HLIBpro
1.2

Table of contents 
Matrixvector multiplication in ๐๐ซ๐จ๐ก๐๐๐ is provided in the form of a vector update:
Here, is either , or for a given matrix . The individual form of is specified by a value of type matop_t:
MATOP_NORM:
, MATOP_TRANS:
, MATOP_CONJ:
.Each matrix classes provides the method mul_vec
for real and cmul_vec
for complex valued factors (see TMatrix), which perform the corresponding operations:
Additionally, the function mul_vec
is available, which also handles the case of a distributed matrix (on distributed memory). To use it, the header file algebra/mul_vec.hh
has to be included.
After including algebra/mat_add.hh
into the corresponding source file, the function add
is available for matrix addition. It implements the matrix update
with matrices . Here, and are real valued. For the complex valued case, the corresponding function is called cadd:
Matrix addition supports multi threaded execution, hence the first argument of both functions defines the number of threads to use.
A crucial requirement for the matrix addition as well as for all matrix operations, is the compatibility of the corresponding index sets and cluster trees, i.e. if then also must hold and the cluster trees for and have to be equal for both matrices. Only the block cluster trees may differ, e.g. a different admissibility condition can be used for both matrices.
A special for of matrix addition is implemented in add_identity
(cadd_identity
), in which
is implemented:
Currently, this is only implemented if has dense diagonal blocks, e.g. which is th case for standard admissibility. Furthermore, since the operation only affects the diagonal part, it is an exact addition without truncation.
General matrix multiplication is provided by the module mat_mul
, e.g. you have to include