Naming Conventions in Inspector-Executor Sparse BLAS Routines

Developer Reference for Intel® oneAPI Math Kernel Library for C

Download PDF

ID 766684

Date 12/16/2022

Version

Public

A newer version of this document is available. Customers should click here to go to the newest version.

Visible to Intel only — GUID: GUID-D5DA1100-EB05-44F5-AA99-96F3458BB112

View Details

Naming Conventions in Inspector-Executor Sparse BLAS Routines

The Inspector-Executor Sparse BLAS API routine names use the following convention:

mkl_sparse_[<character>_]<operation>[_<format>]

The <character> field indicates the data type:

s: real, single precision
c: complex, single precision
d: real, double precision
z: complex, double precision

The data type is included in the name only if the function accepts dense matrix or scalar floating point parameters.

The <operation> field indicates the type of operation:

create: create matrix handle
copy: create a copy of matrix handle
convert: convert matrix between sparse formats
export: export matrix from internal representation to CSR or BSR format
destroy: frees memory allocated for matrix handle
set_<op>_hint: provide information about number of upcoming compute operations and operation type for optimization purposes, where <op> is mv, sv, mm, sm, dotmv, symgs, or memory
optimize: analyze the matrix using hints and store optimization information in matrix handle
mv: compute sparse matrix-vector product
mm: compute sparse matrix by dense matrix product (batch mv)
set_value: change a value in a matrix
spmm/spmmd: compute sparse matrix by sparse matrix product and store the result as a sparse/dense matrix
trsv: solve a triangular system
trsm: solve a triangular system with multiple right-hand sides
add: compute sum of two sparse matrices
symgs: compute a symmetric Gauss-Zeidel preconditioner
symgs_mv: compute a symmetric Gauss-Zeidel preconditioner with a final matrix-vector multiplication
sorv: computes forward, backward sweeps or symmetric successive over-relaxation preconditioner
sypr: compute the symmetric or Hermitian product of sparse matrices and store the result as a sparse matrix
syprd: compute the symmetric or Hermitian product of sparse and dense matrices and store the result as a dense matrix
syrk: compute the product of sparse matrix with its transposed matrix and store the result as a sparse matrix
syrkd: compute the product of sparse matrix with its transposed matrix and store the result as a dense matrix
order: perform ordering of column indexes of the matrix in CSR format
dotmv: compute a sparse matrix-vector product with dot product

The <format> field indicates the sparse matrix storage format:

coo: coordinate format
bsr: block sparse row format plus variations. Fill out either rows_start and rows_end (for 4-arrays representation) or rowIndex array (for 3-array BSR/CSR).
csr: compressed sparse row format plus variations. Fill out either rows_start and rows_end (for 4-arrays representation) or rowIndex array (for 3-array BSR/CSR).
csc: compressed sparse column format plus variations. Fill out either cols_start and cols_end (for 4-arrays representation) or colIndex array (for 3 array CSC).

The format is included in the function name only if the function parameters include an explicit sparse matrix in one of the conventional sparse matrix formats.

Parent topic: Inspector-executor Sparse BLAS Routines

Select Your Language

Using Intel.com Search

Quick Links

Recent Searches

Advanced Search

Only search in

Developer Reference for Intel® oneAPI Math Kernel Library for C

Naming Conventions in Inspector-Executor Sparse BLAS Routines