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