Data Structures

Here are the data structures with brief descriptions:

[detail level 123]

►Nctf
►Ncore
Ccomm
Ccontract_term
Citensor
Csum_term
Ctensor
Cterm
►NCTF
CBivar_Function	Custom bivariate function on two tensors: e.g. C["ij"] = f(A["ik"],B["kj"])
CBivar_Kernel
CBivar_Transform	Custom function f : (X * Y * Z) -> Z applied on three tensors as contraction: e.g. f(A["ij"],B["ij"],C["ij"])
CDecomposition
CdtypePair	Pair for sorting
CEndomorphism	Custom scalar function on tensor: e.g. A["ij"] = f(A["ij"])
CFlop_counter	Term is an abstract object representing some expression of tensors
CFunction
CFunction_timer	Times a specific symbol
CGroup	Group is a Monoid with operator '-' defined special case (parent) of a ring
CHoSVD
CIdx_Partition
CIdx_Tensor	Tensor with an index map associated with it (necessary for overloaded operators)
CMatrix	Matrix class which encapsulates a 2D tensor
CMonoid	A Monoid is a Set equipped with a binary addition operator '+' or a custom function addition must have an identity and be associative, does not need to be commutative special case (parent) of a semiring, group, and ring
CMonoid_Kernel
CPair	Index-value pair used for tensor data input
CPartition
CPartitionOps	Data structure containing what each partition is going to do
CRing	Ring class defined by a datatype and addition and multiplicaton functions addition must have an identity, inverse, and be associative, does not need to be commutative multiplications must have an identity and be distributive
CScalar	Scalar class which encapsulates a 0D tensor
CSchedule
CScheduleBase
CScheduleTimer
CSemiring	Semiring is a Monoid with an addition multiplicaton function addition must have an identity and be associative, does not need to be commutative multiplications must have an identity as well as be distributive and associative special case (parent) of a Ring (which also has an additive inverse)
CSet	Set class defined by a datatype and a min/max function (if it is partially ordered i.e. is_ord=true) currently assumes min and max are given by numeric_limits (custom min/max not allowed)
CSparse_Tensor	Sparse subset of a tensor
CTensor	Instance of a tensor within a CTF world
CTensorOperation	A tensor operation, containing all the data (op, lhs, rhs) required to run it. Also provides methods to get a list of inputs and outputs, as well as successor and dependency information used in scheduling
CTensorOperationBase	Provides a untemplated base class for tensor operations
CTimer	Local process walltime measurement
CTimer_epoch	Epoch during which to measure timers
CTransform
CTyp_AIdx_Tensor
CTyp_Contract_Term
CTyp_Idx_Tensor
CTyp_Sum_Term
CUnivar_Function	Custom function f : X -> Y to be applied to tensor elemetns: e.g. B["ij"] = f(A["ij"])
CUnivar_Transform	Custom function f : (X * Y) -> X applied on two tensors as summation: e.g. B["ij"] = f(A["ij"],B["ij"])
CVector	Vector class which encapsulates a 1D tensor
CWorld	Instance of the CTF library (world) on a MPI communicator
►NCTF_int
Caccumulatable	Abstract class that knows how to add
Calgstrct	Algstrct (algebraic structure) defines the elementwise operations computed in each tensor contraction, virtual classes defined in derived typed classes or algstrctcpy
CBifun_Term
Cbivar_function	Untyped internal class for triply-typed bivariate function
CBoolPair
CCommData
CCompPair
CCompPtrPair
CConstPairIterator
CContract_Term	An experession representing a contraction of a set of tensors contained in operands
Ccontraction	Class for execution distributed contraction of tensors
CCOO_Matrix	Serialized matrix in coordinate format, meaning three arrays of dimension nnz are stored, one of values, and two of row and column indices
CCSR_Matrix	Abstraction for a serialized sparse matrix stored in column-sparse-row (CSR) layout
Cctr
Cctr_2d_general
Cctr_replicate
Cctr_virt
CCubicModel	Cubic performance models, which given measurements, provides new model guess
Cdistribution
Cendomorphism	Untyped internal class for singly-typed single variable function (Endomorphism)
Cgrid_wrapper
Cint1
Cint2
CIntPair
Ciparam
CLinModel	Linear performance models, which given measurements, provides new model guess
Cmapping
Cmem_loc
Cmem_transfer
CModel
Coffload_arr	Offloaded array/buffer
Coffload_tsr	Offloaded and serialized tensor data
CPairIterator
Cscaling	Class for execution distributed scaling of a tensor
Cscl
Cscl_virt
Cseq_tsr_ctr
Cseq_tsr_scl
Cseq_tsr_spctr
Cseq_tsr_spsum
Cseq_tsr_sum
CShortPair
Cspctr
Cspctr_2d_general
Cspctr_pin_keys
Cspctr_replicate
Cspctr_virt
Cstrp_ctr
Cstrp_scl
Cstrp_sum
Cstrp_tsr
CSum_Term
Csummation	Class for execution distributed summation of tensors
Ctensor	Internal distributed tensor class
Ctensor_name_less	Comparison function for sets of tensor pointers This ensures the set iteration order is consistent across nodes
CTerm	Term is an abstract object representing some expression of tensors
Ctime_param
Ctopology
Ctspsum
Ctspsum_map
Ctspsum_permute
Ctspsum_pin_keys
Ctspsum_replicate	Performs replication along a dimension, generates 2.5D algs
Ctspsum_virt
Ctsum
Ctsum_replicate	Performs replication along a dimension, generates 2.5D algs
Ctsum_virt
CUnifun_Term
Cunivar_function	Untyped internal class for doubly-typed univariate function
CAmplitudes
Ccpath
Ccust_sp_type
Ccust_type
Cdpair
Cforce
Cgrp
Cindex_locator_
CIntegrals
Cmpath
Cparticle
Cpath
CtCTF_Idx_Tensor
CtCTF_World