndef EIGEN_CONSTRAINEDCG_H
#define EIGEN_CONSTRAINEDCG_H
#include "../../../../Eigen/Core"
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
/** \ingroup IterativeLinearSolvers_Module
* Compute the pseudo inverse of the non-square matrix C such that
* \f$ CINV = (C * C^T)^{-1} * C \f$ based on a conjugate gradient method.
*
* This function is internally used by constrained_cg.
*/
template <typename CMatrix, typename CINVMatrix>
void pseudo_inverse(const CMatrix &C, CINVMatrix &CINV)
{
// optimisable : copie de la ligne, precalcul de C * trans(C).
typedef typename CMatrix::Scalar Scalar;
typedef typename CMatrix::Index Index;
// FIXME use sparse vectors ?
typedef Matrix<Scalar,Dynamic,1> TmpVec;
Index rows = C.rows(), cols = C.cols();
TmpVec d(rows), e(rows), l(cols), p(rows), q(rows), r(rows);
Scalar rho, rho_1, alpha;
d.setZero();
typedef Triplet<double> T;
std::vector<T> tripletList;
for (Index i = 0; i < rows; ++i)
{
d[i] = 1.0;
rho = 1.0;
e.setZero();
r = d;
p = d;
while (rho >= 1e-38)
{ /* conjugate gradient to compute e */
/* which is the i-th row of inv(C * trans(C)) */
l = C.transpose() * p;
q = C * l;
alpha = rho / p.dot(q);
e += alpha * p;
r += -alpha * q;
rho_1 = rho;
rho = r.dot(r);
p = (rho/rho_1) * p + r;
}
l = C.transpose() * e; // l is the i-th row of CINV
// FIXME add a generic "prune/filter" expression for both dense and sparse object to sparse
for (Index j=0; j<l.size(); ++j)
if (l[j]<1e-15)
tripletList.push_back(T(i,j,l(j)));
d[i] = 0.0;
}
CINV.setFromTriplets(tripletList.begin(), tripletList.end());
}
/** \ingroup IterativeLinearSolvers_Module
* Constrained conjugate gradient
*
* Computes the minimum of \f$ 1/2((Ax).x) - bx \f$ under the constraint \f$ Cx \le f \f$
*/
template<typename TMatrix, typename CMatrix,
typename VectorX, typename VectorB, typename VectorF>
void constrained_cg(const TMatrix& A, const CMatrix& C, VectorX& x,
const VectorB& b, const VectorF& f, IterationController &iter)
{
using std::sqrt;
typedef typename TMatrix::Scalar Scalar;
typedef typename TMatrix::Index Index;
typedef Matrix<Scalar,Dynamic,1> TmpVec;
Scalar rho = 1.0, rho_1, lambda, gamma;
Index xSize = x.size();
TmpVec p(xSize), q(xSize), q2(xSize),
r(xSize), old_z(xSize), z(xSize),
memox(xSize);
std::vector<bool> satured(C.rows());
p.setZero();
iter.setRhsNorm(sqrt(b.dot(b))); // gael vect_sp(PS, b, b)
if (iter.rhsNorm() == 0.0) iter.setRhsNorm(1.0);
SparseMatrix<Scalar,RowMajor> CINV(C.rows(), C.cols());
pseudo_inverse(C, CINV);
while(true)
{
// computation of residual
old_z = z;
memox = x;
r = b;
r += A * -x;
z = r;
bool transition = false;
for (Index i = 0; i < C.rows(); ++i)
{
Scalar al = C.row(i).dot(x) - f.coeff(i);
if (al >= -1.0E-15)
{
if (!satured[i])
{
satured[i] = true;
transition = true;
}
Scalar bb = CINV.row(i).dot(z);
if (bb > 0.0)
// FIXME: we should allow that: z += -bb * C.row(i);
for (typename CMatrix::InnerIterator it(C,i); it; ++it)
z.coeffRef(it.index()) -= bb*it.value();
}
else
satured[i] = false;
}
// descent direction
rho_1 = rho;
rho = r.dot(z);
if (iter.finished(rho)) break;
if (transition || iter.first()) gamma = 0.0;
else gamma = (std::max)(0.0, (rho - old_z.dot(z)) / rho_1);
p = z + gamma*p;
++iter;
// one dimensional optimization
q = A * p;
lambda = rho / q.dot(p);
for (Index i = 0; i < C.rows(); ++i)
{
if (!satured[i])
{
Scalar bb = C.row(i).dot(p) - f[i];
if (bb > 0.0)
lambda = (std::min)(lambda, (f.coeff(i)-C.row(i).dot(x)) / bb);
}
}
x += lambda * p;
memox -= x;
}
}
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_CONSTRAINEDCG_H

156
unsupported/Eigen/src/IterativeSolvers/IterationController.h
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@ -1,156 +0,0 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
/* NOTE The class IterationController has been adapted from the iteration
* class of the GMM++ and ITL libraries.
*/
//=======================================================================
// Copyright (C) 1997-2001
// Authors: Andrew Lumsdaine <lums@osl.iu.edu>
// Lie-Quan Lee <llee@osl.iu.edu>
//
// This file is part of the Iterative Template Library
//
// You should have received a copy of the License Agreement for the
// Iterative Template Library along with the software; see the
// file LICENSE.
//
// Permission to modify the code and to distribute modified code is
// granted, provided the text of this NOTICE is retained, a notice that
// the code was modified is included with the above COPYRIGHT NOTICE and
// with the COPYRIGHT NOTICE in the LICENSE file, and that the LICENSE
// file is distributed with the modified code.
//
// LICENSOR MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED.
// By way of example, but not limitation, Licensor MAKES NO
// REPRESENTATIONS OR WARRANTIES OF MERCHANTABILITY OR FITNESS FOR ANY
// PARTICULAR PURPOSE OR THAT THE USE OF THE LICENSED SOFTWARE COMPONENTS
// OR DOCUMENTATION WILL NOT INFRINGE ANY PATENTS, COPYRIGHTS, TRADEMARKS
// OR OTHER RIGHTS.
//=======================================================================
//========================================================================
//
// Copyright (C) 2002-2007 Yves Renard
//
// This file is a part of GETFEM++
//
// Getfem++ is free software; you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as
// published by the Free Software Foundation; version 2.1 of the License.
//
// 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 Lesser General Public License for more details.
// You should have received a copy of the GNU Lesser General Public
// License along with this program; if not, write to the Free Software
// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301,
// USA.
//
//========================================================================
#include "../../../../Eigen/src/Core/util/NonMPL2.h"
#ifndef EIGEN_ITERATION_CONTROLLER_H
#define EIGEN_ITERATION_CONTROLLER_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \ingroup IterativeLinearSolvers_Module
* \class IterationController
*
* \brief Controls the iterations of the iterative solvers
*
* This class has been adapted from the iteration class of GMM++ and ITL libraries.
*
*/
class IterationController
{
protected :
double m_rhsn; ///< Right hand side norm
size_t m_maxiter; ///< Max. number of iterations
int m_noise; ///< if noise > 0 iterations are printed
double m_resmax; ///< maximum residual
double m_resminreach, m_resadd;
size_t m_nit; ///< iteration number
double m_res; ///< last computed residual
bool m_written;
void (*m_callback)(const IterationController&);
public :
void init()
{
m_nit = 0; m_res = 0.0; m_written = false;
m_resminreach = 1E50; m_resadd = 0.0;
m_callback = 0;
}
IterationController(double r = 1.0E-8, int noi = 0, size_t mit = size_t(-1))
: m_rhsn(1.0), m_maxiter(mit), m_noise(noi), m_resmax(r) { init(); }
void operator ++(int) { m_nit++; m_written = false; m_resadd += m_res; }
void operator ++() { (*this)++; }
bool first() { return m_nit == 0; }
/* get/set the "noisyness" (verbosity) of the solvers */
int noiseLevel() const { return m_noise; }
void setNoiseLevel(int n) { m_noise = n; }
void reduceNoiseLevel() { if (m_noise > 0) m_noise--; }
double maxResidual() const { return m_resmax; }
void setMaxResidual(double r) { m_resmax = r; }
double residual() const { return m_res; }
/* change the user-definable callback, called after each iteration */
void setCallback(void (*t)(const IterationController&))
{
m_callback = t;
}
size_t iteration() const { return m_nit; }
void setIteration(size_t i) { m_nit = i; }
size_t maxIterarions() const { return m_maxiter; }
void setMaxIterations(size_t i) { m_maxiter = i; }
double rhsNorm() const { return m_rhsn; }
void setRhsNorm(double r) { m_rhsn = r; }
bool converged() const { return m_res <= m_rhsn * m_resmax; }
bool converged(double nr)
{
using std::abs;
m_res = abs(nr);
m_resminreach = (std::min)(m_resminreach, m_res);
return converged();
}
template<typename VectorType> bool converged(const VectorType &v)
{ return converged(v.squaredNorm()); }
bool finished(double nr)
{
if (m_callback) m_callback(*this);
if (m_noise > 0 && !m_written)
{
converged(nr);
m_written = true;
}
return (m_nit >= m_maxiter || converged(nr));
}
template <typename VectorType>
bool finished(const MatrixBase<VectorType> &v)
{ return finished(double(v.squaredNorm())); }
};
} // end namespace Eigen
#endif // EIGEN_ITERATION_CONTROLLER_H