Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 123456789]

►Cgko::AbsoluteComputable	The AbsoluteComputable is an interface that allows to get the component wise absolute of a LinOp
►Cgko::EnableAbsoluteComputation< remove_complex< Coo< ValueType, IndexType > > >
Cgko::matrix::Coo< ValueType, IndexType >	COO stores a matrix in the coordinate matrix format
►Cgko::EnableAbsoluteComputation< remove_complex< Csr< ValueType, IndexType > > >
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
►Cgko::EnableAbsoluteComputation< remove_complex< Dense< ValueType > > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::EnableAbsoluteComputation< remove_complex< Diagonal< ValueType > > >
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
►Cgko::EnableAbsoluteComputation< remove_complex< Ell< ValueType, IndexType > > >
Cgko::matrix::Ell< ValueType, IndexType >	ELL is a matrix format where stride with explicit zeros is used such that all rows have the same number of stored elements
►Cgko::EnableAbsoluteComputation< remove_complex< Fbcsr< ValueType, IndexType > > >
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
►Cgko::EnableAbsoluteComputation< remove_complex< Hybrid< ValueType, IndexType > > >
Cgko::matrix::Hybrid< ValueType, IndexType >	HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
►Cgko::EnableAbsoluteComputation< remove_complex< Sellp< ValueType, IndexType > > >
Cgko::matrix::Sellp< ValueType, IndexType >	SELL-P is a matrix format similar to ELL format
►Cgko::EnableAbsoluteComputation< remove_complex< Vector< ValueType > > >
Cgko::experimental::distributed::Vector< ValueType >	Vector is a format which explicitly stores (multiple) distributed column vectors in a dense storage format
►Cgko::EnableAbsoluteComputation< AbsoluteLinOp >	The EnableAbsoluteComputation mixin provides the default implementations of compute_absolute_linop and the absolute interface
Cgko::matrix::Dense< value_type >
►Cgko::Allocator	Provides generic allocation and deallocation functionality to be used by an Executor
►Cgko::CpuAllocatorBase	Implement this interface to provide an allocator for OmpExecutor or ReferenceExecutor
Cgko::CpuAllocator	Allocator using new/delete
Cgko::CudaHostAllocator
Cgko::CudaUnifiedAllocator
Cgko::HipHostAllocator
Cgko::HipUnifiedAllocator
►Cgko::CudaAllocatorBase	Implement this interface to provide an allocator for CudaExecutor
Cgko::CudaAllocator	Allocator using cudaMalloc
Cgko::CudaAsyncAllocator
Cgko::CudaHostAllocator
Cgko::CudaUnifiedAllocator
►Cgko::HipAllocatorBase	Implement this interface to provide an allocator for HipExecutor
Cgko::HipAllocator
Cgko::HipAsyncAllocator
Cgko::HipHostAllocator
Cgko::HipUnifiedAllocator
Cgko::amd_device	Amd_device handles the number of executor on Amd devices and have the corresponding recursive_mutex
►Cgko::solver::ApplyWithInitialGuess	ApplyWithInitialGuess provides a way to give the input guess for apply function
►Cgko::solver::EnableApplyWithInitialGuess< Ir< ValueType > >
Cgko::solver::Ir< ValueType >	Iterative refinement (IR) is an iterative method that uses another coarse method to approximate the error of the current solution via the current residual
►Cgko::solver::EnableApplyWithInitialGuess< Multigrid >
Cgko::solver::Multigrid	Multigrid methods have a hierarchy of many levels, whose corase level is a subset of the fine level, of the problem
Cgko::solver::EnableApplyWithInitialGuess< DerivedType >	EnableApplyWithInitialGuess providing default operation for ApplyWithInitialGuess with correct validation and log
Cgko::array< ValueType >	An array is a container which encapsulates fixed-sized arrays, stored on the Executor tied to the array
Cgko::array< bool >
Cgko::array< char >
Cgko::array< comm_index_type >
Cgko::array< gko::precision_reduction >
Cgko::array< gko::stopping_status >
Cgko::array< global_index_type >
Cgko::array< GlobalIndexType >
Cgko::array< index_type >
Cgko::array< IndexType >
Cgko::array< int64 >
Cgko::array< local_index_type >
Cgko::array< LocalIndexType >
Cgko::array< real_type >
Cgko::array< remove_complex< value_type > >
Cgko::array< size_type >
Cgko::array< T >
Cgko::array< unsigned char >
Cgko::array< value_type >
Cgko::device_matrix_data< ValueType, IndexType >::arrays	Stores the internal arrays of a device_matrix_data object
Cgko::batch_dim< Dimensionality, DimensionType >	A type representing the dimensions of a multidimensional batch object
Cgko::batch_dim< 2 >
►CBatchLinOp
►Cgko::EnableAbstractPolymorphicObject< Bicgstab< ValueType >, BatchLinOp >
►Cgko::EnablePolymorphicObject< Bicgstab< ValueType >, BatchLinOp >
►Cgko::batch::EnableBatchLinOp< Bicgstab< ValueType >, BatchLinOp >
►Cgko::batch::solver::EnableBatchSolver< Bicgstab< ValueType >, ValueType >
Cgko::batch::solver::Bicgstab< ValueType >	BiCGSTAB or the Bi-Conjugate Gradient-Stabilized is a Krylov subspace solver
►Cgko::EnableAbstractPolymorphicObject< Cg< ValueType >, BatchLinOp >
►Cgko::EnablePolymorphicObject< Cg< ValueType >, BatchLinOp >
►Cgko::batch::EnableBatchLinOp< Cg< ValueType >, BatchLinOp >
►Cgko::batch::solver::EnableBatchSolver< Cg< ValueType >, ValueType >
Cgko::batch::solver::Cg< ValueType >	Cg or the Conjugate Gradient is a Krylov subspace solver
►Cgko::EnableAbstractPolymorphicObject< Csr< ValueType, IndexType >, BatchLinOp >
►Cgko::EnablePolymorphicObject< Csr< ValueType, IndexType >, BatchLinOp >
►Cgko::batch::EnableBatchLinOp< Csr< ValueType, IndexType > >
Cgko::batch::matrix::Csr< ValueType, IndexType >	Csr is a general sparse matrix format that stores the column indices for each nonzero entry and a cumulative sum of the number of nonzeros in each row
►Cgko::EnableAbstractPolymorphicObject< Dense< ValueType >, BatchLinOp >
►Cgko::EnablePolymorphicObject< Dense< ValueType >, BatchLinOp >
►Cgko::batch::EnableBatchLinOp< Dense< ValueType > >
Cgko::batch::matrix::Dense< ValueType >	Dense is a batch matrix format which explicitly stores all values of the matrix in each of the batches
►Cgko::EnableAbstractPolymorphicObject< Ell< ValueType, IndexType >, BatchLinOp >
►Cgko::EnablePolymorphicObject< Ell< ValueType, IndexType >, BatchLinOp >
►Cgko::batch::EnableBatchLinOp< Ell< ValueType, IndexType > >
Cgko::batch::matrix::Ell< ValueType, IndexType >	Ell is a sparse matrix format that stores the same number of nonzeros in each row, enabling coalesced accesses
►Cgko::EnableAbstractPolymorphicObject< Identity< ValueType >, BatchLinOp >
►Cgko::EnablePolymorphicObject< Identity< ValueType >, BatchLinOp >
►Cgko::batch::EnableBatchLinOp< Identity< ValueType > >
Cgko::batch::matrix::Identity< ValueType >	The batch Identity matrix, which represents a batch of Identity matrices
►Cgko::EnableAbstractPolymorphicObject< Jacobi< ValueType, IndexType >, BatchLinOp >
►Cgko::EnablePolymorphicObject< Jacobi< ValueType, IndexType >, BatchLinOp >
►Cgko::batch::EnableBatchLinOp< Jacobi< ValueType, IndexType > >
Cgko::batch::preconditioner::Jacobi< ValueType, IndexType >	A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks (stored in a dense row major fashion) of the source operator
►Cgko::batch::solver::BatchSolver	The BatchSolver is a base class for all batched solvers and provides the common getters and setter for these batched solver classes
Cgko::batch::solver::EnableBatchSolver< Bicgstab< ValueType >, ValueType >
Cgko::batch::solver::EnableBatchSolver< Cg< ValueType >, ValueType >
Cgko::batch::solver::EnableBatchSolver< ConcreteSolver, ValueType, PolymorphicBase >	This mixin provides apply and common iterative solver functionality to all the batched solvers
Cgko::preconditioner::block_interleaved_storage_scheme< IndexType >	Defines the parameters of the interleaved block storage scheme used by block-Jacobi blocks
Cgko::preconditioner::block_interleaved_storage_scheme< index_type >
►Cgko::experimental::mpi::CollectiveCommunicator	Interface for a collective communicator
Cgko::experimental::mpi::DenseCommunicator	A CollectiveCommunicator that uses a dense communication
Cgko::experimental::mpi::NeighborhoodCommunicator	A CollectiveCommunicator that uses a neighborhood topology
Cgko::experimental::mpi::communicator	A thin wrapper of MPI_Comm that supports most MPI calls
Cgko::experimental::mpi::contiguous_type	A move-only wrapper for a contiguous MPI_Datatype
►Cgko::ConvertibleTo< ResultType >	ConvertibleTo interface is used to mark that the implementer can be converted to the object of ResultType
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::EnablePolymorphicAssignment< ConcreteType, ResultType >	This mixin is used to enable a default PolymorphicObject::copy_from() implementation for objects that have implemented conversions between them
►Cgko::ConvertibleTo< Amd< IndexType > >
►Cgko::EnablePolymorphicAssignment< Amd< IndexType > >
Cgko::experimental::reorder::Amd< IndexType >	Computes a Approximate Minimum Degree (AMD) reordering of an input matrix
►Cgko::ConvertibleTo< Bicg< ValueType > >
►Cgko::EnablePolymorphicAssignment< Bicg< ValueType > >
►Cgko::EnableLinOp< Bicg< ValueType > >
Cgko::solver::Bicg< ValueType >	BICG or the Biconjugate gradient method is a Krylov subspace solver
►Cgko::ConvertibleTo< Bicgstab< ValueType > >
►Cgko::EnablePolymorphicAssignment< Bicgstab< ValueType > >
Cgko::batch::EnableBatchLinOp< Bicgstab< ValueType >, BatchLinOp >
►Cgko::EnableLinOp< Bicgstab< ValueType > >
Cgko::solver::Bicgstab< ValueType >	BiCGSTAB or the Bi-Conjugate Gradient-Stabilized is a Krylov subspace solver
►Cgko::ConvertibleTo< BlockOperator >
►Cgko::EnablePolymorphicAssignment< BlockOperator >
►Cgko::EnableLinOp< BlockOperator >
Cgko::BlockOperator	A BlockOperator represents a linear operator that is partitioned into multiple blocks
►Cgko::ConvertibleTo< CbGmres< ValueType > >
►Cgko::EnablePolymorphicAssignment< CbGmres< ValueType > >
►Cgko::EnableLinOp< CbGmres< ValueType > >
Cgko::solver::CbGmres< ValueType >	CB-GMRES or the compressed basis generalized minimal residual method is an iterative type Krylov subspace method which is suitable for nonsymmetric linear systems
►Cgko::ConvertibleTo< Cg< ValueType > >
►Cgko::EnablePolymorphicAssignment< Cg< ValueType > >
Cgko::batch::EnableBatchLinOp< Cg< ValueType >, BatchLinOp >
►Cgko::EnableLinOp< Cg< ValueType > >
Cgko::solver::Cg< ValueType >	CG or the conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
►Cgko::ConvertibleTo< Cgs< ValueType > >
►Cgko::EnablePolymorphicAssignment< Cgs< ValueType > >
►Cgko::EnableLinOp< Cgs< ValueType > >
Cgko::solver::Cgs< ValueType >	CGS or the conjugate gradient square method is an iterative type Krylov subspace method which is suitable for general systems
►Cgko::ConvertibleTo< Cholesky< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Cholesky< ValueType, IndexType > >
Cgko::experimental::factorization::Cholesky< ValueType, IndexType >	Computes a Cholesky factorization of a symmetric, positive-definite sparse matrix
►Cgko::ConvertibleTo< Combination< ValueType > >
►Cgko::EnablePolymorphicAssignment< Combination< ValueType > >
►Cgko::EnableLinOp< Combination< ValueType > >
Cgko::Combination< ValueType >	The Combination class can be used to construct a linear combination of multiple linear operators c1 * op1 + c2 * op2 + ..
►Cgko::ConvertibleTo< Composition< ValueType > >
►Cgko::EnablePolymorphicAssignment< Composition< ValueType > >
►Cgko::EnableLinOp< Composition< ValueType > >
►Cgko::Composition< ValueType >	The Composition class can be used to compose linear operators op1, op2, ..., opn and obtain the operator op1 * op2 * ..
Cgko::factorization::Ic< ValueType, IndexType >	Represents an incomplete Cholesky factorization (IC(0)) of a sparse matrix
Cgko::factorization::Ilu< ValueType, IndexType >	Represents an incomplete LU factorization – ILU(0) – of a sparse matrix
Cgko::factorization::ParIc< ValueType, IndexType >	ParIC is an incomplete Cholesky factorization which is computed in parallel
Cgko::factorization::ParIct< ValueType, IndexType >	ParICT is an incomplete threshold-based Cholesky factorization which is computed in parallel
Cgko::factorization::ParIlu< ValueType, IndexType >	ParILU is an incomplete LU factorization which is computed in parallel
Cgko::factorization::ParIlut< ValueType, IndexType >	ParILUT is an incomplete threshold-based LU factorization which is computed in parallel
►Cgko::ConvertibleTo< ConcreteBatchLinOp >
►Cgko::EnablePolymorphicAssignment< ConcreteBatchLinOp >
Cgko::batch::EnableBatchLinOp< ConcreteBatchLinOp, PolymorphicBase >	The EnableBatchLinOp mixin can be used to provide sensible default implementations of the majority of the BatchLinOp and PolymorphicObject interface
►Cgko::ConvertibleTo< ConcreteFactory >
►Cgko::EnablePolymorphicAssignment< ConcreteFactory >
►Cgko::EnableDefaultFactory< ConcreteFactory, ProductType, ParametersType, PolymorphicBase >	This mixin provides a default implementation of a concrete factory
Cgko::batch::preconditioner::Jacobi< ValueType, IndexType >::Factory
Cgko::batch::solver::Bicgstab< ValueType >::Factory
Cgko::batch::solver::Cg< ValueType >::Factory
Cgko::experimental::distributed::preconditioner::Schwarz< ValueType, LocalIndexType, GlobalIndexType >::Factory
Cgko::experimental::reorder::ScaledReordered< ValueType, IndexType >::Factory
Cgko::experimental::solver::Direct< ValueType, IndexType >::Factory
Cgko::factorization::Ic< ValueType, IndexType >::Factory
Cgko::factorization::Ilu< ValueType, IndexType >::Factory
Cgko::factorization::ParIc< ValueType, IndexType >::Factory
Cgko::factorization::ParIct< ValueType, IndexType >::Factory
Cgko::factorization::ParIlu< ValueType, IndexType >::Factory
Cgko::factorization::ParIlut< ValueType, IndexType >::Factory
Cgko::multigrid::FixedCoarsening< ValueType, IndexType >::Factory
Cgko::multigrid::Pgm< ValueType, IndexType >::Factory
Cgko::preconditioner::Ic< LSolverType, IndexType >::Factory
Cgko::preconditioner::Ilu< LSolverType, USolverType, ReverseApply, IndexType >::Factory
Cgko::preconditioner::Isai< IsaiType, ValueType, IndexType >::Factory
Cgko::preconditioner::Jacobi< ValueType, IndexType >::Factory
Cgko::reorder::Rcm< ValueType, IndexType >::Factory
Cgko::solver::Bicg< ValueType >::Factory
Cgko::solver::Bicgstab< ValueType >::Factory
Cgko::solver::CbGmres< ValueType >::Factory
Cgko::solver::Cg< ValueType >::Factory
Cgko::solver::Cgs< ValueType >::Factory
Cgko::solver::Fcg< ValueType >::Factory
Cgko::solver::Gcr< ValueType >::Factory
Cgko::solver::Gmres< ValueType >::Factory
Cgko::solver::Idr< ValueType >::Factory
Cgko::solver::Ir< ValueType >::Factory
Cgko::solver::LowerTrs< ValueType, IndexType >::Factory
Cgko::solver::Minres< ValueType >::Factory
Cgko::solver::Multigrid::Factory
Cgko::solver::UpperTrs< ValueType, IndexType >::Factory
Cgko::stop::AbsoluteResidualNorm< ValueType >::Factory
Cgko::stop::Combined::Factory
Cgko::stop::ImplicitResidualNorm< ValueType >::Factory
Cgko::stop::Iteration::Factory
Cgko::stop::RelativeResidualNorm< ValueType >::Factory
Cgko::stop::ResidualNorm< ValueType >::Factory
Cgko::stop::ResidualNormReduction< ValueType >::Factory
Cgko::stop::Time::Factory
►Cgko::ConvertibleTo< ConcreteLinOp >
►Cgko::EnablePolymorphicAssignment< ConcreteLinOp >
►Cgko::EnableLinOp< ConcreteLinOp, PolymorphicBase >	The EnableLinOp mixin can be used to provide sensible default implementations of the majority of the LinOp and PolymorphicObject interface
Cgko::matrix::Dense< value_type >
Cgko::solver::Multigrid	Multigrid methods have a hierarchy of many levels, whose corase level is a subset of the fine level, of the problem
►Cgko::ConvertibleTo< ConcreteSolver >
►Cgko::EnablePolymorphicAssignment< ConcreteSolver >
►Cgko::batch::EnableBatchLinOp< ConcreteSolver, PolymorphicBase >
Cgko::batch::solver::EnableBatchSolver< ConcreteSolver, ValueType, PolymorphicBase >	This mixin provides apply and common iterative solver functionality to all the batched solvers
►Cgko::ConvertibleTo< Coo< next_precision< ValueType >, IndexType > >
Cgko::matrix::Coo< ValueType, IndexType >	COO stores a matrix in the coordinate matrix format
►Cgko::ConvertibleTo< Coo< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Coo< ValueType, IndexType > >
►Cgko::EnableLinOp< Coo< ValueType, IndexType > >
Cgko::matrix::Coo< ValueType, IndexType >	COO stores a matrix in the coordinate matrix format
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
►Cgko::ConvertibleTo< Coo< ValueType, int32 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Coo< ValueType, int64 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Csr< next_precision< ValueType >, IndexType > >
Cgko::batch::matrix::Csr< ValueType, IndexType >	Csr is a general sparse matrix format that stores the column indices for each nonzero entry and a cumulative sum of the number of nonzeros in each row
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
►Cgko::ConvertibleTo< Csr< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Csr< ValueType, IndexType > >
Cgko::batch::EnableBatchLinOp< Csr< ValueType, IndexType > >
►Cgko::EnableLinOp< Csr< ValueType, IndexType > >
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Coo< ValueType, IndexType >	COO stores a matrix in the coordinate matrix format
Cgko::matrix::Ell< ValueType, IndexType >	ELL is a matrix format where stride with explicit zeros is used such that all rows have the same number of stored elements
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
Cgko::matrix::Hybrid< ValueType, IndexType >	HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
Cgko::matrix::Sellp< ValueType, IndexType >	SELL-P is a matrix format similar to ELL format
Cgko::matrix::SparsityCsr< ValueType, IndexType >	SparsityCsr is a matrix format which stores only the sparsity pattern of a sparse matrix by compressing each row of the matrix (compressed sparse row format)
►Cgko::ConvertibleTo< Csr< ValueType, int32 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
►Cgko::ConvertibleTo< Csr< ValueType, int64 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
►Cgko::ConvertibleTo< Dense< next_precision< ValueType > > >
Cgko::batch::matrix::Dense< ValueType >	Dense is a batch matrix format which explicitly stores all values of the matrix in each of the batches
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Dense< ValueType > >
►Cgko::EnablePolymorphicAssignment< Dense< ValueType > >
Cgko::batch::EnableBatchLinOp< Dense< ValueType > >
►Cgko::EnableLinOp< Dense< ValueType > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Coo< ValueType, IndexType >	COO stores a matrix in the coordinate matrix format
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Ell< ValueType, IndexType >	ELL is a matrix format where stride with explicit zeros is used such that all rows have the same number of stored elements
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
Cgko::matrix::Hybrid< ValueType, IndexType >	HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
Cgko::matrix::Sellp< ValueType, IndexType >	SELL-P is a matrix format similar to ELL format
Cgko::matrix::SparsityCsr< ValueType, IndexType >	SparsityCsr is a matrix format which stores only the sparsity pattern of a sparse matrix by compressing each row of the matrix (compressed sparse row format)
►Cgko::ConvertibleTo< Diagonal< next_precision< ValueType > > >
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
►Cgko::ConvertibleTo< Diagonal< ValueType > >
►Cgko::EnablePolymorphicAssignment< Diagonal< ValueType > >
►Cgko::EnableLinOp< Diagonal< ValueType > >
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
►Cgko::ConvertibleTo< Direct< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Direct< ValueType, IndexType > >
►Cgko::EnableLinOp< Direct< ValueType, IndexType > >
Cgko::experimental::solver::Direct< ValueType, IndexType >	A direct solver based on a factorization into lower and upper triangular factors (with an optional diagonal scaling)
►Cgko::ConvertibleTo< Ell< next_precision< ValueType >, IndexType > >
Cgko::batch::matrix::Ell< ValueType, IndexType >	Ell is a sparse matrix format that stores the same number of nonzeros in each row, enabling coalesced accesses
Cgko::matrix::Ell< ValueType, IndexType >	ELL is a matrix format where stride with explicit zeros is used such that all rows have the same number of stored elements
►Cgko::ConvertibleTo< Ell< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Ell< ValueType, IndexType > >
Cgko::batch::EnableBatchLinOp< Ell< ValueType, IndexType > >
►Cgko::EnableLinOp< Ell< ValueType, IndexType > >
Cgko::matrix::Ell< ValueType, IndexType >	ELL is a matrix format where stride with explicit zeros is used such that all rows have the same number of stored elements
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
►Cgko::ConvertibleTo< Ell< ValueType, int32 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Ell< ValueType, int64 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Factorization< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Factorization< ValueType, IndexType > >
►Cgko::EnableLinOp< Factorization< ValueType, IndexType > >
Cgko::experimental::factorization::Factorization< ValueType, IndexType >	Represents a generic factorization consisting of two triangular factors (upper and lower) and an optional diagonal scaling matrix
►Cgko::ConvertibleTo< Fbcsr< next_precision< ValueType >, IndexType > >
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
►Cgko::ConvertibleTo< Fbcsr< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Fbcsr< ValueType, IndexType > >
►Cgko::EnableLinOp< Fbcsr< ValueType, IndexType > >
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
►Cgko::ConvertibleTo< Fbcsr< ValueType, int32 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Fbcsr< ValueType, int64 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Fcg< ValueType > >
►Cgko::EnablePolymorphicAssignment< Fcg< ValueType > >
►Cgko::EnableLinOp< Fcg< ValueType > >
Cgko::solver::Fcg< ValueType >	FCG or the flexible conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
►Cgko::ConvertibleTo< Fft >
►Cgko::EnablePolymorphicAssignment< Fft >
►Cgko::EnableLinOp< Fft >
Cgko::matrix::Fft	This LinOp implements a 1D Fourier matrix using the FFT algorithm
►Cgko::ConvertibleTo< Fft2 >
►Cgko::EnablePolymorphicAssignment< Fft2 >
►Cgko::EnableLinOp< Fft2 >
Cgko::matrix::Fft2	This LinOp implements a 2D Fourier matrix using the FFT algorithm
►Cgko::ConvertibleTo< Fft3 >
►Cgko::EnablePolymorphicAssignment< Fft3 >
►Cgko::EnableLinOp< Fft3 >
Cgko::matrix::Fft3	This LinOp implements a 3D Fourier matrix using the FFT algorithm
►Cgko::ConvertibleTo< FixedCoarsening< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< FixedCoarsening< ValueType, IndexType > >
►Cgko::EnableLinOp< FixedCoarsening< ValueType, IndexType > >
Cgko::multigrid::FixedCoarsening< ValueType, IndexType >	FixedCoarsening is a very simple coarse grid generation algorithm
►Cgko::ConvertibleTo< GaussSeidel< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< GaussSeidel< ValueType, IndexType > >
Cgko::preconditioner::GaussSeidel< ValueType, IndexType >	This class generates the Gauss-Seidel preconditioner
►Cgko::ConvertibleTo< Gcr< ValueType > >
►Cgko::EnablePolymorphicAssignment< Gcr< ValueType > >
►Cgko::EnableLinOp< Gcr< ValueType > >
Cgko::solver::Gcr< ValueType >	GCR or the generalized conjugate residual method is an iterative type Krylov subspace method similar to GMRES which is suitable for nonsymmetric linear systems
►Cgko::ConvertibleTo< Gmres< ValueType > >
►Cgko::EnablePolymorphicAssignment< Gmres< ValueType > >
►Cgko::EnableLinOp< Gmres< ValueType > >
Cgko::solver::Gmres< ValueType >	GMRES or the generalized minimal residual method is an iterative type Krylov subspace method which is suitable for nonsymmetric linear systems
►Cgko::ConvertibleTo< Hybrid< next_precision< ValueType >, IndexType > >
Cgko::matrix::Hybrid< ValueType, IndexType >	HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
►Cgko::ConvertibleTo< Hybrid< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Hybrid< ValueType, IndexType > >
►Cgko::EnableLinOp< Hybrid< ValueType, IndexType > >
Cgko::matrix::Hybrid< ValueType, IndexType >	HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
►Cgko::ConvertibleTo< Hybrid< ValueType, int32 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Hybrid< ValueType, int64 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Ic< LSolverType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Ic< LSolverType, IndexType > >
►Cgko::EnableLinOp< Ic< LSolverType, IndexType > >
Cgko::preconditioner::Ic< LSolverType, IndexType >	The Incomplete Cholesky (IC) preconditioner solves the equation for a given lower triangular matrix L and the right hand side b (can contain multiple right hand sides)
►Cgko::ConvertibleTo< Identity< ValueType > >
►Cgko::EnablePolymorphicAssignment< Identity< ValueType > >
Cgko::batch::EnableBatchLinOp< Identity< ValueType > >
►Cgko::EnableLinOp< Identity< ValueType > >
Cgko::matrix::Identity< ValueType >	This class is a utility which efficiently implements the identity matrix (a linear operator which maps each vector to itself)
►Cgko::ConvertibleTo< Idr< ValueType > >
►Cgko::EnablePolymorphicAssignment< Idr< ValueType > >
►Cgko::EnableLinOp< Idr< ValueType > >
Cgko::solver::Idr< ValueType >	IDR(s) is an efficient method for solving large nonsymmetric systems of linear equations
►Cgko::ConvertibleTo< Ilu< LSolverType, USolverType, ReverseApply, IndexType > >
►Cgko::EnablePolymorphicAssignment< Ilu< LSolverType, USolverType, ReverseApply, IndexType > >
►Cgko::EnableLinOp< Ilu< LSolverType, USolverType, ReverseApply, IndexType > >
Cgko::preconditioner::Ilu< LSolverType, USolverType, ReverseApply, IndexType >	The Incomplete LU (ILU) preconditioner solves the equation for a given lower triangular matrix L, an upper triangular matrix U and the right hand side b (can contain multiple right hand sides)
►Cgko::ConvertibleTo< Ir< ValueType > >
►Cgko::EnablePolymorphicAssignment< Ir< ValueType > >
►Cgko::EnableLinOp< Ir< ValueType > >
Cgko::solver::Ir< ValueType >	Iterative refinement (IR) is an iterative method that uses another coarse method to approximate the error of the current solution via the current residual
►Cgko::ConvertibleTo< Isai< IsaiType, ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Isai< IsaiType, ValueType, IndexType > >
►Cgko::EnableLinOp< Isai< IsaiType, ValueType, IndexType > >
Cgko::preconditioner::Isai< IsaiType, ValueType, IndexType >	The Incomplete Sparse Approximate Inverse (ISAI) Preconditioner generates an approximate inverse matrix for a given square matrix A, lower triangular matrix L, upper triangular matrix U or symmetric positive (spd) matrix B
►Cgko::ConvertibleTo< Jacobi< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Jacobi< ValueType, IndexType > >
Cgko::batch::EnableBatchLinOp< Jacobi< ValueType, IndexType > >
►Cgko::EnableLinOp< Jacobi< ValueType, IndexType > >
Cgko::preconditioner::Jacobi< ValueType, IndexType >	A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks of the source operator
►Cgko::ConvertibleTo< LowerTrs< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< LowerTrs< ValueType, IndexType > >
►Cgko::EnableLinOp< LowerTrs< ValueType, IndexType > >
Cgko::solver::LowerTrs< ValueType, IndexType >	LowerTrs is the triangular solver which solves the system L x = b, when L is a lower triangular matrix
►Cgko::ConvertibleTo< Lu< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Lu< ValueType, IndexType > >
Cgko::experimental::factorization::Lu< ValueType, IndexType >	Computes an LU factorization of a sparse matrix
►Cgko::ConvertibleTo< matrix::Dense< ValueType > >
Cgko::preconditioner::Jacobi< ValueType, IndexType >	A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks of the source operator
►Cgko::ConvertibleTo< Matrix< next_precision< ValueType >, LocalIndexType, GlobalIndexType > >
Cgko::experimental::distributed::Matrix< ValueType, LocalIndexType, GlobalIndexType >	The Matrix class defines a (MPI-)distributed matrix
►Cgko::ConvertibleTo< Matrix< ValueType, LocalIndexType, GlobalIndexType > >
►Cgko::EnablePolymorphicAssignment< Matrix< ValueType, LocalIndexType, GlobalIndexType > >
►Cgko::EnableLinOp< Matrix< ValueType, LocalIndexType, GlobalIndexType > >
Cgko::experimental::distributed::Matrix< ValueType, LocalIndexType, GlobalIndexType >	The Matrix class defines a (MPI-)distributed matrix
►Cgko::ConvertibleTo< Mc64< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Mc64< ValueType, IndexType > >
Cgko::experimental::reorder::Mc64< ValueType, IndexType >	MC64 is an algorithm for permuting large entries to the diagonal of a sparse matrix
►Cgko::ConvertibleTo< Minres< ValueType > >
►Cgko::EnablePolymorphicAssignment< Minres< ValueType > >
►Cgko::EnableLinOp< Minres< ValueType > >
Cgko::solver::Minres< ValueType >	Minres is an iterative type Krylov subspace method, which is suitable for indefinite and full-rank symmetric/hermitian operators
►Cgko::ConvertibleTo< Multigrid >
►Cgko::EnablePolymorphicAssignment< Multigrid >
Cgko::EnableLinOp< Multigrid >
►Cgko::ConvertibleTo< MultiVector< next_precision< ValueType > > >
Cgko::batch::MultiVector< ValueType >	MultiVector stores multiple vectors in a batched fashion and is useful for batched operations
►Cgko::ConvertibleTo< MultiVector< ValueType > >
►Cgko::EnablePolymorphicAssignment< MultiVector< ValueType > >
Cgko::batch::MultiVector< ValueType >	MultiVector stores multiple vectors in a batched fashion and is useful for batched operations
►Cgko::ConvertibleTo< Partition< LocalIndexType, GlobalIndexType > >
►Cgko::EnablePolymorphicAssignment< Partition< LocalIndexType, GlobalIndexType > >
Cgko::experimental::distributed::Partition< LocalIndexType, GlobalIndexType >	Represents a partition of a range of indices [0, size) into a disjoint set of parts
►Cgko::ConvertibleTo< Permutation< IndexType > >
►Cgko::EnablePolymorphicAssignment< Permutation< IndexType > >
►Cgko::EnableLinOp< Permutation< IndexType > >
Cgko::matrix::Permutation< IndexType >	Permutation is a matrix format that represents a permutation matrix, i.e
►Cgko::ConvertibleTo< Perturbation< ValueType > >
►Cgko::EnablePolymorphicAssignment< Perturbation< ValueType > >
►Cgko::EnableLinOp< Perturbation< ValueType > >
Cgko::Perturbation< ValueType >	The Perturbation class can be used to construct a LinOp to represent the operation (identity + scalar * basis * projector)
►Cgko::ConvertibleTo< Pgm< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Pgm< ValueType, IndexType > >
►Cgko::EnableLinOp< Pgm< ValueType, IndexType > >
Cgko::multigrid::Pgm< ValueType, IndexType >	Parallel graph match (Pgm) is the aggregate method introduced in the paper M
►Cgko::ConvertibleTo< Rcm< IndexType > >
►Cgko::EnablePolymorphicAssignment< Rcm< IndexType > >
Cgko::experimental::reorder::Rcm< IndexType >	Rcm (Reverse Cuthill-McKee) is a reordering algorithm minimizing the bandwidth of a matrix
►Cgko::ConvertibleTo< Rcm< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Rcm< ValueType, IndexType > >
Cgko::reorder::Rcm< ValueType, IndexType >	Rcm (Reverse Cuthill-McKee) is a reordering algorithm minimizing the bandwidth of a matrix
►Cgko::ConvertibleTo< RowGatherer< IndexType > >
►Cgko::EnablePolymorphicAssignment< RowGatherer< IndexType > >
►Cgko::EnableLinOp< RowGatherer< IndexType > >
Cgko::matrix::RowGatherer< IndexType >	RowGatherer is a matrix "format" which stores the gather indices arrays which can be used to gather rows to another matrix
►Cgko::ConvertibleTo< ScaledPermutation< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< ScaledPermutation< ValueType, IndexType > >
►Cgko::EnableLinOp< ScaledPermutation< ValueType, IndexType > >
Cgko::matrix::ScaledPermutation< ValueType, IndexType >	ScaledPermutation is a matrix combining a permutation with scaling factors
►Cgko::ConvertibleTo< ScaledReordered< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< ScaledReordered< ValueType, IndexType > >
►Cgko::EnableLinOp< ScaledReordered< ValueType, IndexType > >
Cgko::experimental::reorder::ScaledReordered< ValueType, IndexType >	Provides an interface to wrap reorderings like Rcm and diagonal scaling like equilibration around a LinOp like e.g
►Cgko::ConvertibleTo< Schwarz< ValueType, LocalIndexType, GlobalIndexType > >
►Cgko::EnablePolymorphicAssignment< Schwarz< ValueType, LocalIndexType, GlobalIndexType > >
►Cgko::EnableLinOp< Schwarz< ValueType, LocalIndexType, GlobalIndexType > >
Cgko::experimental::distributed::preconditioner::Schwarz< ValueType, LocalIndexType, GlobalIndexType >	A Schwarz preconditioner is a simple domain decomposition preconditioner that generalizes the Block Jacobi preconditioner, incorporating options for different local subdomain solvers and overlaps between the subdomains
►Cgko::ConvertibleTo< Sellp< next_precision< ValueType >, IndexType > >
Cgko::matrix::Sellp< ValueType, IndexType >	SELL-P is a matrix format similar to ELL format
►Cgko::ConvertibleTo< Sellp< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Sellp< ValueType, IndexType > >
►Cgko::EnableLinOp< Sellp< ValueType, IndexType > >
Cgko::matrix::Sellp< ValueType, IndexType >	SELL-P is a matrix format similar to ELL format
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
►Cgko::ConvertibleTo< Sellp< ValueType, int32 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Sellp< ValueType, int64 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< Sor< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< Sor< ValueType, IndexType > >
Cgko::preconditioner::Sor< ValueType, IndexType >	This class generates the (S)SOR preconditioner
►Cgko::ConvertibleTo< SparsityCsr< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< SparsityCsr< ValueType, IndexType > >
►Cgko::EnableLinOp< SparsityCsr< ValueType, IndexType > >
Cgko::matrix::SparsityCsr< ValueType, IndexType >	SparsityCsr is a matrix format which stores only the sparsity pattern of a sparse matrix by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
►Cgko::ConvertibleTo< SparsityCsr< ValueType, int32 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< SparsityCsr< ValueType, int64 > >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::ConvertibleTo< UpperTrs< ValueType, IndexType > >
►Cgko::EnablePolymorphicAssignment< UpperTrs< ValueType, IndexType > >
►Cgko::EnableLinOp< UpperTrs< ValueType, IndexType > >
Cgko::solver::UpperTrs< ValueType, IndexType >	UpperTrs is the triangular solver which solves the system U x = b, when U is an upper triangular matrix
►Cgko::ConvertibleTo< Vector< next_precision< ValueType > > >
Cgko::experimental::distributed::Vector< ValueType >	Vector is a format which explicitly stores (multiple) distributed column vectors in a dense storage format
►Cgko::ConvertibleTo< Vector< ValueType > >
►Cgko::EnablePolymorphicAssignment< Vector< ValueType > >
►Cgko::EnableLinOp< Vector< ValueType > >
Cgko::experimental::distributed::Vector< ValueType >	Vector is a format which explicitly stores (multiple) distributed column vectors in a dense storage format
Cgko::matrix::CooBuilder< ValueType, IndexType >
Cgko::cpx_real_type< T >	Access the underlying real type of a complex number
►CCriterion
►Cgko::EnableAbstractPolymorphicObject< Combined, Criterion >
►Cgko::EnablePolymorphicObject< Combined, Criterion >
Cgko::stop::Combined	Used to combine multiple criterions together through an OR operation
►Cgko::EnableAbstractPolymorphicObject< Iteration, Criterion >
►Cgko::EnablePolymorphicObject< Iteration, Criterion >
Cgko::stop::Iteration	Stopping criterion which stops the iteration process after a preset number of iterations
►Cgko::EnableAbstractPolymorphicObject< ResidualNormBase< ValueType >, Criterion >
►Cgko::EnablePolymorphicObject< ResidualNormBase< ValueType >, Criterion >
►Cgko::stop::ResidualNormBase< ValueType >	The ResidualNormBase class provides a framework for stopping criteria related to the residual norm
Cgko::stop::AbsoluteResidualNorm< ValueType >	The AbsoluteResidualNorm class is a stopping criterion which stops the iteration process when the residual norm is below a certain threshold, i.e
Cgko::stop::ImplicitResidualNorm< ValueType >	The ImplicitResidualNorm class is a stopping criterion which stops the iteration process when the implicit residual norm is below a certain threshold relative to
Cgko::stop::RelativeResidualNorm< ValueType >	The RelativeResidualNorm class is a stopping criterion which stops the iteration process when the residual norm is below a certain threshold relative to the norm of the right-hand side, i.e
Cgko::stop::ResidualNorm< ValueType >	The ResidualNorm class is a stopping criterion which stops the iteration process when the actual residual norm is below a certain threshold relative to
Cgko::stop::ResidualNormReduction< ValueType >	The ResidualNormReduction class is a stopping criterion which stops the iteration process when the residual norm is below a certain threshold relative to the norm of the initial residual, i.e
►Cgko::EnableAbstractPolymorphicObject< Time, Criterion >
►Cgko::EnablePolymorphicObject< Time, Criterion >
Cgko::stop::Time	Stopping criterion which stops the iteration process after a certain amount of time has passed
Cgko::log::criterion_data	Struct representing Criterion related data
Cgko::stop::CriterionArgs	This struct is used to pass parameters to the EnableDefaultCriterionFactoryCriterionFactory::generate() method
Cgko::matrix::CsrBuilder< ValueType, IndexType >
Cgko::cuda_stream	An RAII wrapper for a custom CUDA stream
Cgko::default_converter< S, R >	Used to convert objects of type S to objects of type R using static_cast
Cgko::deferred_factory_parameter< FactoryType >	Represents a factory parameter of factory type that can either initialized by a pre-existing factory or by passing in a factory_parameters object whose .on(exec) will be called to instantiate a factory
Cgko::deferred_factory_parameter< const gko::LinOpFactory >
Cgko::deferred_factory_parameter< const typename l_solver_type::Factory >
Cgko::deferred_factory_parameter< const typename u_solver_type::Factory >
Cgko::deferred_factory_parameter< excess_solver_factory_type >
Cgko::deferred_factory_parameter< factorization_type >
Cgko::deferred_factory_parameter< l_solver_type >
Cgko::deferred_factory_parameter< local_solver_type >
Cgko::deferred_factory_parameter< preconditioner_type >
Cgko::deferred_factory_parameter< solver_type >
Cgko::deferred_factory_parameter< u_solver_type >
Cgko::device_matrix_data< ValueType, IndexType >	This type is a device-side equivalent to matrix_data
►Cgko::DiagonalLinOpExtractable	The diagonal of a LinOp can be extracted
►Cgko::DiagonalExtractable< ValueType >	The diagonal of a LinOp implementing this interface can be extracted
Cgko::matrix::Dense< value_type >
Cgko::matrix::Coo< ValueType, IndexType >	COO stores a matrix in the coordinate matrix format
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Ell< ValueType, IndexType >	ELL is a matrix format where stride with explicit zeros is used such that all rows have the same number of stored elements
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
Cgko::matrix::Hybrid< ValueType, IndexType >	HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
Cgko::matrix::Sellp< ValueType, IndexType >	SELL-P is a matrix format similar to ELL format
Cgko::dim< Dimensionality, DimensionType >	A type representing the dimensions of a multidimensional object
Cgko::dim< 1u, DimensionType >
Cgko::dim< 2 >
Cgko::dim< 3 >
Cgko::dim< dimensionality, dimension_type >
►Cgko::experimental::distributed::DistributedBase	A base class for distributed objects
Cgko::experimental::distributed::Matrix< ValueType, LocalIndexType, GlobalIndexType >	The Matrix class defines a (MPI-)distributed matrix
Cgko::experimental::distributed::Vector< ValueType >	Vector is a format which explicitly stores (multiple) distributed column vectors in a dense storage format
►Cgko::enable_parameters_type< ConcreteParametersType, Factory >	The enable_parameters_type mixin is used to create a base implementation of the factory parameters structure
Cgko::experimental::reorder::Rcm< IndexType >::parameters_type
►Cgko::enable_parameters_type< Parameters, Factory >
Cgko::batch::solver::enable_preconditioned_iterative_solver_factory_parameters< Parameters, Factory >
►Cgko::solver::enable_iterative_solver_factory_parameters< Parameters, Factory >
Cgko::solver::enable_preconditioned_iterative_solver_factory_parameters< Parameters, Factory >
►Cgko::enable_parameters_type< parameters_type, Amd< IndexType > >
Cgko::experimental::reorder::Amd< IndexType >::parameters_type
►Cgko::enable_parameters_type< parameters_type, Cholesky >
Cgko::experimental::factorization::Cholesky< ValueType, IndexType >::parameters_type
►Cgko::enable_parameters_type< parameters_type, Factory >
►Cgko::solver::enable_iterative_solver_factory_parameters< parameters_type, Factory >
►Cgko::solver::enable_preconditioned_iterative_solver_factory_parameters< parameters_type, Factory >
Cgko::solver::Bicg< ValueType >::parameters_type
Cgko::solver::Bicgstab< ValueType >::parameters_type
Cgko::solver::CbGmres< ValueType >::parameters_type
Cgko::solver::Cg< ValueType >::parameters_type
Cgko::solver::Cgs< ValueType >::parameters_type
Cgko::solver::Fcg< ValueType >::parameters_type
Cgko::solver::Gcr< ValueType >::parameters_type
Cgko::solver::Gmres< ValueType >::parameters_type
Cgko::solver::Idr< ValueType >::parameters_type
Cgko::solver::Minres< ValueType >::parameters_type
Cgko::solver::Ir< ValueType >::parameters_type
Cgko::solver::Multigrid::parameters_type
►Cgko::batch::solver::enable_preconditioned_iterative_solver_factory_parameters< parameters_type, Factory >
Cgko::batch::solver::Bicgstab< ValueType >::parameters_type
Cgko::batch::solver::Cg< ValueType >::parameters_type
Cgko::batch::preconditioner::Jacobi< ValueType, IndexType >::parameters_type
Cgko::experimental::distributed::preconditioner::Schwarz< ValueType, LocalIndexType, GlobalIndexType >::parameters_type
Cgko::experimental::reorder::ScaledReordered< ValueType, IndexType >::parameters_type
Cgko::experimental::solver::Direct< ValueType, IndexType >::parameters_type
Cgko::factorization::Ic< ValueType, IndexType >::parameters_type
Cgko::factorization::Ilu< ValueType, IndexType >::parameters_type
Cgko::factorization::ParIc< ValueType, IndexType >::parameters_type
Cgko::factorization::ParIct< ValueType, IndexType >::parameters_type
Cgko::factorization::ParIlu< ValueType, IndexType >::parameters_type
Cgko::factorization::ParIlut< ValueType, IndexType >::parameters_type
Cgko::multigrid::FixedCoarsening< ValueType, IndexType >::parameters_type
Cgko::multigrid::Pgm< ValueType, IndexType >::parameters_type
Cgko::preconditioner::Ic< LSolverType, IndexType >::parameters_type
Cgko::preconditioner::Ilu< LSolverType, USolverType, ReverseApply, IndexType >::parameters_type
Cgko::preconditioner::Isai< IsaiType, ValueType, IndexType >::parameters_type
Cgko::preconditioner::Jacobi< ValueType, IndexType >::parameters_type
Cgko::reorder::Rcm< ValueType, IndexType >::parameters_type
Cgko::solver::LowerTrs< ValueType, IndexType >::parameters_type
Cgko::solver::UpperTrs< ValueType, IndexType >::parameters_type
Cgko::stop::AbsoluteResidualNorm< ValueType >::parameters_type
Cgko::stop::Combined::parameters_type
Cgko::stop::ImplicitResidualNorm< ValueType >::parameters_type
Cgko::stop::Iteration::parameters_type
Cgko::stop::RelativeResidualNorm< ValueType >::parameters_type
Cgko::stop::ResidualNorm< ValueType >::parameters_type
Cgko::stop::ResidualNormReduction< ValueType >::parameters_type
Cgko::stop::Time::parameters_type
►Cgko::enable_parameters_type< parameters_type, GaussSeidel >
Cgko::preconditioner::GaussSeidel< ValueType, IndexType >::parameters_type
►Cgko::enable_parameters_type< parameters_type, Lu >
Cgko::experimental::factorization::Lu< ValueType, IndexType >::parameters_type
►Cgko::enable_parameters_type< parameters_type, Mc64 >
Cgko::experimental::reorder::Mc64< ValueType, IndexType >::parameters_type
Cgko::enable_parameters_type< parameters_type, Rcm< IndexType > >
►Cgko::enable_parameters_type< parameters_type, Sor >
Cgko::preconditioner::Sor< ValueType, IndexType >::parameters_type
►Cenable_shared_from_this
Cgko::CudaExecutor	This is the Executor subclass which represents the CUDA device
Cgko::DpcppExecutor	This is the Executor subclass which represents a DPC++ enhanced device
Cgko::HipExecutor	This is the Executor subclass which represents the HIP enhanced device
►Cgko::OmpExecutor	This is the Executor subclass which represents the OpenMP device (typically CPU)
Cgko::ReferenceExecutor	This is a specialization of the OmpExecutor, which runs the reference implementations of the kernels used for debugging purposes
Cgko::EnableCreateMethod< ConcreteType >	This mixin implements a static create() method on ConcreteType that dynamically allocates the memory, uses the passed-in arguments to construct the object, and returns an std::unique_ptr to such an object
►Cgko::EnableCreateMethod< Combination< ValueType > >
Cgko::Combination< ValueType >	The Combination class can be used to construct a linear combination of multiple linear operators c1 * op1 + c2 * op2 + ..
►Cgko::EnableCreateMethod< Composition< ValueType > >
Cgko::Composition< ValueType >	The Composition class can be used to compose linear operators op1, op2, ..., opn and obtain the operator op1 * op2 * ..
►Cgko::EnableCreateMethod< Perturbation< ValueType > >
Cgko::Perturbation< ValueType >	The Perturbation class can be used to construct a LinOp to represent the operation (identity + scalar * basis * projector)
►Cgko::detail::EnableDeviceReset	Controls whether the DeviceReset function should be called thanks to a boolean
Cgko::CudaExecutor	This is the Executor subclass which represents the CUDA device
Cgko::HipExecutor	This is the Executor subclass which represents the HIP enhanced device
Cgko::experimental::mpi::environment	Class that sets up and finalizes the MPI environment
Cgko::err< T >
►Cstd::exception	STL class
►Cgko::Error	Used to report exceptional behaviour in library functions
Cgko::AllocationError	AllocationError is thrown if a memory allocation fails
Cgko::BadDimension	BadDimension is thrown if an operation is being applied to a LinOp with bad dimensions
Cgko::BlockSizeError< IndexType >	Error that denotes issues between block sizes and matrix dimensions
Cgko::CublasError	CublasError is thrown when a cuBLAS routine throws a non-zero error code
Cgko::CudaError	CudaError is thrown when a CUDA routine throws a non-zero error code
Cgko::CufftError	CufftError is thrown when a cuFFT routine throws a non-zero error code
Cgko::CurandError	CurandError is thrown when a cuRAND routine throws a non-zero error code
Cgko::CusparseError	CusparseError is thrown when a cuSPARSE routine throws a non-zero error code
Cgko::DimensionMismatch	DimensionMismatch is thrown if an operation is being applied to LinOps of incompatible size
Cgko::HipblasError	HipblasError is thrown when a hipBLAS routine throws a non-zero error code
Cgko::HipError	HipError is thrown when a HIP routine throws a non-zero error code
Cgko::HipfftError	HipfftError is thrown when a hipFFT routine throws a non-zero error code
Cgko::HiprandError	HiprandError is thrown when a hipRAND routine throws a non-zero error code
Cgko::HipsparseError	HipsparseError is thrown when a hipSPARSE routine throws a non-zero error code
Cgko::InvalidStateError	Exception thrown if an object is in an invalid state
Cgko::KernelNotFound	KernelNotFound is thrown if Ginkgo cannot find a kernel which satisfies the criteria imposed by the input arguments
Cgko::MetisError	MetisError is thrown when METIS routine throws an error code
Cgko::MpiError	MpiError is thrown when a MPI routine throws a non-zero error code
Cgko::NotCompiled	NotCompiled is thrown when attempting to call an operation which is a part of a module that was not compiled on the system
Cgko::NotImplemented	NotImplemented is thrown in case an operation has not yet been implemented (but will be implemented in the future)
Cgko::NotSupported	NotSupported is thrown in case it is not possible to perform the requested operation on the given object type
Cgko::OutOfBoundsError	OutOfBoundsError is thrown if a memory access is detected to be out-of-bounds
Cgko::OverflowError	OverflowError is thrown when an index calculation for storage requirements overflows
Cgko::StreamError	StreamError is thrown if accessing a stream failed
Cgko::UnsupportedMatrixProperty	Exception throws if a matrix does not have a property required by a numerical method
Cgko::ValueMismatch	ValueMismatch is thrown if two values are not equal
Cgko::log::executor_data	Struct representing Executor related data
Cgko::executor_deleter< T >	This is a deleter that uses an executor's free method to deallocate the data
Cgko::executor_deleter< T[]>
►Cfalse_type
Cgko::solver::has_with_criteria< SolverType, typename >	Helper structure to test if the Factory of SolverType has a function with_criteria
Cgko::matrix::FbcsrBuilder< ValueType, IndexType >
Cgko::half	A class providing basic support for half precision floating point types
Cgko::hip_stream	An RAII wrapper for a custom HIP stream
Chwloc_obj_t
Chwloc_obj_type_t
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::add >
Cgko::accessor::add< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::bitwise_and >
Cgko::accessor::bitwise_and< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::bitwise_or >
Cgko::accessor::bitwise_or< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::bitwise_xor >
Cgko::accessor::bitwise_xor< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::div >
Cgko::accessor::div< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::equal >
Cgko::accessor::equal< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::greater >
Cgko::accessor::greater< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::greater_or_equal >
Cgko::accessor::greater_or_equal< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::left_shift >
Cgko::accessor::left_shift< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::less >
Cgko::accessor::less< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::less_or_equal >
Cgko::accessor::less_or_equal< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::logical_and >
Cgko::accessor::logical_and< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::logical_or >
Cgko::accessor::logical_or< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::max_operation >
Cgko::accessor::max_operation< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::min_operation >
Cgko::accessor::min_operation< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::mod >
Cgko::accessor::mod< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::mul >
Cgko::accessor::mul< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::not_equal >
Cgko::accessor::not_equal< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::right_shift >
Cgko::accessor::right_shift< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::sub >
Cgko::accessor::sub< Kind, FirstOperand, SecondOperand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::abs_operation >
►Cgko::accessor::abs_operation< Operand >
Cgko::accessor::abs_operaton< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::bitwise_not >
Cgko::accessor::bitwise_not< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::conj_operation >
►Cgko::accessor::conj_operation< Operand >
Cgko::accessor::conj_operaton< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::imag_operation >
►Cgko::accessor::imag_operation< Operand >
Cgko::accessor::imag_operaton< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::logical_not >
Cgko::accessor::logical_not< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::one_operation >
►Cgko::accessor::one_operation< Operand >
Cgko::accessor::one_operaton< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::real_operation >
►Cgko::accessor::real_operation< Operand >
Cgko::accessor::real_operaton< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::squared_norm_operation >
►Cgko::accessor::squared_norm_operation< Operand >
Cgko::accessor::squared_norm_operaton< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::unary_minus >
Cgko::accessor::unary_minus< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::unary_plus >
Cgko::accessor::unary_plus< Operand >
►Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::zero_operation >
Cgko::accessor::zero_operation< Operand >
Cgko::experimental::distributed::index_map< LocalIndexType, GlobalIndexType >	This class defines mappings between global and local indices
Cgko::experimental::distributed::index_map< local_index_type, global_index_type >
Cgko::index_set< IndexType >	An index set class represents an ordered set of intervals
Cgko::log::iteration_complete_data	Struct representing iteration complete related data
►Cgko::solver::IterativeBase	A LinOp implementing this interface stores a stopping criterion factory
►Cgko::solver::EnableIterativeBase< Bicg< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Bicg< ValueType > >
Cgko::solver::Bicg< ValueType >	BICG or the Biconjugate gradient method is a Krylov subspace solver
►Cgko::solver::EnableIterativeBase< Bicgstab< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Bicgstab< ValueType > >
Cgko::solver::Bicgstab< ValueType >	BiCGSTAB or the Bi-Conjugate Gradient-Stabilized is a Krylov subspace solver
►Cgko::solver::EnableIterativeBase< CbGmres< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, CbGmres< ValueType > >
Cgko::solver::CbGmres< ValueType >	CB-GMRES or the compressed basis generalized minimal residual method is an iterative type Krylov subspace method which is suitable for nonsymmetric linear systems
►Cgko::solver::EnableIterativeBase< Cg< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Cg< ValueType > >
Cgko::solver::Cg< ValueType >	CG or the conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
►Cgko::solver::EnableIterativeBase< Cgs< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Cgs< ValueType > >
Cgko::solver::Cgs< ValueType >	CGS or the conjugate gradient square method is an iterative type Krylov subspace method which is suitable for general systems
►Cgko::solver::EnableIterativeBase< Fcg< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Fcg< ValueType > >
Cgko::solver::Fcg< ValueType >	FCG or the flexible conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
►Cgko::solver::EnableIterativeBase< Gcr< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Gcr< ValueType > >
Cgko::solver::Gcr< ValueType >	GCR or the generalized conjugate residual method is an iterative type Krylov subspace method similar to GMRES which is suitable for nonsymmetric linear systems
►Cgko::solver::EnableIterativeBase< Gmres< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Gmres< ValueType > >
Cgko::solver::Gmres< ValueType >	GMRES or the generalized minimal residual method is an iterative type Krylov subspace method which is suitable for nonsymmetric linear systems
►Cgko::solver::EnableIterativeBase< Idr< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Idr< ValueType > >
Cgko::solver::Idr< ValueType >	IDR(s) is an efficient method for solving large nonsymmetric systems of linear equations
►Cgko::solver::EnableIterativeBase< Ir< ValueType > >
Cgko::solver::Ir< ValueType >	Iterative refinement (IR) is an iterative method that uses another coarse method to approximate the error of the current solution via the current residual
►Cgko::solver::EnableIterativeBase< Minres< ValueType > >
►Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Minres< ValueType > >
Cgko::solver::Minres< ValueType >	Minres is an iterative type Krylov subspace method, which is suitable for indefinite and full-rank symmetric/hermitian operators
►Cgko::solver::EnableIterativeBase< Multigrid >
Cgko::solver::Multigrid	Multigrid methods have a hierarchy of many levels, whose corase level is a subset of the fine level, of the problem
►Cgko::solver::EnableIterativeBase< DerivedType >	A LinOp deriving from this CRTP class stores a stopping criterion factory and allows applying with a guess
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, DerivedType >	A LinOp implementing this interface stores a system matrix and stopping criterion factory
Cgko::log::linop_data	Struct representing LinOp related data
Cgko::log::linop_factory_data	Struct representing LinOp factory related data
►Cgko::log::Loggable	Loggable class is an interface which should be implemented by classes wanting to support logging
►Cgko::log::EnableLogging< Executor >
►Cgko::Executor	The first step in using the Ginkgo library consists of creating an executor
►Cgko::detail::ExecutorBase< DpcppExecutor >
Cgko::DpcppExecutor	This is the Executor subclass which represents a DPC++ enhanced device
►Cgko::detail::ExecutorBase< ConcreteExecutor >
Cgko::CudaExecutor	This is the Executor subclass which represents the CUDA device
Cgko::HipExecutor	This is the Executor subclass which represents the HIP enhanced device
Cgko::OmpExecutor	This is the Executor subclass which represents the OpenMP device (typically CPU)
►Cgko::log::EnableLogging< PolymorphicObject >
►Cgko::PolymorphicObject	A PolymorphicObject is the abstract base for all "heavy" objects in Ginkgo that behave polymorphically
►Cgko::EnableAbstractPolymorphicObject< AbstractFactory< AbstractProductType, ComponentsType > >
Cgko::AbstractFactory< AbstractProductType, ComponentsType >	The AbstractFactory is a generic interface template that enables easy implementation of the abstract factory design pattern
►Cgko::EnableAbstractPolymorphicObject< AbstractFactory< BatchLinOp, std::shared_ptr< const BatchLinOp > > >
►Cgko::AbstractFactory< BatchLinOp, std::shared_ptr< const BatchLinOp > >
Cgko::batch::BatchLinOpFactory	A BatchLinOpFactory represents a higher order mapping which transforms one batch linear operator into another
►Cgko::EnableAbstractPolymorphicObject< AbstractFactory< LinOp, std::shared_ptr< const LinOp > > >
►Cgko::AbstractFactory< LinOp, std::shared_ptr< const LinOp > >
►Cgko::LinOpFactory	A LinOpFactory represents a higher order mapping which transforms one linear operator into another
►Cgko::EnableAbstractPolymorphicObject< Amd< IndexType >, LinOpFactory >
►Cgko::EnablePolymorphicObject< Amd< IndexType >, LinOpFactory >
Cgko::experimental::reorder::Amd< IndexType >	Computes a Approximate Minimum Degree (AMD) reordering of an input matrix
►Cgko::EnableAbstractPolymorphicObject< Cholesky< ValueType, IndexType >, LinOpFactory >
►Cgko::EnablePolymorphicObject< Cholesky< ValueType, IndexType >, LinOpFactory >
Cgko::experimental::factorization::Cholesky< ValueType, IndexType >	Computes a Cholesky factorization of a symmetric, positive-definite sparse matrix
►Cgko::EnableAbstractPolymorphicObject< GaussSeidel< ValueType, IndexType >, LinOpFactory >
►Cgko::EnablePolymorphicObject< GaussSeidel< ValueType, IndexType >, LinOpFactory >
Cgko::preconditioner::GaussSeidel< ValueType, IndexType >	This class generates the Gauss-Seidel preconditioner
►Cgko::EnableAbstractPolymorphicObject< IdentityFactory< ValueType >, LinOpFactory >
►Cgko::EnablePolymorphicObject< IdentityFactory< ValueType >, LinOpFactory >
Cgko::matrix::IdentityFactory< ValueType >	This factory is a utility which can be used to generate Identity operators
►Cgko::EnableAbstractPolymorphicObject< Lu< ValueType, IndexType >, LinOpFactory >
►Cgko::EnablePolymorphicObject< Lu< ValueType, IndexType >, LinOpFactory >
Cgko::experimental::factorization::Lu< ValueType, IndexType >	Computes an LU factorization of a sparse matrix
►Cgko::EnableAbstractPolymorphicObject< Mc64< ValueType, IndexType >, LinOpFactory >
►Cgko::EnablePolymorphicObject< Mc64< ValueType, IndexType >, LinOpFactory >
Cgko::experimental::reorder::Mc64< ValueType, IndexType >	MC64 is an algorithm for permuting large entries to the diagonal of a sparse matrix
►Cgko::EnableAbstractPolymorphicObject< Rcm< IndexType >, LinOpFactory >
►Cgko::EnablePolymorphicObject< Rcm< IndexType >, LinOpFactory >
Cgko::experimental::reorder::Rcm< IndexType >	Rcm (Reverse Cuthill-McKee) is a reordering algorithm minimizing the bandwidth of a matrix
►Cgko::EnableAbstractPolymorphicObject< Sor< ValueType, IndexType >, LinOpFactory >
►Cgko::EnablePolymorphicObject< Sor< ValueType, IndexType >, LinOpFactory >
Cgko::preconditioner::Sor< ValueType, IndexType >	This class generates the (S)SOR preconditioner
►Cgko::EnableAbstractPolymorphicObject< BatchLinOp >
Cgko::batch::BatchLinOp
►Cgko::EnableAbstractPolymorphicObject< Criterion >
Cgko::stop::Criterion	Base class for all stopping criteria
►Cgko::EnableAbstractPolymorphicObject< LinOp >
►Cgko::LinOp
►Cgko::EnableAbstractPolymorphicObject< Bicg< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Bicg< ValueType >, LinOp >
Cgko::EnableLinOp< Bicg< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Bicgstab< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Bicgstab< ValueType >, LinOp >
Cgko::EnableLinOp< Bicgstab< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< BlockOperator, LinOp >
►Cgko::EnablePolymorphicObject< BlockOperator, LinOp >
Cgko::EnableLinOp< BlockOperator >
►Cgko::EnableAbstractPolymorphicObject< CbGmres< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< CbGmres< ValueType >, LinOp >
Cgko::EnableLinOp< CbGmres< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Cg< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Cg< ValueType >, LinOp >
Cgko::EnableLinOp< Cg< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Cgs< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Cgs< ValueType >, LinOp >
Cgko::EnableLinOp< Cgs< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Combination< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Combination< ValueType >, LinOp >
Cgko::EnableLinOp< Combination< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Composition< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Composition< ValueType >, LinOp >
Cgko::EnableLinOp< Composition< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Coo< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Coo< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Coo< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Csr< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Csr< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Csr< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Dense< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Dense< ValueType >, LinOp >
Cgko::EnableLinOp< Dense< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Diagonal< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Diagonal< ValueType >, LinOp >
Cgko::EnableLinOp< Diagonal< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Direct< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Direct< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Direct< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Ell< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Ell< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Ell< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Factorization< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Factorization< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Factorization< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Fbcsr< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Fbcsr< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Fbcsr< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Fcg< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Fcg< ValueType >, LinOp >
Cgko::EnableLinOp< Fcg< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Fft, LinOp >
►Cgko::EnablePolymorphicObject< Fft, LinOp >
Cgko::EnableLinOp< Fft >
►Cgko::EnableAbstractPolymorphicObject< Fft2, LinOp >
►Cgko::EnablePolymorphicObject< Fft2, LinOp >
Cgko::EnableLinOp< Fft2 >
►Cgko::EnableAbstractPolymorphicObject< Fft3, LinOp >
►Cgko::EnablePolymorphicObject< Fft3, LinOp >
Cgko::EnableLinOp< Fft3 >
►Cgko::EnableAbstractPolymorphicObject< FixedCoarsening< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< FixedCoarsening< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< FixedCoarsening< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Gcr< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Gcr< ValueType >, LinOp >
Cgko::EnableLinOp< Gcr< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Gmres< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Gmres< ValueType >, LinOp >
Cgko::EnableLinOp< Gmres< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Hybrid< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Hybrid< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Hybrid< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Ic< LSolverType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Ic< LSolverType, IndexType >, LinOp >
Cgko::EnableLinOp< Ic< LSolverType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Identity< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Identity< ValueType >, LinOp >
Cgko::EnableLinOp< Identity< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Idr< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Idr< ValueType >, LinOp >
Cgko::EnableLinOp< Idr< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Ilu< LSolverType, USolverType, ReverseApply, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Ilu< LSolverType, USolverType, ReverseApply, IndexType >, LinOp >
Cgko::EnableLinOp< Ilu< LSolverType, USolverType, ReverseApply, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Ir< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Ir< ValueType >, LinOp >
Cgko::EnableLinOp< Ir< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Isai< IsaiType, ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Isai< IsaiType, ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Isai< IsaiType, ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Jacobi< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Jacobi< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Jacobi< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< LowerTrs< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< LowerTrs< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< LowerTrs< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Matrix< ValueType, LocalIndexType, GlobalIndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Matrix< ValueType, LocalIndexType, GlobalIndexType >, LinOp >
Cgko::EnableLinOp< Matrix< ValueType, LocalIndexType, GlobalIndexType > >
►Cgko::EnableAbstractPolymorphicObject< Minres< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Minres< ValueType >, LinOp >
Cgko::EnableLinOp< Minres< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Multigrid, LinOp >
►Cgko::EnablePolymorphicObject< Multigrid, LinOp >
Cgko::EnableLinOp< Multigrid >
►Cgko::EnableAbstractPolymorphicObject< Permutation< IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Permutation< IndexType >, LinOp >
Cgko::EnableLinOp< Permutation< IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Perturbation< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Perturbation< ValueType >, LinOp >
Cgko::EnableLinOp< Perturbation< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< Pgm< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Pgm< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Pgm< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< RowGatherer< IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< RowGatherer< IndexType >, LinOp >
Cgko::EnableLinOp< RowGatherer< IndexType > >
►Cgko::EnableAbstractPolymorphicObject< ScaledPermutation< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< ScaledPermutation< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< ScaledPermutation< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< ScaledReordered< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< ScaledReordered< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< ScaledReordered< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Schwarz< ValueType, LocalIndexType, GlobalIndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Schwarz< ValueType, LocalIndexType, GlobalIndexType >, LinOp >
Cgko::EnableLinOp< Schwarz< ValueType, LocalIndexType, GlobalIndexType > >
►Cgko::EnableAbstractPolymorphicObject< Sellp< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< Sellp< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< Sellp< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< SparsityCsr< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< SparsityCsr< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< SparsityCsr< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< UpperTrs< ValueType, IndexType >, LinOp >
►Cgko::EnablePolymorphicObject< UpperTrs< ValueType, IndexType >, LinOp >
Cgko::EnableLinOp< UpperTrs< ValueType, IndexType > >
►Cgko::EnableAbstractPolymorphicObject< Vector< ValueType >, LinOp >
►Cgko::EnablePolymorphicObject< Vector< ValueType >, LinOp >
Cgko::EnableLinOp< Vector< ValueType > >
►Cgko::EnableAbstractPolymorphicObject< MultiVector< ValueType >, PolymorphicObject >
►Cgko::EnablePolymorphicObject< MultiVector< ValueType > >
Cgko::batch::MultiVector< ValueType >	MultiVector stores multiple vectors in a batched fashion and is useful for batched operations
►Cgko::EnableAbstractPolymorphicObject< Partition< LocalIndexType, GlobalIndexType >, PolymorphicObject >
►Cgko::EnablePolymorphicObject< Partition< LocalIndexType, GlobalIndexType > >
Cgko::experimental::distributed::Partition< LocalIndexType, GlobalIndexType >	Represents a partition of a range of indices [0, size) into a disjoint set of parts
►Cgko::EnableAbstractPolymorphicObject< ReorderingBase< IndexType > >
Cgko::reorder::ReorderingBase< IndexType >	The ReorderingBase class is a base class for all the reordering algorithms
Cgko::log::Record::logged_data	Struct storing the actually logged data
►Cgko::log::Logger
Cgko::batch::log::BatchConvergence< ValueType >	Logs the final residuals and iteration counts for a batch solver
Cgko::log::Convergence< ValueType >	Convergence is a Logger which logs data strictly from the criterion_check_completed event
Cgko::log::Papi< ValueType >	Papi is a Logger which logs every event to the PAPI software
Cgko::log::PerformanceHint	PerformanceHint is a Logger which analyzes the performance of the application and outputs hints for unnecessary copies and allocations
Cgko::log::ProfilerHook	This Logger can be used to annotate the execution of Ginkgo functionality with profiler-specific ranges
Cgko::log::Record	Record is a Logger which logs every event to an object
Cgko::log::SolverProgress	This Logger outputs the value of all scalar values (and potentially vectors) stored internally by the solver after each iteration
Cgko::log::Stream< ValueType >	Stream is a Logger which logs every event to a stream
Cgko::machine_topology	The machine topology class represents the hierarchical topology of a machine, including NUMA nodes, cores and PCI Devices
Cgko::matrix_assembly_data< ValueType, IndexType >	This structure is used as an intermediate type to assemble a sparse matrix
Cgko::matrix_data< ValueType, IndexType >	This structure is used as an intermediate data type to store a sparse matrix
Cgko::matrix_data_entry< ValueType, IndexType >	Type used to store nonzeros
Cgko::accessor::mmul_operation< Kind, FirstAccessor, SecondAccessor >
►Cgko::multigrid::MultigridLevel	This class represents two levels in a multigrid hierarchy
►Cgko::multigrid::EnableMultigridLevel< ValueType >	The EnableMultigridLevel gives the default implementation of MultigridLevel with composition and provides set_multigrid_level function
Cgko::multigrid::FixedCoarsening< ValueType, IndexType >	FixedCoarsening is a very simple coarse grid generation algorithm
Cgko::multigrid::Pgm< ValueType, IndexType >	Parallel graph match (Pgm) is the aggregate method introduced in the paper M
Cgko::log::ProfilerHook::nested_summary_entry
►Cgko::log::ProfilerHook::NestedSummaryWriter	Receives the results from ProfilerHook::create_nested_summary()
Cgko::log::ProfilerHook::TableSummaryWriter	Writes the results from ProfilerHook::create_summary() and ProfilerHook::create_nested_summary() to a ASCII table in Markdown format
Cgko::null_deleter< T >	This is a deleter that does not delete the object
Cgko::null_deleter< T[]>
Cgko::nvidia_device	Nvidia_device handles the number of executor on Nvidia devices and have the corresponding recursive_mutex
Cgko::Operation	Operations can be used to define functionalities whose implementations differ among devices
Cgko::log::operation_data	Struct representing Operator related data
►Cgko::Permutable< IndexType >	Linear operators which support permutation should implement the Permutable interface
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
►Cgko::Permutable< int32 >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
►Cgko::Permutable< int64 >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Csr< ValueType, IndexType >::permuting_reuse_info	A struct describing a transformation of the matrix that reorders the values of the matrix into the transformed matrix
Cgko::config::pnode	Pnode describes a tree of properties
Cgko::log::polymorphic_object_data	Struct representing PolymorphicObject related data
►CPolymorphicBase
►Cgko::EnableAbstractPolymorphicObject< ConcreteBatchLinOp, PolymorphicBase >
►Cgko::EnablePolymorphicObject< ConcreteBatchLinOp, PolymorphicBase >
Cgko::batch::EnableBatchLinOp< ConcreteBatchLinOp, PolymorphicBase >	The EnableBatchLinOp mixin can be used to provide sensible default implementations of the majority of the BatchLinOp and PolymorphicObject interface
►Cgko::EnableAbstractPolymorphicObject< ConcreteFactory, PolymorphicBase >
►Cgko::EnablePolymorphicObject< ConcreteFactory, PolymorphicBase >
Cgko::EnableDefaultFactory< ConcreteFactory, ProductType, ParametersType, PolymorphicBase >	This mixin provides a default implementation of a concrete factory
►Cgko::EnableAbstractPolymorphicObject< ConcreteLinOp, PolymorphicBase >
►Cgko::EnablePolymorphicObject< ConcreteLinOp, PolymorphicBase >
Cgko::EnableLinOp< ConcreteLinOp, PolymorphicBase >	The EnableLinOp mixin can be used to provide sensible default implementations of the majority of the LinOp and PolymorphicObject interface
►Cgko::EnableAbstractPolymorphicObject< ConcreteObject, PolymorphicBase >
Cgko::EnablePolymorphicObject< ConcreteObject, PolymorphicBase >	This mixin inherits from (a subclass of) PolymorphicObject and provides a base implementation of a new concrete polymorphic object
►Cgko::EnableAbstractPolymorphicObject< ConcreteSolver, PolymorphicBase >
►Cgko::EnablePolymorphicObject< ConcreteSolver, PolymorphicBase >
Cgko::batch::EnableBatchLinOp< ConcreteSolver, PolymorphicBase >
Cgko::EnableAbstractPolymorphicObject< AbstractObject, PolymorphicBase >	This mixin inherits from (a subclass of) PolymorphicObject and provides a base implementation of a new abstract object
Cgko::log::EnableLogging< ConcreteLoggable, PolymorphicBase >	EnableLogging is a mixin which should be inherited by any class which wants to enable logging
Cgko::precision_reduction	This class is used to encode storage precisions of low precision algorithms
►Cgko::Preconditionable	A LinOp implementing this interface can be preconditioned
►Cgko::solver::EnablePreconditionable< Bicg< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Bicg< ValueType > >
►Cgko::solver::EnablePreconditionable< Bicgstab< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Bicgstab< ValueType > >
►Cgko::solver::EnablePreconditionable< CbGmres< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, CbGmres< ValueType > >
►Cgko::solver::EnablePreconditionable< Cg< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Cg< ValueType > >
►Cgko::solver::EnablePreconditionable< Cgs< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Cgs< ValueType > >
►Cgko::solver::EnablePreconditionable< Fcg< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Fcg< ValueType > >
►Cgko::solver::EnablePreconditionable< Gcr< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Gcr< ValueType > >
►Cgko::solver::EnablePreconditionable< Gmres< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Gmres< ValueType > >
►Cgko::solver::EnablePreconditionable< Idr< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Idr< ValueType > >
►Cgko::solver::EnablePreconditionable< Minres< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Minres< ValueType > >
►Cgko::solver::EnablePreconditionable< DerivedType >	Mixin providing default operation for Preconditionable with correct value semantics
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, DerivedType >	A LinOp implementing this interface stores a system matrix and stopping criterion factory
Cgko::log::profiling_scope_guard	Scope guard that annotates its scope with the provided profiler hooks
Cgko::ptr_param< T >	This class is used for function parameters in the place of raw pointers
Cgko::range< Accessor >	A range is a multidimensional view of the memory
Cgko::syn::range< Start, End, Step >	Range records start, end, step in template
►Cgko::ReadableFromMatrixData< ValueType, IndexType >	A LinOp implementing this interface can read its data from a matrix_data structure
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Coo< ValueType, IndexType >	COO stores a matrix in the coordinate matrix format
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Ell< ValueType, IndexType >	ELL is a matrix format where stride with explicit zeros is used such that all rows have the same number of stored elements
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
Cgko::matrix::Hybrid< ValueType, IndexType >	HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
Cgko::matrix::Sellp< ValueType, IndexType >	SELL-P is a matrix format similar to ELL format
Cgko::matrix::SparsityCsr< ValueType, IndexType >	SparsityCsr is a matrix format which stores only the sparsity pattern of a sparse matrix by compressing each row of the matrix (compressed sparse row format)
►Cgko::ReadableFromMatrixData< ValueType, int32 >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
►Cgko::ReadableFromMatrixData< ValueType, int64 >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
Cgko::config::registry	This class stores additional context for creating Ginkgo objects from configuration files
►CReorderingBase
►Cgko::EnableAbstractPolymorphicObject< Rcm< ValueType, IndexType >, ReorderingBase< IndexType > >
►Cgko::EnablePolymorphicObject< Rcm< ValueType, IndexType >, ReorderingBase< IndexType > >
Cgko::reorder::Rcm< ValueType, IndexType >	Rcm (Reverse Cuthill-McKee) is a reordering algorithm minimizing the bandwidth of a matrix
Cgko::reorder::ReorderingBaseArgs	This struct is used to pass parameters to the EnableDefaultReorderingBaseFactory::generate() method
Cgko::experimental::mpi::request	Light, move-only wrapper around the MPI_Request handle
Cgko::accessor::row_major< ValueType, Dimensionality >	A row_major accessor is a bridge between a range and the row-major memory layout
►Cgko::ScaledIdentityAddable	Adds the operation M <- a I + b M for matrix M, identity operator I and scalars a and b, where M is the calling object
Cgko::matrix::Dense< value_type >
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::scoped_device_id_guard	This move-only class uses RAII to set the device id within a scoped block, if necessary
Cgko::segmented_array< T >	A minimal interface for a segmented array
Cgko::segmented_array< global_index_type >
Cgko::segmented_array< GlobalIndexType >
Cgko::segmented_array< local_index_type >
Cgko::segmented_array< LocalIndexType >
Cgko::segmented_array< size_type >
►Cgko::solver::detail::SolverBaseLinOp	A LinOp implementing this interface stores a system matrix
►Cgko::solver::SolverBase< MatrixType >
Cgko::solver::EnableSolverBase< DerivedType, MatrixType >	A LinOp deriving from this CRTP class stores a system matrix
►Cgko::solver::SolverBase< factorization::Factorization< ValueType, IndexType > >
►Cgko::solver::EnableSolverBase< Direct< ValueType, IndexType >, factorization::Factorization< ValueType, IndexType > >
Cgko::experimental::solver::Direct< ValueType, IndexType >	A direct solver based on a factorization into lower and upper triangular factors (with an optional diagonal scaling)
►Cgko::solver::SolverBase< LinOp >
►Cgko::solver::EnableSolverBase< Bicg< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Bicg< ValueType > >
►Cgko::solver::EnableSolverBase< Bicgstab< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Bicgstab< ValueType > >
►Cgko::solver::EnableSolverBase< CbGmres< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, CbGmres< ValueType > >
►Cgko::solver::EnableSolverBase< Cg< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Cg< ValueType > >
►Cgko::solver::EnableSolverBase< Cgs< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Cgs< ValueType > >
►Cgko::solver::EnableSolverBase< DerivedType >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, DerivedType >	A LinOp implementing this interface stores a system matrix and stopping criterion factory
►Cgko::solver::EnableSolverBase< Fcg< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Fcg< ValueType > >
►Cgko::solver::EnableSolverBase< Gcr< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Gcr< ValueType > >
►Cgko::solver::EnableSolverBase< Gmres< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Gmres< ValueType > >
►Cgko::solver::EnableSolverBase< Idr< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Idr< ValueType > >
►Cgko::solver::EnableSolverBase< Ir< ValueType > >
Cgko::solver::Ir< ValueType >	Iterative refinement (IR) is an iterative method that uses another coarse method to approximate the error of the current solution via the current residual
►Cgko::solver::EnableSolverBase< Minres< ValueType > >
Cgko::solver::EnablePreconditionedIterativeSolver< ValueType, Minres< ValueType > >
►Cgko::solver::EnableSolverBase< Multigrid >
Cgko::solver::Multigrid	Multigrid methods have a hierarchy of many levels, whose corase level is a subset of the fine level, of the problem
►Cgko::solver::SolverBase< matrix::Csr< ValueType, IndexType > >
►Cgko::solver::EnableSolverBase< LowerTrs< ValueType, IndexType >, matrix::Csr< ValueType, IndexType > >
Cgko::solver::LowerTrs< ValueType, IndexType >	LowerTrs is the triangular solver which solves the system L x = b, when L is a lower triangular matrix
►Cgko::solver::EnableSolverBase< UpperTrs< ValueType, IndexType >, matrix::Csr< ValueType, IndexType > >
Cgko::solver::UpperTrs< ValueType, IndexType >	UpperTrs is the triangular solver which solves the system U x = b, when U is an upper triangular matrix
Cgko::span	A span is a lightweight structure used to create sub-ranges from other ranges
Cgko::experimental::mpi::status	The status struct is a light wrapper around the MPI_Status struct
Cgko::stopping_status	This class is used to keep track of the stopping status of one vector
►Cgko::matrix::Csr< ValueType, IndexType >::strategy_type	Strategy_type is to decide how to set the csr algorithm
Cgko::matrix::Csr< ValueType, IndexType >::automatical
Cgko::matrix::Csr< ValueType, IndexType >::classical	Classical is a strategy_type which uses the same number of threads on each row
Cgko::matrix::Csr< ValueType, IndexType >::cusparse	Cusparse is a strategy_type which uses the sparselib csr
Cgko::matrix::Csr< ValueType, IndexType >::load_balance	Load_balance is a strategy_type which uses the load balance algorithm
Cgko::matrix::Csr< ValueType, IndexType >::merge_path	Merge_path is a strategy_type which uses the merge_path algorithm
Cgko::matrix::Csr< ValueType, IndexType >::sparselib	Sparselib is a strategy_type which uses the sparselib csr
►Cgko::matrix::Hybrid< ValueType, IndexType >::strategy_type	Strategy_type is to decide how to set the hybrid config
Cgko::matrix::Hybrid< ValueType, IndexType >::automatic	Automatic is a strategy_type which decides the number of stored elements per row of the ell part automatically
Cgko::matrix::Hybrid< ValueType, IndexType >::column_limit	Column_limit is a strategy_type which decides the number of stored elements per row of the ell part by specifying the number of columns
Cgko::matrix::Hybrid< ValueType, IndexType >::imbalance_bounded_limit	Imbalance_bounded_limit is a strategy_type which decides the number of stored elements per row of the ell part
Cgko::matrix::Hybrid< ValueType, IndexType >::imbalance_limit	Imbalance_limit is a strategy_type which decides the number of stored elements per row of the ell part according to the percent
Cgko::matrix::Hybrid< ValueType, IndexType >::minimal_storage_limit	Minimal_storage_limit is a strategy_type which decides the number of stored elements per row of the ell part
Cgko::log::ProfilerHook::summary_entry
►Cgko::log::ProfilerHook::SummaryWriter	Receives the results from ProfilerHook::create_summary()
Cgko::log::ProfilerHook::TableSummaryWriter	Writes the results from ProfilerHook::create_summary() and ProfilerHook::create_nested_summary() to a ASCII table in Markdown format
Cgko::time_point	An opaque wrapper for a time point generated by a timer
►Cgko::Timer	Represents a generic timer that can be used to record time points and measure time differences on host or device streams
Cgko::CpuTimer	A timer using std::chrono::steady_clock for timing
Cgko::CudaTimer	A timer using events for timing on a CudaExecutor
Cgko::DpcppTimer	A timer using kernels for timing on a DpcppExecutor in profiling mode
Cgko::HipTimer	A timer using events for timing on a HipExecutor
►Cgko::Transposable	Linear operators which support transposition should implement the Transposable interface
Cgko::matrix::Dense< value_type >
Cgko::Combination< ValueType >	The Combination class can be used to construct a linear combination of multiple linear operators c1 * op1 + c2 * op2 + ..
Cgko::Composition< ValueType >	The Composition class can be used to compose linear operators op1, op2, ..., opn and obtain the operator op1 * op2 * ..
Cgko::experimental::solver::Direct< ValueType, IndexType >	A direct solver based on a factorization into lower and upper triangular factors (with an optional diagonal scaling)
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
Cgko::matrix::Fft	This LinOp implements a 1D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft2	This LinOp implements a 2D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft3	This LinOp implements a 3D Fourier matrix using the FFT algorithm
Cgko::matrix::Identity< ValueType >	This class is a utility which efficiently implements the identity matrix (a linear operator which maps each vector to itself)
Cgko::matrix::SparsityCsr< ValueType, IndexType >	SparsityCsr is a matrix format which stores only the sparsity pattern of a sparse matrix by compressing each row of the matrix (compressed sparse row format)
Cgko::preconditioner::Ic< LSolverType, IndexType >	The Incomplete Cholesky (IC) preconditioner solves the equation for a given lower triangular matrix L and the right hand side b (can contain multiple right hand sides)
Cgko::preconditioner::Ilu< LSolverType, USolverType, ReverseApply, IndexType >	The Incomplete LU (ILU) preconditioner solves the equation for a given lower triangular matrix L, an upper triangular matrix U and the right hand side b (can contain multiple right hand sides)
Cgko::preconditioner::Isai< IsaiType, ValueType, IndexType >	The Incomplete Sparse Approximate Inverse (ISAI) Preconditioner generates an approximate inverse matrix for a given square matrix A, lower triangular matrix L, upper triangular matrix U or symmetric positive (spd) matrix B
Cgko::preconditioner::Jacobi< ValueType, IndexType >	A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks of the source operator
Cgko::solver::Bicg< ValueType >	BICG or the Biconjugate gradient method is a Krylov subspace solver
Cgko::solver::Bicgstab< ValueType >	BiCGSTAB or the Bi-Conjugate Gradient-Stabilized is a Krylov subspace solver
Cgko::solver::Cg< ValueType >	CG or the conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
Cgko::solver::Cgs< ValueType >	CGS or the conjugate gradient square method is an iterative type Krylov subspace method which is suitable for general systems
Cgko::solver::Fcg< ValueType >	FCG or the flexible conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
Cgko::solver::Gcr< ValueType >	GCR or the generalized conjugate residual method is an iterative type Krylov subspace method similar to GMRES which is suitable for nonsymmetric linear systems
Cgko::solver::Gmres< ValueType >	GMRES or the generalized minimal residual method is an iterative type Krylov subspace method which is suitable for nonsymmetric linear systems
Cgko::solver::Idr< ValueType >	IDR(s) is an efficient method for solving large nonsymmetric systems of linear equations
Cgko::solver::Ir< ValueType >	Iterative refinement (IR) is an iterative method that uses another coarse method to approximate the error of the current solution via the current residual
Cgko::solver::LowerTrs< ValueType, IndexType >	LowerTrs is the triangular solver which solves the system L x = b, when L is a lower triangular matrix
Cgko::solver::Minres< ValueType >	Minres is an iterative type Krylov subspace method, which is suitable for indefinite and full-rank symmetric/hermitian operators
Cgko::solver::UpperTrs< ValueType, IndexType >	UpperTrs is the triangular solver which solves the system U x = b, when U is an upper triangular matrix
Cgko::accessor::transpose_operation< Accessor >
►Ctrue_type
Cgko::are_all_integral< Args >	Evaluates if all template arguments Args fulfill std::is_integral
Cgko::truncated< typename, size_t, size_t >
►Ctype
Cgko::are_all_integral< First, Args... >
Cgko::config::type_descriptor	This class describes the value and index types to be used when building a Ginkgo type from a configuration file
Cgko::experimental::mpi::type_impl< T >	A struct that is used to determine the MPI_Datatype of a specified type
Cgko::experimental::mpi::type_impl< char >
Cgko::experimental::mpi::type_impl< double >
Cgko::experimental::mpi::type_impl< float >
Cgko::experimental::mpi::type_impl< int >
Cgko::experimental::mpi::type_impl< long >
Cgko::experimental::mpi::type_impl< long double >
Cgko::experimental::mpi::type_impl< long long >
Cgko::experimental::mpi::type_impl< unsigned >
Cgko::experimental::mpi::type_impl< unsigned char >
Cgko::experimental::mpi::type_impl< unsigned long >
Cgko::experimental::mpi::type_impl< unsigned long long >
Cgko::experimental::mpi::type_impl< unsigned short >
Cgko::syn::type_list< Types >	Type_list records several types in template
Cgko::stop::Criterion::Updater	Serves for convenient argument passing to the Criterion's check function
►Cgko::UseComposition< ValueType >	The UseComposition class can be used to store the composition information in LinOp
Cgko::multigrid::EnableMultigridLevel< ValueType >	The EnableMultigridLevel gives the default implementation of MultigridLevel with composition and provides set_multigrid_level function
Cgko::syn::value_list< T, Values >	Value_list records several values with the same type in template
Cgko::version	This structure is used to represent versions of various Ginkgo modules
Cgko::version_info	Ginkgo uses version numbers to label new features and to communicate backward compatibility guarantees:
Cgko::experimental::mpi::window< ValueType >	This class wraps the MPI_Window class with RAII functionality
Cgko::solver::workspace_traits< Solver >	Traits class providing information on the type and location of workspace vectors inside a solver
Cgko::solver::workspace_traits< Bicg< ValueType > >
Cgko::solver::workspace_traits< Bicgstab< ValueType > >
Cgko::solver::workspace_traits< Cg< ValueType > >
Cgko::solver::workspace_traits< Cgs< ValueType > >
Cgko::solver::workspace_traits< Fcg< ValueType > >
Cgko::solver::workspace_traits< Gcr< ValueType > >
Cgko::solver::workspace_traits< gko::experimental::solver::Direct< ValueType, IndexType > >
Cgko::solver::workspace_traits< Gmres< ValueType > >
Cgko::solver::workspace_traits< Idr< ValueType > >
Cgko::solver::workspace_traits< Ir< ValueType > >
Cgko::solver::workspace_traits< LowerTrs< ValueType, IndexType > >
Cgko::solver::workspace_traits< Minres< ValueType > >
Cgko::solver::workspace_traits< Multigrid >
Cgko::solver::workspace_traits< UpperTrs< ValueType, IndexType > >
►Cgko::WritableToMatrixData< ValueType, IndexType >	A LinOp implementing this interface can write its data to a matrix_data structure
Cgko::matrix::Dense< value_type >
Cgko::matrix::Dense< value_type >
Cgko::matrix::Coo< ValueType, IndexType >	COO stores a matrix in the coordinate matrix format
Cgko::matrix::Csr< ValueType, IndexType >	CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matrix (compressed sparse row format)
Cgko::matrix::Ell< ValueType, IndexType >	ELL is a matrix format where stride with explicit zeros is used such that all rows have the same number of stored elements
Cgko::matrix::Fbcsr< ValueType, IndexType >	Fixed-block compressed sparse row storage matrix format
Cgko::matrix::Hybrid< ValueType, IndexType >	HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
Cgko::matrix::ScaledPermutation< ValueType, IndexType >	ScaledPermutation is a matrix combining a permutation with scaling factors
Cgko::matrix::Sellp< ValueType, IndexType >	SELL-P is a matrix format similar to ELL format
Cgko::matrix::SparsityCsr< ValueType, IndexType >	SparsityCsr is a matrix format which stores only the sparsity pattern of a sparse matrix by compressing each row of the matrix (compressed sparse row format)
Cgko::preconditioner::Jacobi< ValueType, IndexType >	A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks of the source operator
►Cgko::WritableToMatrixData< default_precision, IndexType >
Cgko::matrix::Permutation< IndexType >	Permutation is a matrix format that represents a permutation matrix, i.e
►Cgko::WritableToMatrixData< std::complex< double >, int32 >
Cgko::matrix::Fft	This LinOp implements a 1D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft2	This LinOp implements a 2D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft3	This LinOp implements a 3D Fourier matrix using the FFT algorithm
►Cgko::WritableToMatrixData< std::complex< double >, int64 >
Cgko::matrix::Fft	This LinOp implements a 1D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft2	This LinOp implements a 2D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft3	This LinOp implements a 3D Fourier matrix using the FFT algorithm
►Cgko::WritableToMatrixData< std::complex< float >, int32 >
Cgko::matrix::Fft	This LinOp implements a 1D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft2	This LinOp implements a 2D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft3	This LinOp implements a 3D Fourier matrix using the FFT algorithm
►Cgko::WritableToMatrixData< std::complex< float >, int64 >
Cgko::matrix::Fft	This LinOp implements a 1D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft2	This LinOp implements a 2D Fourier matrix using the FFT algorithm
Cgko::matrix::Fft3	This LinOp implements a 3D Fourier matrix using the FFT algorithm
►Cgko::WritableToMatrixData< ValueType, int32 >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
►Cgko::WritableToMatrixData< ValueType, int64 >
Cgko::matrix::Dense< ValueType >	Dense is a matrix format which explicitly stores all values of the matrix
Cgko::matrix::Diagonal< ValueType >	This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)