Ginkgo: Class Hierarchy

| Ginkgo Generated from branch based on main. Ginkgo version 1.11.0 A numerical linear algebra library targeting many-core architectures

Loading...
Searching...
No Matches
Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 12345]

C gko::AbsoluteComputable | The AbsoluteComputable is an interface that allows to get the component wise absolute of a LinOp
C gko::EnableAbsoluteComputation< remove_complex< Vector< double > > > |
C gko::experimental::distributed::Vector< ValueType > | Vector is a format which explicitly stores (multiple) distributed column vectors in a dense storage format
C gko::EnableAbsoluteComputation< remove_complex< Coo< default_precision, int32 > > > |
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::EnableAbsoluteComputation< remove_complex< Csr< default_precision, int32 > > > |
C gko::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)
C gko::EnableAbsoluteComputation< remove_complex< Dense< default_precision > > > |
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::EnableAbsoluteComputation< remove_complex< Diagonal< default_precision > > > |
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::EnableAbsoluteComputation< remove_complex< Ell< default_precision, int32 > > > |
C gko::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
C gko::EnableAbsoluteComputation< remove_complex< Fbcsr< default_precision, int32 > > > |
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::EnableAbsoluteComputation< remove_complex< Hybrid< default_precision, int32 > > > |
C gko::matrix::Hybrid< ValueType, IndexType > | HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
C gko::EnableAbsoluteComputation< remove_complex< Sellp< default_precision, int32 > > > |
C gko::matrix::Sellp< ValueType, IndexType > | SELL-P is a matrix format similar to ELL format
C gko::EnableAbsoluteComputation< AbsoluteLinOp > | The EnableAbsoluteComputation mixin provides the default implementations of compute_absolute_linop and the absolute interface
C gko::experimental::distributed::Vector< ValueType > |
C gko::experimental::distributed::Vector< to_complex< value_type > > |
C gko::experimental::distributed::Vector< previous_precision< ValueType > > |
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Ell< value_type, index_type > |
C gko::matrix::Ell< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::Allocator | Provides generic allocation and deallocation functionality to be used by an Executor
C gko::CpuAllocatorBase | Implement this interface to provide an allocator for OmpExecutor or ReferenceExecutor
C gko::CpuAllocator | Allocator using new/delete
C gko::CudaHostAllocator |
C gko::CudaUnifiedAllocator |
C gko::HipHostAllocator |
C gko::HipUnifiedAllocator |
C gko::CudaAllocatorBase | Implement this interface to provide an allocator for CudaExecutor
C gko::CudaAllocator | Allocator using cudaMalloc
C gko::CudaAsyncAllocator |
C gko::CudaHostAllocator |
C gko::CudaUnifiedAllocator |
C gko::HipAllocatorBase | Implement this interface to provide an allocator for HipExecutor
C gko::HipAllocator |
C gko::HipAsyncAllocator |
C gko::HipHostAllocator |
C gko::HipUnifiedAllocator |
C gko::amd_device | Amd_device handles the number of executor on Amd devices and have the corresponding recursive_mutex
C gko::solver::ApplyWithInitialGuess | ApplyWithInitialGuess provides a way to give the input guess for apply function
C gko::solver::EnableApplyWithInitialGuess< Chebyshev< default_precision > > |
C gko::solver::Chebyshev< ValueType > | Chebyshev iteration is an iterative method for solving nonsymmetric problems based on some knowledge of the spectrum of the (preconditioned) system matrix
C gko::solver::EnableApplyWithInitialGuess< Multigrid > |
C gko::solver::Multigrid | Multigrid methods have a hierarchy of many levels, whose corase level is a subset of the fine level, of the problem
C gko::solver::EnableApplyWithInitialGuess< DerivedType > | EnableApplyWithInitialGuess providing default operation for ApplyWithInitialGuess with correct validation and log
C gko::solver::Chebyshev< ValueType > |
C gko::array< ValueType > | An array is a container which encapsulates fixed-sized arrays, stored on the Executor tied to the array
C gko::device_matrix_data< ValueType, IndexType >::arrays | Stores the internal arrays of a device_matrix_data object
C gko::batch_dim< Dimensionality, DimensionType > | A type representing the dimensions of a multidimensional batch object
C gko::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
C gko::batch::solver::EnableBatchSolver< Bicgstab< default_precision >, default_precision > |
C gko::batch::solver::Bicgstab< ValueType > | BiCGSTAB or the Bi-Conjugate Gradient-Stabilized is a Krylov subspace solver
C gko::batch::solver::EnableBatchSolver< Cg< default_precision >, default_precision > |
C gko::batch::solver::Cg< ValueType > | Cg or the Conjugate Gradient is a Krylov subspace solver
C gko::batch::solver::EnableBatchSolver< ConcreteSolver, ValueType, PolymorphicBase > | This mixin provides apply and common iterative solver functionality to all the batched solvers
C gko::bfloat16 | A class providing basic support for bfloat16 precision floating point types
C gko::preconditioner::block_interleaved_storage_scheme< IndexType > | Defines the parameters of the interleaved block storage scheme used by block-Jacobi blocks
C gko::experimental::mpi::CollectiveCommunicator | Interface for a collective communicator
C gko::experimental::mpi::DenseCommunicator | A CollectiveCommunicator that uses a dense communication
C gko::experimental::mpi::NeighborhoodCommunicator | A CollectiveCommunicator that uses a neighborhood topology
C gko::experimental::mpi::communicator | A thin wrapper of MPI_Comm that supports most MPI calls
C gko::experimental::mpi::contiguous_type | A move-only wrapper for a contiguous MPI_Datatype
CConvertibleTo |
C gko::EnablePolymorphicAssignment< BlockOperator > |
C gko::EnableLinOp< BlockOperator > |
C gko::BlockOperator | A BlockOperator represents a linear operator that is partitioned into multiple blocks
C gko::EnablePolymorphicAssignment< Combination< default_precision > > |
C gko::EnableLinOp< Combination< default_precision > > |
C gko::Combination< ValueType > | The Combination class can be used to construct a linear combination of multiple linear operators c1 * op1 + c2 * op2 + ... + ck * opk
C gko::EnablePolymorphicAssignment< Composition< default_precision > > |
C gko::EnableLinOp< Composition< default_precision > > |
C gko::Composition< default_precision > |
C gko::factorization::ParIc< ValueType, IndexType > | ParIC is an incomplete Cholesky factorization which is computed in parallel
C gko::factorization::ParIct< ValueType, IndexType > | ParICT is an incomplete threshold-based Cholesky factorization which is computed in parallel
C gko::factorization::ParIlu< ValueType, IndexType > | ParILU is an incomplete LU factorization which is computed in parallel
C gko::factorization::ParIlut< ValueType, IndexType > | ParILUT is an incomplete threshold-based LU factorization which is computed in parallel
C gko::Composition< ValueType > | The Composition class can be used to compose linear operators op1, op2, ..., opn and obtain the operator op1 * op2 * ... * opn
C gko::EnablePolymorphicAssignment< ConcreteFactory > |
C gko::EnableDefaultFactory< ConcreteFactory, ConcreteBatchLinOp, ParametersType, PolymorphicBase > |
C gko::batch::preconditioner::Jacobi< ValueType, IndexType >::Factory |
C gko::batch::solver::Bicgstab< ValueType >::Factory |
C gko::batch::solver::Cg< ValueType >::Factory |
C gko::EnableDefaultFactory< ConcreteFactory, ConcreteLinOp, ParametersType, PolymorphicBase > |
C gko::experimental::distributed::preconditioner::Schwarz< ValueType, LocalIndexType, GlobalIndexType >::Factory |
C gko::experimental::reorder::ScaledReordered< ValueType, IndexType >::Factory |
C gko::experimental::solver::Direct< ValueType, IndexType >::Factory |
C gko::factorization::Ic< ValueType, IndexType >::Factory |
C gko::factorization::Ilu< ValueType, IndexType >::Factory |
C gko::factorization::ParIc< ValueType, IndexType >::Factory |
C gko::factorization::ParIct< ValueType, IndexType >::Factory |
C gko::factorization::ParIlu< ValueType, IndexType >::Factory |
C gko::factorization::ParIlut< ValueType, IndexType >::Factory |
C gko::multigrid::FixedCoarsening< ValueType, IndexType >::Factory |
C gko::multigrid::Pgm< ValueType, IndexType >::Factory |
C gko::preconditioner::Ic< LSolverTypeOrValueType, IndexType >::Factory |
C gko::preconditioner::Ilu< LSolverTypeOrValueType, USolverTypeOrValueType, ReverseApply, IndexType >::Factory |
C gko::preconditioner::Isai< IsaiType, ValueType, IndexType >::Factory |
C gko::preconditioner::Jacobi< ValueType, IndexType >::Factory |
C gko::solver::Bicg< ValueType >::Factory |
C gko::solver::Bicgstab< ValueType >::Factory |
C gko::solver::CbGmres< ValueType >::Factory |
C gko::solver::Cg< ValueType >::Factory |
C gko::solver::Cgs< ValueType >::Factory |
C gko::solver::Chebyshev< ValueType >::Factory |
C gko::solver::Factory |
C gko::solver::Fcg< ValueType >::Factory |
C gko::solver::Gcr< ValueType >::Factory |
C gko::solver::Gmres< ValueType >::Factory |
C gko::solver::Idr< ValueType >::Factory |
C gko::solver::LowerTrs< ValueType, IndexType >::Factory |
C gko::solver::Minres< ValueType >::Factory |
C gko::solver::Multigrid::Factory |
C gko::solver::PipeCg< ValueType >::Factory |
C gko::solver::UpperTrs< ValueType, IndexType >::Factory |
C gko::EnableDefaultFactory< ConcreteFactory, ConcreteReorderingBase, ParametersType, PolymorphicBase > |
C gko::reorder::Rcm< ValueType, IndexType >::Factory |
C gko::EnableDefaultFactory< ConcreteFactory, ConcreteCriterion, ParametersType, PolymorphicBase > |
C gko::stop::AbsoluteResidualNorm< ValueType >::Factory |
C gko::stop::Combined::Factory |
C gko::stop::ImplicitResidualNorm< ValueType >::Factory |
C gko::stop::Iteration::Factory |
C gko::stop::RelativeResidualNorm< ValueType >::Factory |
C gko::stop::ResidualNorm< ValueType >::Factory |
C gko::stop::ResidualNormReduction< ValueType >::Factory |
C gko::stop::Time::Factory |
C gko::EnableDefaultFactory< ConcreteFactory, ProductType, ParametersType, PolymorphicBase > | This mixin provides a default implementation of a concrete factory
C gko::EnablePolymorphicAssignment< ConcreteLinOp > |
C gko::EnableLinOp< ConcreteLinOp, PolymorphicBase > | The EnableLinOp mixin can be used to provide sensible default implementations of the majority of the LinOp and PolymorphicObject interface
C gko::Combination< ValueType > |
C gko::Composition< ValueType > |
C gko::Composition< value_type > |
C gko::experimental::distributed::Vector< ValueType > |
C gko::experimental::distributed::Vector< to_complex< value_type > > |
C gko::experimental::distributed::Vector< previous_precision< ValueType > > |
C gko::experimental::factorization::Factorization< value_type, index_type > |
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Ell< value_type, index_type > |
C gko::matrix::Ell< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::matrix::Identity< ValueType > |
C gko::matrix::Permutation< index_type > |
C gko::matrix::Permutation< IndexType > |
C gko::matrix::SparsityCsr< value_type, index_type > |
C gko::matrix::SparsityCsr< IndexType, ValueType > |
C gko::matrix::SparsityCsr< ValueType, IndexType > |
C gko::preconditioner::Ic< LSolverTypeOrValueType, IndexType > |
C gko::preconditioner::Jacobi< ValueType, IndexType > |
C gko::solver::Bicg< ValueType > |
C gko::solver::Bicgstab< ValueType > |
C gko::solver::Cg< ValueType > |
C gko::solver::Cgs< ValueType > |
C gko::solver::Chebyshev< ValueType > |
C gko::solver::Fcg< ValueType > |
C gko::solver::Gcr< ValueType > |
C gko::solver::Gmres< ValueType > |
C gko::solver::Idr< ValueType > |
C gko::solver::LowerTrs< value_type, index_type > |
C gko::solver::LowerTrs< ValueType, IndexType > |
C gko::solver::Minres< ValueType > |
C gko::solver::PipeCg< ValueType > |
C gko::solver::UpperTrs< value_type, index_type > |
C gko::solver::UpperTrs< ValueType, IndexType > |
C gko::EnablePolymorphicAssignment< Perturbation< default_precision > > |
C gko::EnableLinOp< Perturbation< default_precision > > |
C gko::Perturbation< ValueType > | The Perturbation class can be used to construct a LinOp to represent the operation (identity + scalar * basis * projector)
C gko::EnablePolymorphicAssignment< ConcreteBatchLinOp > |
C gko::batch::EnableBatchLinOp< ConcreteBatchLinOp, PolymorphicBase > | The EnableBatchLinOp mixin can be used to provide sensible default implementations of the majority of the BatchLinOp and PolymorphicObject interface
C gko::batch::matrix::Csr< ValueType, IndexType > |
C gko::batch::matrix::Dense< ValueType > |
C gko::EnablePolymorphicAssignment< MultiVector< default_precision > > |
C gko::batch::MultiVector< ValueType > | MultiVector stores multiple vectors in a batched fashion and is useful for batched operations
C gko::EnablePolymorphicAssignment< Csr< default_precision, int32 > > |
C gko::EnableLinOp< Csr< default_precision, int32 > > |
C gko::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)
C gko::batch::EnableBatchLinOp< Csr< default_precision, int32 > > |
C gko::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
C gko::EnablePolymorphicAssignment< Dense< default_precision > > |
C gko::EnableLinOp< Dense< default_precision > > |
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::batch::EnableBatchLinOp< Dense< default_precision > > |
C gko::batch::matrix::Dense< ValueType > | Dense is a batch matrix format which explicitly stores all values of the matrix in each of the batches
C gko::EnablePolymorphicAssignment< Ell< default_precision, int32 > > |
C gko::EnableLinOp< Ell< default_precision, int32 > > |
C gko::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
C gko::batch::EnableBatchLinOp< Ell< default_precision, int32 > > |
C gko::batch::matrix::Ell< ValueType, IndexType > | Ell is a sparse matrix format that stores the same number of nonzeros in each row, enabling coalesced accesses
C gko::EnablePolymorphicAssignment< Identity< default_precision > > |
C gko::EnableLinOp< Identity< default_precision > > |
C gko::matrix::Identity< ValueType > | This class is a utility which efficiently implements the identity matrix (a linear operator which maps each vector to itself)
C gko::batch::EnableBatchLinOp< Identity< default_precision > > |
C gko::batch::matrix::Identity< ValueType > | The batch Identity matrix, which represents a batch of Identity matrices
C gko::EnablePolymorphicAssignment< Jacobi< default_precision, int32 > > |
C gko::EnableLinOp< Jacobi< default_precision, int32 > > |
C gko::preconditioner::Jacobi< ValueType, IndexType > | A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks of the source operator
C gko::batch::EnableBatchLinOp< Jacobi< default_precision, int32 > > |
C gko::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
C gko::EnablePolymorphicAssignment< Bicgstab< default_precision > > |
C gko::EnableLinOp< Bicgstab< default_precision > > |
C gko::solver::Bicgstab< ValueType > | BiCGSTAB or the Bi-Conjugate Gradient-Stabilized is a Krylov subspace solver
C gko::batch::EnableBatchLinOp< Bicgstab< default_precision >, BatchLinOp > |
C gko::batch::solver::EnableBatchSolver< Bicgstab< default_precision >, default_precision > |
C gko::EnablePolymorphicAssignment< Cg< default_precision > > |
C gko::EnableLinOp< Cg< default_precision > > |
C gko::solver::Cg< ValueType > | CG or the conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
C gko::batch::EnableBatchLinOp< Cg< default_precision >, BatchLinOp > |
C gko::batch::solver::EnableBatchSolver< Cg< default_precision >, default_precision > |
C gko::EnablePolymorphicAssignment< ConcreteSolver > |
C gko::batch::EnableBatchLinOp< ConcreteSolver, BatchLinOp > |
C gko::batch::solver::EnableBatchSolver< ConcreteSolver, ValueType, PolymorphicBase > | This mixin provides apply and common iterative solver functionality to all the batched solvers
C gko::EnablePolymorphicAssignment< Matrix< default_precision, int32, int64 > > |
C gko::EnableLinOp< Matrix< default_precision, int32, int64 > > |
C gko::experimental::distributed::Matrix< ValueType, LocalIndexType, GlobalIndexType > | The Matrix class defines a (MPI-)distributed matrix
C gko::EnablePolymorphicAssignment< Partition< int32, int64 > > |
C gko::experimental::distributed::Partition< LocalIndexType, GlobalIndexType > | Represents a partition of a range of indices [0, size) into a disjoint set of parts
C gko::EnablePolymorphicAssignment< RowGatherer< int32 > > |
C gko::EnableLinOp< RowGatherer< int32 > > |
C gko::matrix::RowGatherer< IndexType > | RowGatherer is a matrix "format" which stores the gather indices arrays which can be used to gather rows to another matrix
C gko::experimental::distributed::RowGatherer< LocalIndexType > | The distributed::RowGatherer gathers the rows of distributed::Vector that are located on other processes
C gko::EnablePolymorphicAssignment< Vector< double > > |
C gko::EnableLinOp< Vector< double > > |
C gko::experimental::distributed::Vector< ValueType > | Vector is a format which explicitly stores (multiple) distributed column vectors in a dense storage format
C gko::EnablePolymorphicAssignment< Schwarz< default_precision, int32, int64 > > |
C gko::EnableLinOp< Schwarz< default_precision, int32, int64 > > |
C gko::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
C gko::EnablePolymorphicAssignment< Cholesky< ValueType, IndexType > > |
C gko::experimental::factorization::Cholesky< ValueType, IndexType > | Computes a Cholesky factorization of a symmetric, positive-definite sparse matrix
C gko::EnablePolymorphicAssignment< Factorization< ValueType, IndexType > > |
C gko::EnableLinOp< Factorization< ValueType, IndexType > > |
C gko::experimental::factorization::Factorization< ValueType, IndexType > | Represents a generic factorization consisting of two triangular factors (upper and lower) and an optional diagonal scaling matrix
C gko::EnablePolymorphicAssignment< Lu< ValueType, IndexType > > |
C gko::experimental::factorization::Lu< ValueType, IndexType > | Computes an LU factorization of a sparse matrix
C gko::EnablePolymorphicAssignment< Amd< int32 > > |
C gko::experimental::reorder::Amd< IndexType > | Computes a Approximate Minimum Degree (AMD) reordering of an input matrix
C gko::EnablePolymorphicAssignment< Mc64< default_precision, int32 > > |
C gko::experimental::reorder::Mc64< ValueType, IndexType > | MC64 is an algorithm for permuting large entries to the diagonal of a sparse matrix
C gko::EnablePolymorphicAssignment< Rcm< int32 > > |
C gko::experimental::reorder::Rcm< IndexType > | Rcm (Reverse Cuthill-McKee) is a reordering algorithm minimizing the bandwidth of a matrix
C gko::EnablePolymorphicAssignment< ScaledReordered< default_precision, int32 > > |
C gko::EnableLinOp< ScaledReordered< default_precision, int32 > > |
C gko::experimental::reorder::ScaledReordered< ValueType, IndexType > | Provides an interface to wrap reorderings like Rcm and diagonal scaling like equilibration around a LinOp like e.g
C gko::EnablePolymorphicAssignment< Direct< ValueType, IndexType > > |
C gko::EnableLinOp< Direct< ValueType, IndexType > > |
C gko::experimental::solver::Direct< ValueType, IndexType > | A direct solver based on a factorization into lower and upper triangular factors (with an optional diagonal scaling)
C gko::EnablePolymorphicAssignment< Composition< gko::default_precision > > |
C gko::EnableLinOp< Composition< gko::default_precision > > |
C gko::Composition< gko::default_precision > |
C gko::factorization::Ic< ValueType, IndexType > | Represents an incomplete Cholesky factorization (IC(0)) of a sparse matrix
C gko::factorization::Ilu< ValueType, IndexType > | Represents an incomplete LU factorization – ILU(0) – of a sparse matrix
C gko::EnablePolymorphicAssignment< Coo< default_precision, int32 > > |
C gko::EnableLinOp< Coo< default_precision, int32 > > |
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::EnablePolymorphicAssignment< Diagonal< default_precision > > |
C gko::EnableLinOp< Diagonal< default_precision > > |
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::EnablePolymorphicAssignment< Fbcsr< default_precision, int32 > > |
C gko::EnableLinOp< Fbcsr< default_precision, int32 > > |
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::EnablePolymorphicAssignment< Fft > |
C gko::EnableLinOp< Fft > |
C gko::matrix::Fft | This LinOp implements a 1D Fourier matrix using the FFT algorithm
C gko::EnablePolymorphicAssignment< Fft2 > |
C gko::EnableLinOp< Fft2 > |
C gko::matrix::Fft2 | This LinOp implements a 2D Fourier matrix using the FFT algorithm
C gko::EnablePolymorphicAssignment< Fft3 > |
C gko::EnableLinOp< Fft3 > |
C gko::matrix::Fft3 | This LinOp implements a 3D Fourier matrix using the FFT algorithm
C gko::EnablePolymorphicAssignment< Hybrid< default_precision, int32 > > |
C gko::EnableLinOp< Hybrid< default_precision, int32 > > |
C gko::matrix::Hybrid< ValueType, IndexType > | HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
C gko::EnablePolymorphicAssignment< Permutation< int32 > > |
C gko::EnableLinOp< Permutation< int32 > > |
C gko::matrix::Permutation< IndexType > | Permutation is a matrix format that represents a permutation matrix, i.e
C gko::EnablePolymorphicAssignment< ScaledPermutation< default_precision, int32 > > |
C gko::EnableLinOp< ScaledPermutation< default_precision, int32 > > |
C gko::matrix::ScaledPermutation< ValueType, IndexType > | ScaledPermutation is a matrix combining a permutation with scaling factors
C gko::EnablePolymorphicAssignment< Sellp< default_precision, int32 > > |
C gko::EnableLinOp< Sellp< default_precision, int32 > > |
C gko::matrix::Sellp< ValueType, IndexType > | SELL-P is a matrix format similar to ELL format
C gko::EnablePolymorphicAssignment< SparsityCsr< default_precision, int32 > > |
C gko::EnableLinOp< SparsityCsr< default_precision, int32 > > |
C gko::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)
C gko::EnablePolymorphicAssignment< FixedCoarsening< default_precision, int32 > > |
C gko::EnableLinOp< FixedCoarsening< default_precision, int32 > > |
C gko::multigrid::FixedCoarsening< ValueType, IndexType > | FixedCoarsening is a very simple coarse grid generation algorithm
C gko::EnablePolymorphicAssignment< Pgm< default_precision, int32 > > |
C gko::EnableLinOp< Pgm< default_precision, int32 > > |
C gko::multigrid::Pgm< ValueType, IndexType > | Parallel graph match (Pgm) is the aggregate method introduced in the paper M
C gko::EnablePolymorphicAssignment< GaussSeidel< default_precision, int32 > > |
C gko::preconditioner::GaussSeidel< ValueType, IndexType > | This class generates the Gauss-Seidel preconditioner
C gko::EnablePolymorphicAssignment< Ic< solver::LowerTrs<>, int32 > > |
C gko::EnableLinOp< Ic< solver::LowerTrs<>, int32 > > |
C gko::preconditioner::Ic< LSolverTypeOrValueType, 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)
C gko::EnablePolymorphicAssignment< Isai< IsaiType, ValueType, IndexType > > |
C gko::EnableLinOp< Isai< IsaiType, ValueType, IndexType > > |
C gko::preconditioner::Isai< IsaiType==isai_type::general ? isai_type::general :IsaiType==isai_type::spd ? isai_type::spd :IsaiType==isai_type::lower ? isai_type::upper :isai_type::lower, ValueType, IndexType > |
C gko::preconditioner::Isai< isai_type::lower, ValueType, IndexType > |
C gko::preconditioner::Isai< isai_type::upper, ValueType, IndexType > |
C gko::preconditioner::Isai< isai_type::general, ValueType, IndexType > |
C gko::preconditioner::Isai< isai_type::spd, ValueType, IndexType > |
C gko::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
C gko::EnablePolymorphicAssignment< Sor< default_precision, int32 > > |
C gko::preconditioner::Sor< ValueType, IndexType > | This class generates the (S)SOR preconditioner
C gko::EnablePolymorphicAssignment< Rcm< default_precision, int32 > > |
C gko::reorder::Rcm< ValueType, IndexType > | Rcm (Reverse Cuthill-McKee) is a reordering algorithm minimizing the bandwidth of a matrix
C gko::EnablePolymorphicAssignment< Bicg< default_precision > > |
C gko::EnableLinOp< Bicg< default_precision > > |
C gko::solver::Bicg< ValueType > | BICG or the Biconjugate gradient method is a Krylov subspace solver
C gko::EnablePolymorphicAssignment< CbGmres< default_precision > > |
C gko::EnableLinOp< CbGmres< default_precision > > |
C gko::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
C gko::EnablePolymorphicAssignment< Cgs< default_precision > > |
C gko::EnableLinOp< Cgs< default_precision > > |
C gko::solver::Cgs< ValueType > | CGS or the conjugate gradient square method is an iterative type Krylov subspace method which is suitable for general systems
C gko::EnablePolymorphicAssignment< Chebyshev< default_precision > > |
C gko::EnableLinOp< Chebyshev< default_precision > > |
C gko::solver::Chebyshev< ValueType > | Chebyshev iteration is an iterative method for solving nonsymmetric problems based on some knowledge of the spectrum of the (preconditioned) system matrix
C gko::EnablePolymorphicAssignment< Fcg< default_precision > > |
C gko::EnableLinOp< Fcg< default_precision > > |
C gko::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
C gko::EnablePolymorphicAssignment< Gcr< default_precision > > |
C gko::EnableLinOp< Gcr< default_precision > > |
C gko::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
C gko::EnablePolymorphicAssignment< Gmres< default_precision > > |
C gko::EnableLinOp< Gmres< default_precision > > |
C gko::solver::Gmres< ValueType > | GMRES or the generalized minimal residual method is an iterative type Krylov subspace method which is suitable for nonsymmetric linear systems
C gko::EnablePolymorphicAssignment< Idr< default_precision > > |
C gko::EnableLinOp< Idr< default_precision > > |
C gko::solver::Idr< ValueType > | IDR(s) is an efficient method for solving large nonsymmetric systems of linear equations
C gko::EnablePolymorphicAssignment< LowerTrs< default_precision, int32 > > |
C gko::EnableLinOp< LowerTrs< default_precision, int32 > > |
C gko::solver::LowerTrs< ValueType, IndexType > | LowerTrs is the triangular solver which solves the system L x = b, when L is a lower triangular matrix
C gko::EnablePolymorphicAssignment< Minres< default_precision > > |
C gko::EnableLinOp< Minres< default_precision > > |
C gko::solver::Minres< ValueType > | Minres is an iterative type Krylov subspace method, which is suitable for indefinite and full-rank symmetric/hermitian operators
C gko::EnablePolymorphicAssignment< Multigrid > |
C gko::EnableLinOp< Multigrid > |
C gko::solver::Multigrid | Multigrid methods have a hierarchy of many levels, whose corase level is a subset of the fine level, of the problem
C gko::EnablePolymorphicAssignment< PipeCg< default_precision > > |
C gko::EnableLinOp< PipeCg< default_precision > > |
C gko::solver::PipeCg< ValueType > | PIPE_CG or the pipelined conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
C gko::EnablePolymorphicAssignment< UpperTrs< default_precision, int32 > > |
C gko::EnableLinOp< UpperTrs< default_precision, int32 > > |
C gko::solver::UpperTrs< ValueType, IndexType > | UpperTrs is the triangular solver which solves the system U x = b, when U is an upper triangular matrix
C gko::batch::matrix::Csr< ValueType, IndexType > |
C gko::batch::matrix::Dense< ValueType > |
C gko::experimental::distributed::Vector< ValueType > |
C gko::experimental::distributed::Vector< to_complex< value_type > > |
C gko::experimental::distributed::Vector< previous_precision< ValueType > > |
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Ell< value_type, index_type > |
C gko::matrix::Ell< value_type, index_type > |
C gko::matrix::Ell< value_type, index_type > |
C gko::matrix::Ell< ValueType, IndexType > |
C gko::matrix::Ell< ValueType, IndexType > |
C gko::matrix::Ell< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::matrix::SparsityCsr< value_type, index_type > |
C gko::matrix::SparsityCsr< value_type, index_type > |
C gko::matrix::SparsityCsr< IndexType, ValueType > |
C gko::matrix::SparsityCsr< IndexType, ValueType > |
C gko::matrix::SparsityCsr< ValueType, IndexType > |
C gko::matrix::SparsityCsr< ValueType, IndexType > |
C gko::preconditioner::Jacobi< ValueType, IndexType > |
C gko::EnablePolymorphicAssignment< ConcreteType, ResultType > | This mixin is used to enable a default PolymorphicObject::copy_from() implementation for objects that have implemented conversions between them
C gko::experimental::distributed::Partition< LocalIndexType, GlobalIndexType > |
C gko::batch::MultiVector< ValueType > | MultiVector stores multiple vectors in a batched fashion and is useful for batched operations
C gko::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
C gko::batch::matrix::Dense< ValueType > | Dense is a batch matrix format which explicitly stores all values of the matrix in each of the batches
C gko::batch::matrix::Ell< ValueType, IndexType > | Ell is a sparse matrix format that stores the same number of nonzeros in each row, enabling coalesced accesses
C gko::experimental::distributed::Matrix< ValueType, LocalIndexType, GlobalIndexType > | The Matrix class defines a (MPI-)distributed matrix
C gko::experimental::distributed::Vector< ValueType > | Vector is a format which explicitly stores (multiple) distributed column vectors in a dense storage format
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::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)
C gko::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)
C gko::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)
C gko::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)
C gko::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)
C gko::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)
C gko::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)
C gko::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)
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::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
C gko::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
C gko::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
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::matrix::Hybrid< ValueType, IndexType > | HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
C gko::matrix::Hybrid< ValueType, IndexType > | HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
C gko::matrix::Hybrid< ValueType, IndexType > | HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
C gko::matrix::Sellp< ValueType, IndexType > | SELL-P is a matrix format similar to ELL format
C gko::matrix::Sellp< ValueType, IndexType > | SELL-P is a matrix format similar to ELL format
C gko::matrix::Sellp< ValueType, IndexType > | SELL-P is a matrix format similar to ELL format
C gko::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)
C gko::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)
C gko::preconditioner::Jacobi< ValueType, IndexType > | A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks of the source operator
C gko::matrix::CooBuilder< ValueType, IndexType > |
C gko::cpx_real_type< T > | Access the underlying real type of a complex number
C gko::log::criterion_data | Struct representing Criterion related data
C gko::stop::CriterionArgs | This struct is used to pass parameters to the EnableDefaultCriterionFactoryCriterionFactory::generate() method
C gko::matrix::CsrBuilder< ValueType, IndexType > |
C gko::cuda_stream | An RAII wrapper for a custom CUDA stream
C gko::default_converter< S, R > | Used to convert objects of type S to objects of type R using static_cast
C gko::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
C gko::device_matrix_data< ValueType, IndexType > | This type is a device-side equivalent to matrix_data
C gko::DiagonalLinOpExtractable | The diagonal of a LinOp can be extracted
C gko::DiagonalExtractable< default_precision > |
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::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)
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::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
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::matrix::Hybrid< ValueType, IndexType > | HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
C gko::matrix::Sellp< ValueType, IndexType > | SELL-P is a matrix format similar to ELL format
C gko::DiagonalExtractable< ValueType > | The diagonal of a LinOp implementing this interface can be extracted
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Ell< value_type, index_type > |
C gko::matrix::Ell< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::dim< Dimensionality, DimensionType > | A type representing the dimensions of a multidimensional object
C gko::dim< 1u, DimensionType > |
C gko::experimental::distributed::DistributedBase | A base class for distributed objects
C gko::experimental::distributed::Vector< ValueType > |
C gko::experimental::distributed::Vector< to_complex< value_type > > |
C gko::experimental::distributed::Vector< previous_precision< ValueType > > |
C gko::experimental::distributed::Matrix< ValueType, LocalIndexType, GlobalIndexType > | The Matrix class defines a (MPI-)distributed matrix
C gko::experimental::distributed::RowGatherer< LocalIndexType > | The distributed::RowGatherer gathers the rows of distributed::Vector that are located on other processes
C gko::experimental::distributed::Vector< ValueType > | Vector is a format which explicitly stores (multiple) distributed column vectors in a dense storage format
C gko::enable_parameters_type< ConcreteParametersType, Factory > | The enable_parameters_type mixin is used to create a base implementation of the factory parameters structure
C gko::enable_parameters_type< Parameters, Factory > |
C gko::batch::solver::enable_preconditioned_iterative_solver_factory_parameters< Parameters, Factory > |
C gko::solver::enable_iterative_solver_factory_parameters< Parameters, Factory > |
C gko::solver::enable_preconditioned_iterative_solver_factory_parameters< Parameters, Factory > |
C gko::enable_parameters_type< parameters_type, Amd< IndexType > > |
C gko::experimental::reorder::Amd< IndexType >::parameters_type |
C gko::enable_parameters_type< parameters_type, Cholesky > |
C gko::experimental::factorization::Cholesky< ValueType, IndexType >::parameters_type |
C gko::enable_parameters_type< parameters_type, Factory > |
C gko::batch::solver::enable_preconditioned_iterative_solver_factory_parameters< parameters_type, Factory > |
C gko::batch::solver::Bicgstab< ValueType >::parameters_type |
C gko::batch::solver::Cg< ValueType >::parameters_type |
C gko::solver::enable_iterative_solver_factory_parameters< parameters_type, Factory > |
C gko::solver::enable_preconditioned_iterative_solver_factory_parameters< parameters_type, Factory > |
C gko::solver::Bicg< ValueType >::parameters_type |
C gko::solver::Bicgstab< ValueType >::parameters_type |
C gko::solver::CbGmres< ValueType >::parameters_type |
C gko::solver::Cg< ValueType >::parameters_type |
C gko::solver::Cgs< ValueType >::parameters_type |
C gko::solver::Chebyshev< ValueType >::parameters_type |
C gko::solver::Fcg< ValueType >::parameters_type |
C gko::solver::Gcr< ValueType >::parameters_type |
C gko::solver::Gmres< ValueType >::parameters_type |
C gko::solver::Idr< ValueType >::parameters_type |
C gko::solver::Minres< ValueType >::parameters_type |
C gko::solver::PipeCg< ValueType >::parameters_type |
C gko::solver::Multigrid::parameters_type |
C gko::solver::parameters_type |
C gko::batch::preconditioner::Jacobi< ValueType, IndexType >::parameters_type |
C gko::experimental::distributed::preconditioner::Schwarz< ValueType, LocalIndexType, GlobalIndexType >::parameters_type |
C gko::experimental::reorder::ScaledReordered< ValueType, IndexType >::parameters_type |
C gko::experimental::solver::Direct< ValueType, IndexType >::parameters_type |
C gko::factorization::Ic< ValueType, IndexType >::parameters_type |
C gko::factorization::Ilu< ValueType, IndexType >::parameters_type |
C gko::factorization::ParIc< ValueType, IndexType >::parameters_type |
C gko::factorization::ParIct< ValueType, IndexType >::parameters_type |
C gko::factorization::ParIlu< ValueType, IndexType >::parameters_type |
C gko::factorization::ParIlut< ValueType, IndexType >::parameters_type |
C gko::multigrid::FixedCoarsening< ValueType, IndexType >::parameters_type |
C gko::multigrid::Pgm< ValueType, IndexType >::parameters_type |
C gko::preconditioner::Ic< LSolverTypeOrValueType, IndexType >::parameters_type |
C gko::preconditioner::Ilu< LSolverTypeOrValueType, USolverTypeOrValueType, ReverseApply, IndexType >::parameters_type |
C gko::preconditioner::Isai< IsaiType, ValueType, IndexType >::parameters_type |
C gko::preconditioner::Jacobi< ValueType, IndexType >::parameters_type |
C gko::reorder::Rcm< ValueType, IndexType >::parameters_type |
C gko::solver::LowerTrs< ValueType, IndexType >::parameters_type |
C gko::solver::UpperTrs< ValueType, IndexType >::parameters_type |
C gko::stop::AbsoluteResidualNorm< ValueType >::parameters_type |
C gko::stop::Combined::parameters_type |
C gko::stop::ImplicitResidualNorm< ValueType >::parameters_type |
C gko::stop::Iteration::parameters_type |
C gko::stop::RelativeResidualNorm< ValueType >::parameters_type |
C gko::stop::ResidualNorm< ValueType >::parameters_type |
C gko::stop::ResidualNormReduction< ValueType >::parameters_type |
C gko::stop::Time::parameters_type |
C gko::enable_parameters_type< parameters_type, GaussSeidel > |
C gko::preconditioner::GaussSeidel< ValueType, IndexType >::parameters_type |
C gko::enable_parameters_type< parameters_type, Lu > |
C gko::experimental::factorization::Lu< ValueType, IndexType >::parameters_type |
C gko::enable_parameters_type< parameters_type, Mc64 > |
C gko::experimental::reorder::Mc64< ValueType, IndexType >::parameters_type |
C gko::enable_parameters_type< parameters_type, Rcm< IndexType > > |
C gko::experimental::reorder::Rcm< IndexType >::parameters_type |
C gko::enable_parameters_type< parameters_type, Sor > |
C gko::preconditioner::Sor< ValueType, IndexType >::parameters_type |
Cstd::enable_shared_from_this |
C gko::CudaExecutor | This is the Executor subclass which represents the CUDA device
C gko::DpcppExecutor | This is the Executor subclass which represents a DPC++ enhanced device
C gko::HipExecutor | This is the Executor subclass which represents the HIP enhanced device
C gko::OmpExecutor | This is the Executor subclass which represents the OpenMP device (typically CPU)
C gko::ReferenceExecutor | This is a specialization of the OmpExecutor, which runs the reference implementations of the kernels used for debugging purposes
CEnableAbstractPolymorphicObject |
C gko::AbstractFactory< ReorderingBase< IndexType >, ReorderingBaseArgs > |
C gko::AbstractFactory< gko::reorder::ReorderingBase< IndexType >, gko::reorder::ReorderingBaseArgs > |
C gko::AbstractFactory< Criterion, CriterionArgs > |
C gko::AbstractFactory< LinOp, std::shared_ptr< const LinOp > > |
C gko::LinOpFactory | A LinOpFactory represents a higher order mapping which transforms one linear operator into another
C gko::AbstractFactory< BatchLinOp, std::shared_ptr< const BatchLinOp > > |
C gko::batch::BatchLinOpFactory | A BatchLinOpFactory represents a higher order mapping which transforms one batch linear operator into another
C gko::EnablePolymorphicObject< BlockOperator, LinOp > |
C gko::EnableLinOp< BlockOperator > |
C gko::EnablePolymorphicObject< Combination< default_precision >, LinOp > |
C gko::EnableLinOp< Combination< default_precision > > |
C gko::EnablePolymorphicObject< Composition< default_precision >, LinOp > |
C gko::EnableLinOp< Composition< default_precision > > |
C gko::EnablePolymorphicObject< ConcreteFactory, PolymorphicBase > |
C gko::EnableDefaultFactory< ConcreteFactory, ConcreteBatchLinOp, ParametersType, PolymorphicBase > |
C gko::EnableDefaultFactory< ConcreteFactory, ConcreteLinOp, ParametersType, PolymorphicBase > |
C gko::EnableDefaultFactory< ConcreteFactory, ConcreteReorderingBase, ParametersType, PolymorphicBase > |
C gko::EnableDefaultFactory< ConcreteFactory, ConcreteCriterion, ParametersType, PolymorphicBase > |
C gko::EnableDefaultFactory< ConcreteFactory, ProductType, ParametersType, PolymorphicBase > | This mixin provides a default implementation of a concrete factory
C gko::EnablePolymorphicObject< ConcreteLinOp, LinOp > |
C gko::EnableLinOp< ConcreteLinOp, PolymorphicBase > | The EnableLinOp mixin can be used to provide sensible default implementations of the majority of the LinOp and PolymorphicObject interface
C gko::EnablePolymorphicObject< Perturbation< default_precision >, LinOp > |
C gko::EnableLinOp< Perturbation< default_precision > > |
C gko::EnablePolymorphicObject< ConcreteBatchLinOp, BatchLinOp > |
C gko::batch::EnableBatchLinOp< ConcreteBatchLinOp, PolymorphicBase > | The EnableBatchLinOp mixin can be used to provide sensible default implementations of the majority of the BatchLinOp and PolymorphicObject interface
C gko::EnablePolymorphicObject< MultiVector< default_precision > > |
C gko::batch::MultiVector< ValueType > | MultiVector stores multiple vectors in a batched fashion and is useful for batched operations
C gko::EnablePolymorphicObject< Csr< default_precision, int32 >, BatchLinOp > |
C gko::batch::EnableBatchLinOp< Csr< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Dense< default_precision >, BatchLinOp > |
C gko::batch::EnableBatchLinOp< Dense< default_precision > > |
C gko::EnablePolymorphicObject< Ell< default_precision, int32 >, BatchLinOp > |
C gko::batch::EnableBatchLinOp< Ell< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Identity< default_precision >, BatchLinOp > |
C gko::batch::EnableBatchLinOp< Identity< default_precision > > |
C gko::EnablePolymorphicObject< Jacobi< default_precision, int32 >, BatchLinOp > |
C gko::batch::EnableBatchLinOp< Jacobi< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Bicgstab< default_precision >, BatchLinOp > |
C gko::batch::EnableBatchLinOp< Bicgstab< default_precision >, BatchLinOp > |
C gko::EnablePolymorphicObject< Cg< default_precision >, BatchLinOp > |
C gko::batch::EnableBatchLinOp< Cg< default_precision >, BatchLinOp > |
C gko::EnablePolymorphicObject< ConcreteSolver, BatchLinOp > |
C gko::batch::EnableBatchLinOp< ConcreteSolver, BatchLinOp > |
C gko::EnablePolymorphicObject< Matrix< default_precision, int32, int64 >, LinOp > |
C gko::EnableLinOp< Matrix< default_precision, int32, int64 > > |
C gko::EnablePolymorphicObject< Partition< int32, int64 > > |
C gko::experimental::distributed::Partition< LocalIndexType, GlobalIndexType > | Represents a partition of a range of indices [0, size) into a disjoint set of parts
C gko::EnablePolymorphicObject< RowGatherer< int32 > > |
C gko::experimental::distributed::RowGatherer< LocalIndexType > | The distributed::RowGatherer gathers the rows of distributed::Vector that are located on other processes
C gko::EnablePolymorphicObject< Vector< double >, LinOp > |
C gko::EnableLinOp< Vector< double > > |
C gko::EnablePolymorphicObject< Schwarz< default_precision, int32, int64 >, LinOp > |
C gko::EnableLinOp< Schwarz< default_precision, int32, int64 > > |
C gko::EnablePolymorphicObject< Cholesky< ValueType, IndexType >, LinOpFactory > |
C gko::experimental::factorization::Cholesky< ValueType, IndexType > | Computes a Cholesky factorization of a symmetric, positive-definite sparse matrix
C gko::EnablePolymorphicObject< Factorization< ValueType, IndexType >, LinOp > |
C gko::EnableLinOp< Factorization< ValueType, IndexType > > |
C gko::EnablePolymorphicObject< Lu< ValueType, IndexType >, LinOpFactory > |
C gko::experimental::factorization::Lu< ValueType, IndexType > | Computes an LU factorization of a sparse matrix
C gko::EnablePolymorphicObject< Amd< int32 >, LinOpFactory > |
C gko::experimental::reorder::Amd< IndexType > | Computes a Approximate Minimum Degree (AMD) reordering of an input matrix
C gko::EnablePolymorphicObject< Mc64< default_precision, int32 >, LinOpFactory > |
C gko::experimental::reorder::Mc64< ValueType, IndexType > | MC64 is an algorithm for permuting large entries to the diagonal of a sparse matrix
C gko::EnablePolymorphicObject< Rcm< int32 >, LinOpFactory > |
C gko::experimental::reorder::Rcm< IndexType > | Rcm (Reverse Cuthill-McKee) is a reordering algorithm minimizing the bandwidth of a matrix
C gko::EnablePolymorphicObject< ScaledReordered< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< ScaledReordered< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Direct< ValueType, IndexType >, LinOp > |
C gko::EnableLinOp< Direct< ValueType, IndexType > > |
C gko::EnablePolymorphicObject< Composition< gko::default_precision >, LinOp > |
C gko::EnableLinOp< Composition< gko::default_precision > > |
C gko::EnablePolymorphicObject< Coo< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< Coo< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Csr< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< Csr< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Dense< default_precision >, LinOp > |
C gko::EnableLinOp< Dense< default_precision > > |
C gko::EnablePolymorphicObject< Diagonal< default_precision >, LinOp > |
C gko::EnableLinOp< Diagonal< default_precision > > |
C gko::EnablePolymorphicObject< Ell< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< Ell< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Fbcsr< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< Fbcsr< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Fft, LinOp > |
C gko::EnableLinOp< Fft > |
C gko::EnablePolymorphicObject< Fft2, LinOp > |
C gko::EnableLinOp< Fft2 > |
C gko::EnablePolymorphicObject< Fft3, LinOp > |
C gko::EnableLinOp< Fft3 > |
C gko::EnablePolymorphicObject< Hybrid< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< Hybrid< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Identity< default_precision >, LinOp > |
C gko::EnableLinOp< Identity< default_precision > > |
C gko::EnablePolymorphicObject< IdentityFactory< default_precision >, LinOpFactory > |
C gko::matrix::IdentityFactory< ValueType > | This factory is a utility which can be used to generate Identity operators
C gko::EnablePolymorphicObject< Permutation< int32 >, LinOp > |
C gko::EnableLinOp< Permutation< int32 > > |
C gko::EnablePolymorphicObject< RowGatherer< int32 >, LinOp > |
C gko::EnableLinOp< RowGatherer< int32 > > |
C gko::EnablePolymorphicObject< ScaledPermutation< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< ScaledPermutation< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Sellp< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< Sellp< default_precision, int32 > > |
C gko::EnablePolymorphicObject< SparsityCsr< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< SparsityCsr< default_precision, int32 > > |
C gko::EnablePolymorphicObject< FixedCoarsening< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< FixedCoarsening< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Pgm< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< Pgm< default_precision, int32 > > |
C gko::EnablePolymorphicObject< GaussSeidel< default_precision, int32 >, LinOpFactory > |
C gko::preconditioner::GaussSeidel< ValueType, IndexType > | This class generates the Gauss-Seidel preconditioner
C gko::EnablePolymorphicObject< Ic< solver::LowerTrs<>, int32 >, LinOp > |
C gko::EnableLinOp< Ic< solver::LowerTrs<>, int32 > > |
C gko::EnablePolymorphicObject< Isai< IsaiType, ValueType, IndexType >, LinOp > |
C gko::EnableLinOp< Isai< IsaiType, ValueType, IndexType > > |
C gko::EnablePolymorphicObject< Jacobi< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< Jacobi< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Sor< default_precision, int32 >, LinOpFactory > |
C gko::preconditioner::Sor< ValueType, IndexType > | This class generates the (S)SOR preconditioner
C gko::EnablePolymorphicObject< Rcm< default_precision, int32 >, ReorderingBase< int32 > > |
C gko::reorder::Rcm< ValueType, IndexType > | Rcm (Reverse Cuthill-McKee) is a reordering algorithm minimizing the bandwidth of a matrix
C gko::EnablePolymorphicObject< Bicg< default_precision >, LinOp > |
C gko::EnableLinOp< Bicg< default_precision > > |
C gko::EnablePolymorphicObject< Bicgstab< default_precision >, LinOp > |
C gko::EnableLinOp< Bicgstab< default_precision > > |
C gko::EnablePolymorphicObject< CbGmres< default_precision >, LinOp > |
C gko::EnableLinOp< CbGmres< default_precision > > |
C gko::EnablePolymorphicObject< Cg< default_precision >, LinOp > |
C gko::EnableLinOp< Cg< default_precision > > |
C gko::EnablePolymorphicObject< Cgs< default_precision >, LinOp > |
C gko::EnableLinOp< Cgs< default_precision > > |
C gko::EnablePolymorphicObject< Chebyshev< default_precision >, LinOp > |
C gko::EnableLinOp< Chebyshev< default_precision > > |
C gko::EnablePolymorphicObject< Fcg< default_precision >, LinOp > |
C gko::EnableLinOp< Fcg< default_precision > > |
C gko::EnablePolymorphicObject< Gcr< default_precision >, LinOp > |
C gko::EnableLinOp< Gcr< default_precision > > |
C gko::EnablePolymorphicObject< Gmres< default_precision >, LinOp > |
C gko::EnableLinOp< Gmres< default_precision > > |
C gko::EnablePolymorphicObject< Idr< default_precision >, LinOp > |
C gko::EnableLinOp< Idr< default_precision > > |
C gko::EnablePolymorphicObject< LowerTrs< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< LowerTrs< default_precision, int32 > > |
C gko::EnablePolymorphicObject< Minres< default_precision >, LinOp > |
C gko::EnableLinOp< Minres< default_precision > > |
C gko::EnablePolymorphicObject< Multigrid, LinOp > |
C gko::EnableLinOp< Multigrid > |
C gko::EnablePolymorphicObject< PipeCg< default_precision >, LinOp > |
C gko::EnableLinOp< PipeCg< default_precision > > |
C gko::EnablePolymorphicObject< UpperTrs< default_precision, int32 >, LinOp > |
C gko::EnableLinOp< UpperTrs< default_precision, int32 > > |
C gko::EnablePolymorphicObject< ResidualNormBase< default_precision >, Criterion > |
C gko::stop::ResidualNormBase< default_precision > |
C gko::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
C gko::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
C gko::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
C gko::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
C gko::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
C gko::EnablePolymorphicObject< Combined, Criterion > |
C gko::stop::Combined | Used to combine multiple criterions together through an OR operation
C gko::EnablePolymorphicObject< Iteration, Criterion > |
C gko::stop::Iteration | Stopping criterion which stops the iteration process after a preset number of iterations
C gko::EnablePolymorphicObject< ResidualNormBase< ValueType >, Criterion > |
C gko::stop::ResidualNormBase< ValueType > | The ResidualNormBase class provides a framework for stopping criteria related to the residual norm
C gko::EnablePolymorphicObject< Time, Criterion > |
C gko::stop::Time | Stopping criterion which stops the iteration process after a certain amount of time has passed
C gko::AbstractFactory< AbstractProductType, ComponentsType > | The AbstractFactory is a generic interface template that enables easy implementation of the abstract factory design pattern
C gko::EnablePolymorphicObject< ConcreteObject, PolymorphicBase > | This mixin inherits from (a subclass of) PolymorphicObject and provides a base implementation of a new concrete polymorphic object
C gko::experimental::distributed::Partition< LocalIndexType, GlobalIndexType > |
C gko::LinOp |
C gko::batch::BatchLinOp |
C gko::reorder::ReorderingBase< IndexType > | The ReorderingBase class is a base class for all the reordering algorithms
C gko::stop::Criterion | Base class for all stopping criteria
C gko::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
C gko::Combination< ValueType > |
C gko::Composition< ValueType > |
C gko::Composition< value_type > |
C gko::EnableCreateMethod< Combination< default_precision > > |
C gko::Combination< ValueType > | The Combination class can be used to construct a linear combination of multiple linear operators c1 * op1 + c2 * op2 + ... + ck * opk
C gko::EnableCreateMethod< Composition< default_precision > > |
C gko::Composition< default_precision > |
C gko::Composition< ValueType > | The Composition class can be used to compose linear operators op1, op2, ..., opn and obtain the operator op1 * op2 * ... * opn
C gko::EnableCreateMethod< Composition< gko::default_precision > > |
C gko::Composition< gko::default_precision > |
C gko::EnableCreateMethod< Perturbation< default_precision > > |
C gko::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
C gko::CudaExecutor | This is the Executor subclass which represents the CUDA device
C gko::HipExecutor | This is the Executor subclass which represents the HIP enhanced device
CEnableLinOp< Ilu< solver::LowerTrs<>, gko::detail::transposed_type< solver::LowerTrs<> >, false, int32 > > |
C gko::preconditioner::Ilu< LSolverTypeOrValueType, USolverTypeOrValueType, 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)
C gko::experimental::mpi::environment | Class that sets up and finalizes the MPI environment
C gko::err< T > |
Cstd::exception | STL class
C gko::Error | Used to report exceptional behaviour in library functions
C gko::AllocationError | AllocationError is thrown if a memory allocation fails
C gko::BadDimension | BadDimension is thrown if an operation is being applied to a LinOp with bad dimensions
C gko::BlockSizeError< IndexType > | Error that denotes issues between block sizes and matrix dimensions
C gko::CublasError | CublasError is thrown when a cuBLAS routine throws a non-zero error code
C gko::CudaError | CudaError is thrown when a CUDA routine throws a non-zero error code
C gko::CufftError | CufftError is thrown when a cuFFT routine throws a non-zero error code
C gko::CurandError | CurandError is thrown when a cuRAND routine throws a non-zero error code
C gko::CusparseError | CusparseError is thrown when a cuSPARSE routine throws a non-zero error code
C gko::DimensionMismatch | DimensionMismatch is thrown if an operation is being applied to LinOps of incompatible size
C gko::HipError | HipError is thrown when a HIP routine throws a non-zero error code
C gko::HipblasError | HipblasError is thrown when a hipBLAS routine throws a non-zero error code
C gko::HipfftError | HipfftError is thrown when a hipFFT routine throws a non-zero error code
C gko::HiprandError | HiprandError is thrown when a hipRAND routine throws a non-zero error code
C gko::HipsparseError | HipsparseError is thrown when a hipSPARSE routine throws a non-zero error code
C gko::InvalidStateError | Exception thrown if an object is in an invalid state
C gko::KernelNotFound | KernelNotFound is thrown if Ginkgo cannot find a kernel which satisfies the criteria imposed by the input arguments
C gko::MetisError | MetisError is thrown when METIS routine throws an error code
C gko::MpiError | MpiError is thrown when a MPI routine throws a non-zero error code
C gko::NotCompiled | NotCompiled is thrown when attempting to call an operation which is a part of a module that was not compiled on the system
C gko::NotImplemented | NotImplemented is thrown in case an operation has not yet been implemented (but will be implemented in the future)
C gko::NotSupported | NotSupported is thrown in case it is not possible to perform the requested operation on the given object type
C gko::OutOfBoundsError | OutOfBoundsError is thrown if a memory access is detected to be out-of-bounds
C gko::OverflowError | OverflowError is thrown when an index calculation for storage requirements overflows
C gko::StreamError | StreamError is thrown if accessing a stream failed
C gko::UnsupportedMatrixProperty | Exception throws if a matrix does not have a property required by a numerical method
C gko::ValueMismatch | ValueMismatch is thrown if two values are not equal
C gko::log::executor_data | Struct representing Executor related data
C gko::executor_deleter< T > | This is a deleter that uses an executor's free method to deallocate the data
C gko::executor_deleter< T[]> |
Cstd::false_type |
C gko::solver::has_with_criteria< SolverType, typename > | Helper structure to test if the Factory of SolverType has a function with_criteria
C gko::matrix::FbcsrBuilder< ValueType, IndexType > |
C gko::half | A class providing basic support for half precision floating point types
C gko::hip_stream | An RAII wrapper for a custom HIP stream
C hwloc_obj_t |
C hwloc_obj_type_t |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::add > |
C gko::accessor::add< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::bitwise_and > |
C gko::accessor::bitwise_and< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::bitwise_or > |
C gko::accessor::bitwise_or< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::bitwise_xor > |
C gko::accessor::bitwise_xor< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::div > |
C gko::accessor::div< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::equal > |
C gko::accessor::equal< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::greater > |
C gko::accessor::greater< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::greater_or_equal > |
C gko::accessor::greater_or_equal< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::left_shift > |
C gko::accessor::left_shift< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::less > |
C gko::accessor::less< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::less_or_equal > |
C gko::accessor::less_or_equal< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::logical_and > |
C gko::accessor::logical_and< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::logical_or > |
C gko::accessor::logical_or< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::max_operation > |
C gko::accessor::max_operation< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::min_operation > |
C gko::accessor::min_operation< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::mod > |
C gko::accessor::mod< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::mul > |
C gko::accessor::mul< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::not_equal > |
C gko::accessor::not_equal< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::right_shift > |
C gko::accessor::right_shift< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_binary_operation< Kind, FirstOperand, SecondOperand, ::gko::accessor::detail::sub > |
C gko::accessor::sub< Kind, FirstOperand, SecondOperand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::abs_operation > |
C gko::accessor::abs_operation< Operand > |
C gko::accessor::abs_operaton< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::bitwise_not > |
C gko::accessor::bitwise_not< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::conj_operation > |
C gko::accessor::conj_operation< Operand > |
C gko::accessor::conj_operaton< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::imag_operation > |
C gko::accessor::imag_operation< Operand > |
C gko::accessor::imag_operaton< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::logical_not > |
C gko::accessor::logical_not< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::one_operation > |
C gko::accessor::one_operation< Operand > |
C gko::accessor::one_operaton< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::real_operation > |
C gko::accessor::real_operation< Operand > |
C gko::accessor::real_operaton< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::squared_norm_operation > |
C gko::accessor::squared_norm_operation< Operand > |
C gko::accessor::squared_norm_operaton< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::unary_minus > |
C gko::accessor::unary_minus< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::unary_plus > |
C gko::accessor::unary_plus< Operand > |
Cgko::detail::implement_unary_operation< Operand, ::gko::accessor::detail::zero_operation > |
C gko::accessor::zero_operation< Operand > |
C gko::experimental::distributed::index_map< LocalIndexType, GlobalIndexType > | This class defines mappings between global and local indices
C gko::index_set< IndexType > | An index set class represents an ordered set of intervals
C gko::log::iteration_complete_data | Struct representing iteration complete related data
C gko::solver::IterativeBase | A LinOp implementing this interface stores a stopping criterion factory
C gko::solver::EnableIterativeBase< Bicg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Bicg< default_precision > > |
C gko::solver::Bicg< ValueType > | BICG or the Biconjugate gradient method is a Krylov subspace solver
C gko::solver::EnableIterativeBase< Bicgstab< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Bicgstab< default_precision > > |
C gko::solver::Bicgstab< ValueType > | BiCGSTAB or the Bi-Conjugate Gradient-Stabilized is a Krylov subspace solver
C gko::solver::EnableIterativeBase< CbGmres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, CbGmres< default_precision > > |
C gko::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
C gko::solver::EnableIterativeBase< Cg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Cg< default_precision > > |
C gko::solver::Cg< ValueType > | CG or the conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
C gko::solver::EnableIterativeBase< Cgs< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Cgs< default_precision > > |
C gko::solver::Cgs< ValueType > | CGS or the conjugate gradient square method is an iterative type Krylov subspace method which is suitable for general systems
C gko::solver::EnableIterativeBase< Chebyshev< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Chebyshev< default_precision > > |
C gko::solver::Chebyshev< ValueType > | Chebyshev iteration is an iterative method for solving nonsymmetric problems based on some knowledge of the spectrum of the (preconditioned) system matrix
C gko::solver::EnableIterativeBase< Fcg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Fcg< default_precision > > |
C gko::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
C gko::solver::EnableIterativeBase< Gcr< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Gcr< default_precision > > |
C gko::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
C gko::solver::EnableIterativeBase< Gmres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Gmres< default_precision > > |
C gko::solver::Gmres< ValueType > | GMRES or the generalized minimal residual method is an iterative type Krylov subspace method which is suitable for nonsymmetric linear systems
C gko::solver::EnableIterativeBase< Idr< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Idr< default_precision > > |
C gko::solver::Idr< ValueType > | IDR(s) is an efficient method for solving large nonsymmetric systems of linear equations
C gko::solver::EnableIterativeBase< Minres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Minres< default_precision > > |
C gko::solver::Minres< ValueType > | Minres is an iterative type Krylov subspace method, which is suitable for indefinite and full-rank symmetric/hermitian operators
C gko::solver::EnableIterativeBase< Multigrid > |
C gko::solver::Multigrid | Multigrid methods have a hierarchy of many levels, whose corase level is a subset of the fine level, of the problem
C gko::solver::EnableIterativeBase< PipeCg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, PipeCg< default_precision > > |
C gko::solver::PipeCg< ValueType > | PIPE_CG or the pipelined conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
C gko::solver::EnableIterativeBase< DerivedType > | A LinOp deriving from this CRTP class stores a stopping criterion factory and allows applying with a guess
C gko::solver::EnablePreconditionedIterativeSolver< ValueType, DerivedType > | A LinOp implementing this interface stores a system matrix and stopping criterion factory
C gko::solver::Bicg< ValueType > |
C gko::solver::Bicgstab< ValueType > |
C gko::solver::Cg< ValueType > |
C gko::solver::Cgs< ValueType > |
C gko::solver::Chebyshev< ValueType > |
C gko::solver::Fcg< ValueType > |
C gko::solver::Gcr< ValueType > |
C gko::solver::Gmres< ValueType > |
C gko::solver::Idr< ValueType > |
C gko::solver::Minres< ValueType > |
C gko::solver::PipeCg< ValueType > |
C gko::log::linop_data | Struct representing LinOp related data
C gko::log::linop_factory_data | Struct representing LinOp factory related data
C gko::log::Loggable | Loggable class is an interface which should be implemented by classes wanting to support logging
C gko::log::EnableLogging< Executor > |
C gko::Executor | The first step in using the Ginkgo library consists of creating an executor
Cgko::detail::ExecutorBase< CudaExecutor > |
C gko::CudaExecutor | This is the Executor subclass which represents the CUDA device
Cgko::detail::ExecutorBase< DpcppExecutor > |
C gko::DpcppExecutor | This is the Executor subclass which represents a DPC++ enhanced device
Cgko::detail::ExecutorBase< HipExecutor > |
C gko::HipExecutor | This is the Executor subclass which represents the HIP enhanced device
Cgko::detail::ExecutorBase< OmpExecutor > |
C gko::OmpExecutor | This is the Executor subclass which represents the OpenMP device (typically CPU)
C gko::log::EnableLogging< PolymorphicObject > |
C gko::PolymorphicObject | A PolymorphicObject is the abstract base for all "heavy" objects in Ginkgo that behave polymorphically
C gko::log::EnableLogging< ConcreteLoggable, PolymorphicBase > | EnableLogging is a mixin which should be inherited by any class which wants to enable logging
C gko::log::Record::logged_data | Struct storing the actually logged data
C gko::log::Logger |
C gko::batch::log::BatchConvergence< ValueType > | Logs the final residuals and iteration counts for a batch solver
C gko::log::Convergence< ValueType > | Convergence is a Logger which logs data strictly from the criterion_check_completed event
C gko::log::Papi< ValueType > | Papi is a Logger which logs every event to the PAPI software
C gko::log::PerformanceHint | PerformanceHint is a Logger which analyzes the performance of the application and outputs hints for unnecessary copies and allocations
C gko::log::ProfilerHook | This Logger can be used to annotate the execution of Ginkgo functionality with profiler-specific ranges
C gko::log::Record | Record is a Logger which logs every event to an object
C gko::log::SolverProgress | This Logger outputs the value of all scalar values (and potentially vectors) stored internally by the solver after each iteration
C gko::log::Stream< ValueType > | Stream is a Logger which logs every event to a stream
C gko::machine_topology | The machine topology class represents the hierarchical topology of a machine, including NUMA nodes, cores and PCI Devices
C gko::matrix_assembly_data< ValueType, IndexType > | This structure is used as an intermediate type to assemble a sparse matrix
C gko::matrix_data< ValueType, IndexType > | This structure is used as an intermediate data type to store a sparse matrix
C gko::matrix_data_entry< ValueType, IndexType > | Type used to store nonzeros
C gko::accessor::mmul_operation< Kind, FirstAccessor, SecondAccessor > |
C gko::multigrid::MultigridLevel | This class represents two levels in a multigrid hierarchy
C gko::multigrid::EnableMultigridLevel< default_precision > |
C gko::multigrid::FixedCoarsening< ValueType, IndexType > | FixedCoarsening is a very simple coarse grid generation algorithm
C gko::multigrid::Pgm< ValueType, IndexType > | Parallel graph match (Pgm) is the aggregate method introduced in the paper M
C gko::multigrid::EnableMultigridLevel< ValueType > | The EnableMultigridLevel gives the default implementation of MultigridLevel with composition and provides set_multigrid_level function
C gko::matrix::Csr< ValueType, IndexType >::multiply_add_reuse_info | Class describing the internal lookup structures created by multiply_add_reuse to recompute a sparse matrix-matrix product with updated values
C gko::matrix::Csr< ValueType, IndexType >::multiply_reuse_info | Class describing the internal lookup structures created by multiply_reuse(const Csr*) to recompute a sparse matrix-matrix product with updated values
C gko::log::ProfilerHook::nested_summary_entry |
C gko::log::ProfilerHook::NestedSummaryWriter | Receives the results from ProfilerHook::create_nested_summary()
C gko::log::ProfilerHook::TableSummaryWriter | Writes the results from ProfilerHook::create_summary() and ProfilerHook::create_nested_summary() to a ASCII table in Markdown format
C gko::null_deleter< T > | This is a deleter that does not delete the object
C gko::null_deleter< T[]> |
C gko::nvidia_device | Nvidia_device handles the number of executor on Nvidia devices and have the corresponding recursive_mutex
C gko::Operation | Operations can be used to define functionalities whose implementations differ among devices
C gko::log::operation_data | Struct representing Operator related data
C gko::Permutable< IndexType > | Linear operators which support permutation should implement the Permutable interface
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::Permutable< int32 > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::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)
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::Permutable< int64 > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::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
C gko::config::pnode | Pnode describes a tree of properties
C gko::log::polymorphic_object_data | Struct representing PolymorphicObject related data
C gko::precision_reduction | This class is used to encode storage precisions of low precision algorithms
C gko::Preconditionable | A LinOp implementing this interface can be preconditioned
C gko::solver::EnablePreconditionable< Bicg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Bicg< default_precision > > |
C gko::solver::EnablePreconditionable< Bicgstab< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Bicgstab< default_precision > > |
C gko::solver::EnablePreconditionable< CbGmres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, CbGmres< default_precision > > |
C gko::solver::EnablePreconditionable< Cg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Cg< default_precision > > |
C gko::solver::EnablePreconditionable< Cgs< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Cgs< default_precision > > |
C gko::solver::EnablePreconditionable< Chebyshev< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Chebyshev< default_precision > > |
C gko::solver::EnablePreconditionable< Fcg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Fcg< default_precision > > |
C gko::solver::EnablePreconditionable< Gcr< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Gcr< default_precision > > |
C gko::solver::EnablePreconditionable< Gmres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Gmres< default_precision > > |
C gko::solver::EnablePreconditionable< Idr< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Idr< default_precision > > |
C gko::solver::EnablePreconditionable< Minres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Minres< default_precision > > |
C gko::solver::EnablePreconditionable< PipeCg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, PipeCg< default_precision > > |
C gko::solver::EnablePreconditionable< DerivedType > | Mixin providing default operation for Preconditionable with correct value semantics
C gko::solver::EnablePreconditionedIterativeSolver< ValueType, DerivedType > | A LinOp implementing this interface stores a system matrix and stopping criterion factory
C gko::log::profiling_scope_guard | Scope guard that annotates its scope with the provided profiler hooks
C gko::ptr_param< T > | This class is used for function parameters in the place of raw pointers
C gko::range< Accessor > | A range is a multidimensional view of the memory
C gko::syn::range< Start, End, Step > | Range records start, end, step in template
C gko::ReadableFromMatrixData< ValueType, IndexType > | A LinOp implementing this interface can read its data from a matrix_data structure
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Ell< value_type, index_type > |
C gko::matrix::Ell< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::matrix::SparsityCsr< value_type, index_type > |
C gko::matrix::SparsityCsr< IndexType, ValueType > |
C gko::matrix::SparsityCsr< ValueType, IndexType > |
C gko::ReadableFromMatrixData< default_precision, int32 > |
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::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)
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::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
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::matrix::Hybrid< ValueType, IndexType > | HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
C gko::matrix::Sellp< ValueType, IndexType > | SELL-P is a matrix format similar to ELL format
C gko::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)
C gko::ReadableFromMatrixData< default_precision, int64 > |
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::config::registry | This class stores additional context for creating Ginkgo objects from configuration files
C gko::reorder::ReorderingBaseArgs | This struct is used to pass parameters to the EnableDefaultReorderingBaseFactory::generate() method
C gko::experimental::mpi::request | Light, move-only wrapper around the MPI_Request handle
C gko::accessor::row_major< ValueType, Dimensionality > | A row_major accessor is a bridge between a range and the row-major memory layout
C gko::matrix::Csr< ValueType, IndexType >::scale_add_reuse_info | Class describing the internal lookup structures created by scale_add_reuse to recompute a sparse matrix-matrix sum with updated values
C gko::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
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::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)
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::scoped_device_id_guard | This move-only class uses RAII to set the device id within a scoped block, if necessary
C gko::segmented_array< T > | A minimal interface for a segmented array
Cgko::solver::detail::SolverBaseLinOp | A LinOp implementing this interface stores a system matrix
C gko::solver::SolverBase< factorization::Factorization< ValueType, IndexType > > |
C gko::solver::EnableSolverBase< Direct< ValueType, IndexType >, factorization::Factorization< ValueType, IndexType > > |
C gko::experimental::solver::Direct< ValueType, IndexType > | A direct solver based on a factorization into lower and upper triangular factors (with an optional diagonal scaling)
C gko::solver::SolverBase< LinOp > |
C gko::solver::EnableSolverBase< Bicg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Bicg< default_precision > > |
C gko::solver::EnableSolverBase< Bicgstab< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Bicgstab< default_precision > > |
C gko::solver::EnableSolverBase< CbGmres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, CbGmres< default_precision > > |
C gko::solver::EnableSolverBase< Cg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Cg< default_precision > > |
C gko::solver::EnableSolverBase< Cgs< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Cgs< default_precision > > |
C gko::solver::EnableSolverBase< Chebyshev< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Chebyshev< default_precision > > |
C gko::solver::EnableSolverBase< Fcg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Fcg< default_precision > > |
C gko::solver::EnableSolverBase< Gcr< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Gcr< default_precision > > |
C gko::solver::EnableSolverBase< Gmres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Gmres< default_precision > > |
C gko::solver::EnableSolverBase< Idr< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Idr< default_precision > > |
C gko::solver::EnableSolverBase< Minres< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, Minres< default_precision > > |
C gko::solver::EnableSolverBase< Multigrid > |
C gko::solver::Multigrid | Multigrid methods have a hierarchy of many levels, whose corase level is a subset of the fine level, of the problem
C gko::solver::EnableSolverBase< PipeCg< default_precision > > |
C gko::solver::EnablePreconditionedIterativeSolver< default_precision, PipeCg< default_precision > > |
C gko::solver::EnableSolverBase< DerivedType, MatrixType > | A LinOp deriving from this CRTP class stores a system matrix
C gko::solver::LowerTrs< value_type, index_type > |
C gko::solver::LowerTrs< ValueType, IndexType > |
C gko::solver::UpperTrs< value_type, index_type > |
C gko::solver::UpperTrs< ValueType, IndexType > |
C gko::solver::EnablePreconditionedIterativeSolver< ValueType, DerivedType > | A LinOp implementing this interface stores a system matrix and stopping criterion factory
C gko::solver::SolverBase< matrix::Csr< default_precision, int32 > > |
C gko::solver::EnableSolverBase< LowerTrs< default_precision, int32 >, matrix::Csr< default_precision, int32 > > |
C gko::solver::LowerTrs< ValueType, IndexType > | LowerTrs is the triangular solver which solves the system L x = b, when L is a lower triangular matrix
C gko::solver::EnableSolverBase< UpperTrs< default_precision, int32 >, matrix::Csr< default_precision, int32 > > |
C gko::solver::UpperTrs< ValueType, IndexType > | UpperTrs is the triangular solver which solves the system U x = b, when U is an upper triangular matrix
C gko::solver::SolverBase< MatrixType > |
C gko::span | A span is a lightweight structure used to create sub-ranges from other ranges
C gko::local_span | A span that is used exclusively for local numbering
C gko::experimental::mpi::status | The status struct is a light wrapper around the MPI_Status struct
C gko::stopping_status | This class is used to keep track of the stopping status of one vector
C gko::matrix::Csr< ValueType, IndexType >::strategy_type | Strategy_type is to decide how to set the csr algorithm
C gko::matrix::Csr< ValueType, IndexType >::automatical |
C gko::matrix::Csr< ValueType, IndexType >::classical | Classical is a strategy_type which uses the same number of threads on each row
C gko::matrix::Csr< ValueType, IndexType >::cusparse | Cusparse is a strategy_type which uses the sparselib csr
C gko::matrix::Csr< ValueType, IndexType >::load_balance | Load_balance is a strategy_type which uses the load balance algorithm
C gko::matrix::Csr< ValueType, IndexType >::merge_path | Merge_path is a strategy_type which uses the merge_path algorithm
C gko::matrix::Csr< ValueType, IndexType >::sparselib | Sparselib is a strategy_type which uses the sparselib csr
C gko::matrix::Hybrid< ValueType, IndexType >::strategy_type | Strategy_type is to decide how to set the hybrid config
C gko::matrix::Hybrid< ValueType, IndexType >::automatic | Automatic is a strategy_type which decides the number of stored elements per row of the ell part automatically
C gko::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
C gko::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
C gko::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
C gko::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
C gko::log::ProfilerHook::summary_entry |
C gko::log::ProfilerHook::SummaryWriter | Receives the results from ProfilerHook::create_summary()
C gko::log::ProfilerHook::TableSummaryWriter | Writes the results from ProfilerHook::create_summary() and ProfilerHook::create_nested_summary() to a ASCII table in Markdown format
C gko::time_point | An opaque wrapper for a time point generated by a timer
C gko::Timer | Represents a generic timer that can be used to record time points and measure time differences on host or device streams
C gko::CpuTimer | A timer using std::chrono::steady_clock for timing
C gko::CudaTimer | A timer using events for timing on a CudaExecutor
C gko::DpcppTimer | A timer using kernels for timing on a DpcppExecutor in profiling mode
C gko::HipTimer | A timer using events for timing on a HipExecutor
C gko::Transposable | Linear operators which support transposition should implement the Transposable interface
C gko::Combination< ValueType > |
C gko::Composition< ValueType > |
C gko::Composition< value_type > |
C gko::Composition< gko::default_precision > |
C gko::Composition< default_precision > |
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::matrix::Identity< ValueType > |
C gko::matrix::SparsityCsr< value_type, index_type > |
C gko::matrix::SparsityCsr< IndexType, ValueType > |
C gko::matrix::SparsityCsr< ValueType, IndexType > |
C gko::preconditioner::Ic< LSolverTypeOrValueType, IndexType > |
C gko::preconditioner::Isai< IsaiType==isai_type::general ? isai_type::general :IsaiType==isai_type::spd ? isai_type::spd :IsaiType==isai_type::lower ? isai_type::upper :isai_type::lower, ValueType, IndexType > |
C gko::preconditioner::Isai< isai_type::lower, ValueType, IndexType > |
C gko::preconditioner::Isai< isai_type::upper, ValueType, IndexType > |
C gko::preconditioner::Isai< isai_type::general, ValueType, IndexType > |
C gko::preconditioner::Isai< isai_type::spd, ValueType, IndexType > |
C gko::preconditioner::Jacobi< ValueType, IndexType > |
C gko::solver::Bicg< ValueType > |
C gko::solver::Bicgstab< ValueType > |
C gko::solver::Cg< ValueType > |
C gko::solver::Cgs< ValueType > |
C gko::solver::Chebyshev< ValueType > |
C gko::solver::Fcg< ValueType > |
C gko::solver::Gcr< ValueType > |
C gko::solver::Gmres< ValueType > |
C gko::solver::Idr< ValueType > |
C gko::solver::LowerTrs< value_type, index_type > |
C gko::solver::LowerTrs< ValueType, IndexType > |
C gko::solver::Minres< ValueType > |
C gko::solver::PipeCg< ValueType > |
C gko::solver::UpperTrs< value_type, index_type > |
C gko::solver::UpperTrs< ValueType, IndexType > |
C gko::Combination< ValueType > | The Combination class can be used to construct a linear combination of multiple linear operators c1 * op1 + c2 * op2 + ... + ck * opk
C gko::Composition< ValueType > | The Composition class can be used to compose linear operators op1, op2, ..., opn and obtain the operator op1 * op2 * ... * opn
C gko::experimental::solver::Direct< ValueType, IndexType > | A direct solver based on a factorization into lower and upper triangular factors (with an optional diagonal scaling)
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::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)
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::matrix::Fft | This LinOp implements a 1D Fourier matrix using the FFT algorithm
C gko::matrix::Fft2 | This LinOp implements a 2D Fourier matrix using the FFT algorithm
C gko::matrix::Fft3 | This LinOp implements a 3D Fourier matrix using the FFT algorithm
C gko::matrix::Identity< ValueType > | This class is a utility which efficiently implements the identity matrix (a linear operator which maps each vector to itself)
C gko::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)
C gko::preconditioner::Ic< LSolverTypeOrValueType, 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)
C gko::preconditioner::Ilu< LSolverTypeOrValueType, USolverTypeOrValueType, 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)
C gko::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
C gko::preconditioner::Jacobi< ValueType, IndexType > | A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks of the source operator
C gko::solver::Bicg< ValueType > | BICG or the Biconjugate gradient method is a Krylov subspace solver
C gko::solver::Bicgstab< ValueType > | BiCGSTAB or the Bi-Conjugate Gradient-Stabilized is a Krylov subspace solver
C gko::solver::Cg< ValueType > | CG or the conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
C gko::solver::Cgs< ValueType > | CGS or the conjugate gradient square method is an iterative type Krylov subspace method which is suitable for general systems
C gko::solver::Chebyshev< ValueType > | Chebyshev iteration is an iterative method for solving nonsymmetric problems based on some knowledge of the spectrum of the (preconditioned) system matrix
C gko::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
C gko::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
C gko::solver::Gmres< ValueType > | GMRES or the generalized minimal residual method is an iterative type Krylov subspace method which is suitable for nonsymmetric linear systems
C gko::solver::Idr< ValueType > | IDR(s) is an efficient method for solving large nonsymmetric systems of linear equations
C gko::solver::LowerTrs< ValueType, IndexType > | LowerTrs is the triangular solver which solves the system L x = b, when L is a lower triangular matrix
C gko::solver::Minres< ValueType > | Minres is an iterative type Krylov subspace method, which is suitable for indefinite and full-rank symmetric/hermitian operators
C gko::solver::PipeCg< ValueType > | PIPE_CG or the pipelined conjugate gradient method is an iterative type Krylov subspace method which is suitable for symmetric positive definite methods
C gko::solver::UpperTrs< ValueType, IndexType > | UpperTrs is the triangular solver which solves the system U x = b, when U is an upper triangular matrix
C gko::accessor::transpose_operation< Accessor > |
Cstd::true_type |
C gko::are_all_integral< First, Args... > |
C gko::are_all_integral< Args > | Evaluates if all template arguments Args fulfill std::is_integral
C gko::truncated< typename, size_t, size_t > |
Cstd::conditional::type |
C gko::are_all_integral< First, Args... > |
C gko::config::type_descriptor | This class describes the value and index types to be used when building a Ginkgo type from a configuration file
C gko::xstd::type_identity< T > |
C gko::experimental::mpi::type_impl< T > | A struct that is used to determine the MPI_Datatype of a specified type
C gko::experimental::mpi::type_impl< char > |
C gko::experimental::mpi::type_impl< double > |
C gko::experimental::mpi::type_impl< float > |
C gko::experimental::mpi::type_impl< int > |
C gko::experimental::mpi::type_impl< long > |
C gko::experimental::mpi::type_impl< long double > |
C gko::experimental::mpi::type_impl< long long > |
C gko::experimental::mpi::type_impl< unsigned > |
C gko::experimental::mpi::type_impl< unsigned char > |
C gko::experimental::mpi::type_impl< unsigned long > |
C gko::experimental::mpi::type_impl< unsigned long long > |
C gko::experimental::mpi::type_impl< unsigned short > |
C gko::syn::type_list< Types > | Type_list records several types in template
C gko::stop::Criterion::Updater | Serves for convenient argument passing to the Criterion's check function
C gko::UseComposition< ValueType > | The UseComposition class can be used to store the composition information in LinOp
C gko::UseComposition< default_precision > |
C gko::multigrid::EnableMultigridLevel< default_precision > |
C gko::UseComposition< ValueType > |
C gko::multigrid::EnableMultigridLevel< ValueType > | The EnableMultigridLevel gives the default implementation of MultigridLevel with composition and provides set_multigrid_level function
C gko::syn::value_list< T, Values > | Value_list records several values with the same type in template
C gko::version | This structure is used to represent versions of various Ginkgo modules
C gko::version_info | Ginkgo uses version numbers to label new features and to communicate backward compatibility guarantees:
C gko::experimental::mpi::window< ValueType > | This class wraps the MPI_Window class with RAII functionality
C gko::solver::workspace_traits< Solver > | Traits class providing information on the type and location of workspace vectors inside a solver
C gko::solver::workspace_traits< Bicg< ValueType > > |
C gko::solver::workspace_traits< Bicgstab< ValueType > > |
C gko::solver::workspace_traits< Cg< ValueType > > |
C gko::solver::workspace_traits< Cgs< ValueType > > |
C gko::solver::workspace_traits< Chebyshev< ValueType > > |
C gko::solver::workspace_traits< Fcg< ValueType > > |
C gko::solver::workspace_traits< Gcr< ValueType > > |
C gko::solver::workspace_traits< gko::experimental::solver::Direct< ValueType, IndexType > > |
C gko::solver::workspace_traits< Gmres< ValueType > > |
C gko::solver::workspace_traits< Idr< ValueType > > |
C gko::solver::workspace_traits< LowerTrs< ValueType, IndexType > > |
C gko::solver::workspace_traits< Minres< ValueType > > |
C gko::solver::workspace_traits< Multigrid > |
C gko::solver::workspace_traits< PipeCg< ValueType > > |
C gko::solver::workspace_traits< UpperTrs< ValueType, IndexType > > |
C gko::WritableToMatrixData< ValueType, IndexType > | A LinOp implementing this interface can write its data to a matrix_data structure
C gko::matrix::Coo< ValueType, IndexType > |
C gko::matrix::Csr< value_type, index_type > |
C gko::matrix::Csr< ValueType, IndexType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< ValueType > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< value_type > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< to_complex< ValueType > > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< absolute_type > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Dense< remove_complex< ValueType > > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Diagonal< ValueType > |
C gko::matrix::Ell< value_type, index_type > |
C gko::matrix::Ell< ValueType, IndexType > |
C gko::matrix::Fbcsr< ValueType, IndexType > |
C gko::matrix::Permutation< index_type > |
C gko::matrix::Permutation< IndexType > |
C gko::matrix::SparsityCsr< value_type, index_type > |
C gko::matrix::SparsityCsr< IndexType, ValueType > |
C gko::matrix::SparsityCsr< ValueType, IndexType > |
C gko::preconditioner::Jacobi< ValueType, IndexType > |
C gko::WritableToMatrixData< default_precision, int32 > |
C gko::matrix::Coo< ValueType, IndexType > | COO stores a matrix in the coordinate matrix format
C gko::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)
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::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
C gko::matrix::Fbcsr< ValueType, IndexType > | Fixed-block compressed sparse row storage matrix format
C gko::matrix::Hybrid< ValueType, IndexType > | HYBRID is a matrix format which splits the matrix into ELLPACK and COO format
C gko::matrix::Permutation< IndexType > | Permutation is a matrix format that represents a permutation matrix, i.e
C gko::matrix::ScaledPermutation< ValueType, IndexType > | ScaledPermutation is a matrix combining a permutation with scaling factors
C gko::matrix::Sellp< ValueType, IndexType > | SELL-P is a matrix format similar to ELL format
C gko::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)
C gko::preconditioner::Jacobi< ValueType, IndexType > | A block-Jacobi preconditioner is a block-diagonal linear operator, obtained by inverting the diagonal blocks of the source operator
C gko::WritableToMatrixData< default_precision, int64 > |
C gko::matrix::Dense< ValueType > | Dense is a matrix format which explicitly stores all values of the matrix
C gko::matrix::Diagonal< ValueType > | This class is a utility which efficiently implements the diagonal matrix (a linear operator which scales a vector row wise)
C gko::WritableToMatrixData< std::complex< double >, int32 > |
C gko::matrix::Fft | This LinOp implements a 1D Fourier matrix using the FFT algorithm
C gko::matrix::Fft2 | This LinOp implements a 2D Fourier matrix using the FFT algorithm
C gko::matrix::Fft3 | This LinOp implements a 3D Fourier matrix using the FFT algorithm
C gko::WritableToMatrixData< std::complex< double >, int64 > |
C gko::matrix::Fft | This LinOp implements a 1D Fourier matrix using the FFT algorithm
C gko::matrix::Fft2 | This LinOp implements a 2D Fourier matrix using the FFT algorithm
C gko::matrix::Fft3 | This LinOp implements a 3D Fourier matrix using the FFT algorithm
C gko::WritableToMatrixData< std::complex< float >, int32 > |
C gko::matrix::Fft | This LinOp implements a 1D Fourier matrix using the FFT algorithm
C gko::matrix::Fft2 | This LinOp implements a 2D Fourier matrix using the FFT algorithm
C gko::matrix::Fft3 | This LinOp implements a 3D Fourier matrix using the FFT algorithm
C gko::WritableToMatrixData< std::complex< float >, int64 > |
C gko::matrix::Fft | This LinOp implements a 1D Fourier matrix using the FFT algorithm
C gko::matrix::Fft2 | This LinOp implements a 2D Fourier matrix using the FFT algorithm
C gko::matrix::Fft3 | This LinOp implements a 3D Fourier matrix using the FFT algorithm