From bb234945233bf2f929440f62e3d9643c61ad8d1e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Tom=C3=A1=C5=A1=20Oberhuber?= <oberhuber.tomas@gmail.com>
Date: Tue, 21 Jan 2020 22:17:46 +0100
Subject: [PATCH] Implementing dense matrix assignment.
---
src/TNL/Matrices/Dense.h | 27 ++-
src/TNL/Matrices/Dense.hpp | 220 ++++++++++++-------
src/TNL/Matrices/Multidiagonal.h | 3 +
src/TNL/Matrices/Multidiagonal.hpp | 14 ++
src/TNL/Matrices/MultidiagonalMatrixView.h | 3 +
src/TNL/Matrices/MultidiagonalMatrixView.hpp | 16 +-
src/TNL/Matrices/Tridiagonal.h | 3 +
src/TNL/Matrices/Tridiagonal.hpp | 16 +-
src/TNL/Matrices/TridiagonalMatrixView.h | 3 +
src/TNL/Matrices/TridiagonalMatrixView.hpp | 16 +-
src/UnitTests/Matrices/DenseMatrixCopyTest.h | 52 +++--
11 files changed, 276 insertions(+), 97 deletions(-)
diff --git a/src/TNL/Matrices/Dense.h b/src/TNL/Matrices/Dense.h
index 2e71316e94..8c109ac1e3 100644
--- a/src/TNL/Matrices/Dense.h
+++ b/src/TNL/Matrices/Dense.h
@@ -167,12 +167,31 @@ class Dense : public Matrix< Real, Device, Index >
Vector2& x,
const RealType& omega = 1.0 ) const;
- // copy assignment
+ /**
+ * \brief Assignment operator for exactly the same type of the dense matrix.
+ *
+ * @param matrix
+ * @return
+ */
Dense& operator=( const Dense& matrix );
- // cross-device copy assignment
- template< typename Real_, typename Device_, typename Index_, bool RowMajorOrder_, typename RealAlocator_ >
- Dense& operator=( const Dense< Real_, Device_, Index_, RowMajorOrder_, RealAlocator_ >& matrix );
+ /**
+ * \brief Assignment operator for other dense matrices.
+ *
+ * @param matrix
+ * @return
+ */
+ template< typename RHSReal, typename RHSDevice, typename RHSIndex,
+ bool RHSRowMajorOrder, typename RHSRealAllocator >
+ Dense& operator=( const Dense< RHSReal, RHSDevice, RHSIndex, RHSRowMajorOrder, RHSRealAllocator >& matrix );
+
+ /**
+ * \brief Assignment operator for other (sparse) types of matrices.
+ * @param matrix
+ * @return
+ */
+ template< typename RHSMatrix >
+ Dense& operator=( const RHSMatrix& matrix );
template< typename Real_, typename Device_, typename Index_, typename RealAllocator_ >
bool operator==( const Dense< Real_, Device_, Index_, RowMajorOrder >& matrix ) const;
diff --git a/src/TNL/Matrices/Dense.hpp b/src/TNL/Matrices/Dense.hpp
index 3d9ff102ed..e1acfee67e 100644
--- a/src/TNL/Matrices/Dense.hpp
+++ b/src/TNL/Matrices/Dense.hpp
@@ -118,7 +118,7 @@ void
Dense< Real, Device, Index, RowMajorOrder, RealAllocator >::
setLike( const Matrix_& matrix )
{
- Matrix< Real, Device, Index, RealAllocator >::setLike( matrix );
+ this->setDimensions( matrix.getRows(), matrix.getColumns() );
}
template< typename Real,
@@ -896,39 +896,81 @@ operator=( const Dense< Real, Device, Index, RowMajorOrder, RealAllocator >& mat
{
setLike( matrix );
this->values = matrix.values;
- /*const IndexType bufferRowsCount( 128 );
- const IndexType columns = this->getColumns();
- const size_t bufferSize = bufferRowsCount * columns;
- Containers::Vector< RealType, Device, IndexType, RealAllocatorType > sourceValuesBuffer( bufferSize );
- Containers::Vector< RealType, DeviceType, IndexType, RealAllocatorType > destinationValuesBuffer( bufferSize );
- auto sourceValuesBuffer_view = sourceValuesBuffer.getView();
- auto destinationValuesBuffer_view = destinationValuesBuffer.getView();
-
- IndexType baseRow( 0 );
- const IndexType rowsCount = this->getRows();
- while( baseRow < rowsCount )
+ return *this;
+}
+
+template< typename Real,
+ typename Device,
+ typename Index,
+ bool RowMajorOrder,
+ typename RealAllocator >
+ template< typename RHSReal, typename RHSDevice, typename RHSIndex,
+ bool RHSRowMajorOrder, typename RHSRealAllocator >
+Dense< Real, Device, Index, RowMajorOrder, RealAllocator >&
+Dense< Real, Device, Index, RowMajorOrder, RealAllocator >::
+operator=( const Dense< RHSReal, RHSDevice, RHSIndex, RHSRowMajorOrder, RHSRealAllocator >& matrix )
+{
+ using RHSMatrix = Dense< RHSReal, RHSDevice, RHSIndex, RHSRowMajorOrder, RHSRealAllocator >;
+ using RHSIndexType = typename RHSMatrix::IndexType;
+ using RHSRealType = typename RHSMatrix::RealType;
+ using RHSDeviceType = typename RHSMatrix::DeviceType;
+
+ this->setLike( matrix );
+ if( RowMajorOrder == RHSRowMajorOrder )
{
- const IndexType lastRow = min( baseRow + bufferRowsCount, rowsCount );
+ this->values = matrix.values;
+ return *this;
+ }
- ////
- // Copy matrix elements into buffer
- auto f1 = [=] __cuda_callable__ ( Index rowIdx, Index columnIdx, Index globalIdx, const Real& value ) mutable {
- const IndexType bufferIdx = ( rowIdx - baseRow ) * columns + columnIdx;
- sourceValuesBuffer_view[ bufferIdx ] = value;
- };
- matrix.forRows( baseRow, lastRow, f1 );
- destinationValuesBuffer = sourceValuesBuffer;
-
- ////
- // Copy buffer to this matrix
- auto f2 = [=] __cuda_callable__ ( IndexType rowIdx, IndexType columnIdx, IndexType globalIdx, RealType& value ) mutable {
- const IndexType bufferIdx = ( rowIdx - baseRow ) * columns + columnIdx;
- value = destinationValuesBuffer_view[ bufferIdx ];
+ auto this_view = this->view;
+ if( std::is_same< DeviceType, RHSDeviceType >::value )
+ {
+ const auto segments_view = this->segments.getView();
+ auto f = [=] __cuda_callable__ ( RHSIndexType rowIdx, RHSIndexType localIdx, RHSIndexType columnIdx, const RHSRealType& value, bool& compute ) mutable {
+ this_view( rowIdx, columnIdx ) = value;
};
- this->forRows( baseRow, lastRow, f2 );
- baseRow += bufferRowsCount;
+ matrix.forAllRows( f );
}
- return *this;*/
+ else
+ {
+ const IndexType maxRowLength = matrix.getColumns();
+ const IndexType bufferRowsCount( 128 );
+ const size_t bufferSize = bufferRowsCount * maxRowLength;
+ Containers::Vector< RHSRealType, RHSDeviceType, RHSIndexType > matrixValuesBuffer( bufferSize );
+ Containers::Vector< RealType, DeviceType, IndexType > thisValuesBuffer( bufferSize );
+ auto matrixValuesBuffer_view = matrixValuesBuffer.getView();
+ auto thisValuesBuffer_view = thisValuesBuffer.getView();
+
+ IndexType baseRow( 0 );
+ const IndexType rowsCount = this->getRows();
+ while( baseRow < rowsCount )
+ {
+ const IndexType lastRow = min( baseRow + bufferRowsCount, rowsCount );
+
+ ////
+ // Copy matrix elements into buffer
+ auto f1 = [=] __cuda_callable__ ( RHSIndexType rowIdx, RHSIndexType localIdx, RHSIndexType columnIdx, const RHSRealType& value, bool& compute ) mutable {
+ const IndexType bufferIdx = ( rowIdx - baseRow ) * maxRowLength + columnIdx;
+ matrixValuesBuffer_view[ bufferIdx ] = value;
+ };
+ matrix.forRows( baseRow, lastRow, f1 );
+
+ ////
+ // Copy the source matrix buffer to this matrix buffer
+ thisValuesBuffer_view = matrixValuesBuffer_view;
+
+ ////
+ // Copy matrix elements from the buffer to the matrix.
+ auto this_view = this->view;
+ auto f2 = [=] __cuda_callable__ ( IndexType columnIdx, IndexType bufferRowIdx ) mutable {
+ IndexType bufferIdx = bufferRowIdx * maxRowLength + columnIdx;
+ this_view( baseRow + bufferRowIdx, columnIdx ) = thisValuesBuffer_view[ bufferIdx ];
+ };
+ Algorithms::ParallelFor2D< DeviceType >::exec( ( IndexType ) 0, ( IndexType ) 0, ( IndexType ) maxRowLength, ( IndexType ) min( bufferRowsCount, this->getRows() - baseRow ), f2 );
+ baseRow += bufferRowsCount;
+ }
+ }
+ return *this;
}
template< typename Real,
@@ -936,59 +978,85 @@ template< typename Real,
typename Index,
bool RowMajorOrder,
typename RealAllocator >
- template< typename Real_, typename Device_, typename Index_, bool RowMajorOrder_, typename RealAllocator_ >
+ template< typename RHSMatrix >
Dense< Real, Device, Index, RowMajorOrder, RealAllocator >&
Dense< Real, Device, Index, RowMajorOrder, RealAllocator >::
-operator=( const Dense< Real_, Device_, Index_, RowMajorOrder_, RealAllocator_ >& matrix )
+operator=( const RHSMatrix& matrix )
{
- this->setLike( matrix );
- if( RowMajorOrder == RowMajorOrder_ )
- this->values = matrix.getValues();
+ using RHSIndexType = typename RHSMatrix::IndexType;
+ using RHSRealType = typename RHSMatrix::RealType;
+ using RHSDeviceType = typename RHSMatrix::DeviceType;
+ using RHSRealAllocatorType = typename RHSMatrix::RealAllocatorType;
+
+ Containers::Vector< RHSIndexType, RHSDeviceType, RHSIndexType > rowLengths;
+ matrix.getCompressedRowLengths( rowLengths );
+ this->setDimensions( matrix.getRows(), matrix.getColumns() );
+
+ // TODO: use getConstView when it works
+ const auto matrixView = const_cast< RHSMatrix& >( matrix ).getView();
+ auto values_view = this->values.getView();
+ RHSIndexType padding_index = matrix.getPaddingIndex();
+ this->values = 0.0;
+
+ if( std::is_same< DeviceType, RHSDeviceType >::value )
+ {
+ const auto segments_view = this->segments.getView();
+ auto f = [=] __cuda_callable__ ( RHSIndexType rowIdx, RHSIndexType localIdx_, RHSIndexType columnIdx, const RHSRealType& value, bool& compute ) mutable {
+ if( value != 0.0 && columnIdx != padding_index )
+ values_view[ segments_view.getGlobalIndex( rowIdx, columnIdx ) ] = value;
+ };
+ matrix.forAllRows( f );
+ }
else
{
- if( std::is_same< DeviceType, Device_ >::value )
+ const IndexType maxRowLength = max( rowLengths );
+ const IndexType bufferRowsCount( 128 );
+ const size_t bufferSize = bufferRowsCount * maxRowLength;
+ Containers::Vector< RHSRealType, RHSDeviceType, RHSIndexType, RHSRealAllocatorType > matrixValuesBuffer( bufferSize );
+ Containers::Vector< RHSIndexType, RHSDeviceType, RHSIndexType > matrixColumnsBuffer( bufferSize );
+ Containers::Vector< RealType, DeviceType, IndexType, RealAllocatorType > thisValuesBuffer( bufferSize );
+ Containers::Vector< IndexType, DeviceType, IndexType > thisColumnsBuffer( bufferSize );
+ auto matrixValuesBuffer_view = matrixValuesBuffer.getView();
+ auto matrixColumnsBuffer_view = matrixColumnsBuffer.getView();
+ auto thisValuesBuffer_view = thisValuesBuffer.getView();
+ auto thisColumnsBuffer_view = thisColumnsBuffer.getView();
+
+ IndexType baseRow( 0 );
+ const IndexType rowsCount = this->getRows();
+ while( baseRow < rowsCount )
{
- auto this_view = this->getView();
- auto f = [=] __cuda_callable__ ( Index_ rowIdx, Index_ columnIdx, Index_ globalIdx, const Real_& value, bool& compute ) mutable {
- this_view.getRow( rowIdx ).setElement( columnIdx, value );
+ const IndexType lastRow = min( baseRow + bufferRowsCount, rowsCount );
+ thisColumnsBuffer = padding_index;
+ matrixColumnsBuffer_view = padding_index;
+
+ ////
+ // Copy matrix elements into buffer
+ auto f1 = [=] __cuda_callable__ ( RHSIndexType rowIdx, RHSIndexType localIdx, RHSIndexType columnIndex, const RHSRealType& value, bool& compute ) mutable {
+ if( columnIndex != padding_index )
+ {
+ const IndexType bufferIdx = ( rowIdx - baseRow ) * maxRowLength + localIdx;
+ matrixColumnsBuffer_view[ bufferIdx ] = columnIndex;
+ matrixValuesBuffer_view[ bufferIdx ] = value;
+ }
};
- matrix.forAllRows( f );
- }
- else
- {
- const IndexType bufferRowsCount( 128 );
- const IndexType columns = this->getColumns();
- const size_t bufferSize = bufferRowsCount * columns;
- Containers::Vector< RealType, Device_, IndexType, RealAllocator_ > sourceValuesBuffer( bufferSize );
- Containers::Vector< RealType, DeviceType, IndexType, RealAllocatorType > destinationValuesBuffer( bufferSize );
- auto sourceValuesBuffer_view = sourceValuesBuffer.getView();
- auto destinationValuesBuffer_view = destinationValuesBuffer.getView();
-
- IndexType baseRow( 0 );
- const IndexType rowsCount = this->getRows();
- while( baseRow < rowsCount )
- {
- const IndexType lastRow = min( baseRow + bufferRowsCount, rowsCount );
-
- ////
- // Copy matrix elements into buffer
- auto f1 = [=] __cuda_callable__ ( Index_ rowIdx, Index_ columnIdx, Index_ globalIdx, const Real_& value, bool& compute ) mutable {
- const IndexType bufferIdx = ( rowIdx - baseRow ) * columns + columnIdx;
- sourceValuesBuffer_view[ bufferIdx ] = value;
- };
- matrix.forRows( baseRow, lastRow, f1 );
-
- destinationValuesBuffer = sourceValuesBuffer;
-
- ////
- // Copy buffer to this matrix
- auto f2 = [=] __cuda_callable__ ( IndexType rowIdx, IndexType columnIdx, IndexType globalIdx, RealType& value, bool& compute ) mutable {
- const IndexType bufferIdx = ( rowIdx - baseRow ) * columns + columnIdx;
- value = destinationValuesBuffer_view[ bufferIdx ];
- };
- this->forRows( baseRow, lastRow, f2 );
- baseRow += bufferRowsCount;
- }
+ matrix.forRows( baseRow, lastRow, f1 );
+
+ ////
+ // Copy the source matrix buffer to this matrix buffer
+ thisValuesBuffer_view = matrixValuesBuffer_view;
+ thisColumnsBuffer_view = matrixColumnsBuffer_view;
+
+ ////
+ // Copy matrix elements from the buffer to the matrix
+ auto this_view = this->view;
+ auto f2 = [=] __cuda_callable__ ( IndexType bufferColumnIdx, IndexType bufferRowIdx ) mutable {
+ IndexType bufferIdx = bufferRowIdx * maxRowLength + bufferColumnIdx;
+ IndexType columnIdx = thisColumnsBuffer_view[ bufferIdx ];
+ if( columnIdx != padding_index )
+ this_view( baseRow + bufferRowIdx, columnIdx ) = thisValuesBuffer_view[ bufferIdx ];
+ };
+ Algorithms::ParallelFor2D< DeviceType >::exec( ( IndexType ) 0, ( IndexType ) 0, ( IndexType ) maxRowLength, ( IndexType ) min( bufferRowsCount, this->getRows() - baseRow ), f2 );
+ baseRow += bufferRowsCount;
}
}
this->view = this->getView();
diff --git a/src/TNL/Matrices/Multidiagonal.h b/src/TNL/Matrices/Multidiagonal.h
index 9e5f922959..927e524491 100644
--- a/src/TNL/Matrices/Multidiagonal.h
+++ b/src/TNL/Matrices/Multidiagonal.h
@@ -201,6 +201,9 @@ class Multidiagonal : public Matrix< Real, Device, Index, RealAllocator >
IndexerType& getIndexer();
+ __cuda_callable__
+ IndexType getPaddingIndex() const;
+
protected:
__cuda_callable__
diff --git a/src/TNL/Matrices/Multidiagonal.hpp b/src/TNL/Matrices/Multidiagonal.hpp
index 94470d3d1c..5d83004f29 100644
--- a/src/TNL/Matrices/Multidiagonal.hpp
+++ b/src/TNL/Matrices/Multidiagonal.hpp
@@ -830,6 +830,20 @@ getElementIndex( const IndexType row, const IndexType column ) const
return this->indexer.getGlobalIndex( row, localIdx );
}
+template< typename Real,
+ typename Device,
+ typename Index,
+ bool RowMajorOrder,
+ typename RealAllocator,
+ typename IndexAllocator >
+__cuda_callable__
+Index
+Multidiagonal< Real, Device, Index, RowMajorOrder, RealAllocator, IndexAllocator >::
+getPaddingIndex() const
+{
+ return this->view.getPaddingIndex();
+}
+
/*
template<>
class MultidiagonalDeviceDependentCode< Devices::Host >
diff --git a/src/TNL/Matrices/MultidiagonalMatrixView.h b/src/TNL/Matrices/MultidiagonalMatrixView.h
index 1e5a9bd28e..f623a3ca66 100644
--- a/src/TNL/Matrices/MultidiagonalMatrixView.h
+++ b/src/TNL/Matrices/MultidiagonalMatrixView.h
@@ -163,6 +163,9 @@ class MultidiagonalMatrixView : public MatrixView< Real, Device, Index >
__cuda_callable__
IndexerType& getIndexer();
+ __cuda_callable__
+ IndexType getPaddingIndex() const;
+
protected:
__cuda_callable__
diff --git a/src/TNL/Matrices/MultidiagonalMatrixView.hpp b/src/TNL/Matrices/MultidiagonalMatrixView.hpp
index 2243684654..f35c6d713f 100644
--- a/src/TNL/Matrices/MultidiagonalMatrixView.hpp
+++ b/src/TNL/Matrices/MultidiagonalMatrixView.hpp
@@ -713,11 +713,25 @@ template< typename Real,
typename Index,
bool RowMajorOrder >
__cuda_callable__
-Index MultidiagonalMatrixView< Real, Device, Index, RowMajorOrder >::
+Index
+MultidiagonalMatrixView< Real, Device, Index, RowMajorOrder >::
getElementIndex( const IndexType row, const IndexType localIdx ) const
{
return this->indexer.getGlobalIndex( row, localIdx );
}
+template< typename Real,
+ typename Device,
+ typename Index,
+ bool RowMajorOrder >
+__cuda_callable__
+Index
+MultidiagonalMatrixView< Real, Device, Index, RowMajorOrder >::
+getPaddingIndex() const
+{
+ return -1;
+}
+
+
} // namespace Matrices
} // namespace TNL
diff --git a/src/TNL/Matrices/Tridiagonal.h b/src/TNL/Matrices/Tridiagonal.h
index 82549e7445..3f89023106 100644
--- a/src/TNL/Matrices/Tridiagonal.h
+++ b/src/TNL/Matrices/Tridiagonal.h
@@ -174,6 +174,9 @@ class Tridiagonal : public Matrix< Real, Device, Index, RealAllocator >
IndexerType& getIndexer();
+ __cuda_callable__
+ IndexType getPaddingIndex() const;
+
protected:
__cuda_callable__
diff --git a/src/TNL/Matrices/Tridiagonal.hpp b/src/TNL/Matrices/Tridiagonal.hpp
index 8f4f4e190b..d99715a47c 100644
--- a/src/TNL/Matrices/Tridiagonal.hpp
+++ b/src/TNL/Matrices/Tridiagonal.hpp
@@ -678,7 +678,8 @@ template< typename Real,
bool RowMajorOrder,
typename RealAllocator >
__cuda_callable__
-Index Tridiagonal< Real, Device, Index, RowMajorOrder, RealAllocator >::
+Index
+Tridiagonal< Real, Device, Index, RowMajorOrder, RealAllocator >::
getElementIndex( const IndexType row, const IndexType column ) const
{
IndexType localIdx = column - row;
@@ -691,6 +692,19 @@ getElementIndex( const IndexType row, const IndexType column ) const
return this->indexer.getGlobalIndex( row, localIdx );
}
+template< typename Real,
+ typename Device,
+ typename Index,
+ bool RowMajorOrder,
+ typename RealAllocator >
+__cuda_callable__
+Index
+Tridiagonal< Real, Device, Index, RowMajorOrder, RealAllocator >::
+getPaddingIndex() const
+{
+ return this->view.getPaddingIndex();
+}
+
/*
template<>
class TridiagonalDeviceDependentCode< Devices::Host >
diff --git a/src/TNL/Matrices/TridiagonalMatrixView.h b/src/TNL/Matrices/TridiagonalMatrixView.h
index 61b005c5a7..82b76c73f7 100644
--- a/src/TNL/Matrices/TridiagonalMatrixView.h
+++ b/src/TNL/Matrices/TridiagonalMatrixView.h
@@ -151,6 +151,9 @@ class TridiagonalMatrixView : public MatrixView< Real, Device, Index >
__cuda_callable__
IndexerType& getIndexer();
+ __cuda_callable__
+ IndexType getPaddingIndex() const;
+
protected:
__cuda_callable__
diff --git a/src/TNL/Matrices/TridiagonalMatrixView.hpp b/src/TNL/Matrices/TridiagonalMatrixView.hpp
index 7fc5fd6b7b..6e293ffd03 100644
--- a/src/TNL/Matrices/TridiagonalMatrixView.hpp
+++ b/src/TNL/Matrices/TridiagonalMatrixView.hpp
@@ -675,7 +675,8 @@ template< typename Real,
typename Index,
bool RowMajorOrder >
__cuda_callable__
-Index TridiagonalMatrixView< Real, Device, Index, RowMajorOrder >::
+Index
+TridiagonalMatrixView< Real, Device, Index, RowMajorOrder >::
getElementIndex( const IndexType row, const IndexType column ) const
{
IndexType localIdx = column - row;
@@ -688,5 +689,18 @@ getElementIndex( const IndexType row, const IndexType column ) const
return this->indexer.getGlobalIndex( row, localIdx );
}
+template< typename Real,
+ typename Device,
+ typename Index,
+ bool RowMajorOrder >
+__cuda_callable__
+Index
+TridiagonalMatrixView< Real, Device, Index, RowMajorOrder >::
+getPaddingIndex() const
+{
+ return -1;
+}
+
+
} // namespace Matrices
} // namespace TNL
diff --git a/src/UnitTests/Matrices/DenseMatrixCopyTest.h b/src/UnitTests/Matrices/DenseMatrixCopyTest.h
index ef7809a6b5..3ef31f1075 100644
--- a/src/UnitTests/Matrices/DenseMatrixCopyTest.h
+++ b/src/UnitTests/Matrices/DenseMatrixCopyTest.h
@@ -59,9 +59,20 @@ using Dense_cuda_RowMajorOrder = TNL::Matrices::Dense< int, TNL::Devices::Cuda,
template< typename Matrix >
void setupUnevenRowSizeMatrix( Matrix& m )
{
- const int rows = 10;
- const int cols = 6;
- m.setDimensions( rows, cols );
+ const int rows = 10;
+ const int cols = 6;
+ m.setDimensions( rows, cols );
+ typename Matrix::CompressedRowLengthsVector rowLengths;
+ rowLengths.setSize( rows );
+ rowLengths.setValue( 5 );
+ rowLengths.setElement( 0, 2 );
+ rowLengths.setElement( 1, 3 );
+ rowLengths.setElement( 2, 3 );
+ rowLengths.setElement( 5, 2 );
+ rowLengths.setElement( 6, 1 );
+ rowLengths.setElement( 7, 1 );
+ rowLengths.setElement( 9, 1 );
+ m.setCompressedRowLengths( rowLengths );
int value = 1;
for( int i = 0; i < cols - 4; i++ ) // 0th row
@@ -183,15 +194,21 @@ void checkUnevenRowSizeMatrix( Matrix& m )
template< typename Matrix >
void setupAntiTriDiagMatrix( Matrix& m )
{
- const int rows = 7;
- const int cols = 6;
- m.setDimensions( rows, cols );
+ const int rows = 7;
+ const int cols = 6;
+ m.setDimensions( rows, cols );
+ typename Matrix::CompressedRowLengthsVector rowLengths;
+ rowLengths.setSize( rows );
+ rowLengths.setValue( 3 );
+ rowLengths.setElement( 0, 4);
+ rowLengths.setElement( 1, 4 );
+ m.setCompressedRowLengths( rowLengths );
- int value = 1;
- for( int i = 0; i < rows; i++ )
- for( int j = cols - 1; j > 2; j-- )
- if( j - i + 1 < cols && j - i + 1 >= 0 )
- m.setElement( i, j - i + 1, value++ );
+ int value = 1;
+ for( int i = 0; i < rows; i++ )
+ for( int j = cols - 1; j > 2; j-- )
+ if( j - i + 1 < cols && j - i + 1 >= 0 )
+ m.setElement( i, j - i + 1, value++ );
}
template< typename Matrix >
@@ -267,6 +284,13 @@ void setupTriDiagMatrix( Matrix& m )
const int rows = 7;
const int cols = 6;
m.setDimensions( rows, cols );
+ typename Matrix::CompressedRowLengthsVector rowLengths;
+ rowLengths.setSize( rows );
+ rowLengths.setValue( 3 );
+ rowLengths.setElement( 0 , 4 );
+ rowLengths.setElement( 1, 4 );
+ m.setCompressedRowLengths( rowLengths );
+
int value = 1;
for( int i = 0; i < rows; i++ )
@@ -387,7 +411,7 @@ void tridiagonalMatrixAssignment()
Matrix matrix;
matrix = hostMatrix;
- using RowCapacitiesType = typename Matrix::RowsCapacitiesType;
+ using RowCapacitiesType = TNL::Containers::Vector< IndexType, DeviceType, IndexType >;
RowCapacitiesType rowCapacities;
matrix.getCompressedRowLengths( rowCapacities );
RowCapacitiesType exactRowLengths{ 1, 3, 3, 3, 3, 3, 3, 3, 3, 2 };
@@ -439,7 +463,7 @@ void multidiagonalMatrixAssignment()
Matrix matrix;
matrix = hostMatrix;
- using RowCapacitiesType = typename Matrix::RowsCapacitiesType;
+ using RowCapacitiesType = TNL::Containers::Vector< IndexType, DeviceType, IndexType >;
RowCapacitiesType rowCapacities;
matrix.getCompressedRowLengths( rowCapacities );
RowCapacitiesType exactRowLengths{ 3, 4, 5, 5, 6, 5, 5, 4, 4, 3 };
@@ -488,7 +512,7 @@ void denseMatrixAssignment()
Matrix matrix;
matrix = hostMatrix;
- using RowCapacitiesType = typename Matrix::RowsCapacitiesType;
+ using RowCapacitiesType = TNL::Containers::Vector< IndexType, DeviceType, IndexType >;
RowCapacitiesType rowCapacities;
matrix.getCompressedRowLengths( rowCapacities );
RowCapacitiesType exactRowLengths{ 0, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
--
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