Developer Reference for Intel® oneAPI Math Kernel Library for Fortran

ID 766686
Date 11/07/2023
Public

A newer version of this document is available.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

Document Table of Contents

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.