Developer Guide for Intel® oneAPI Math Kernel Library for Windows*

Developer Guide

Contents

Functions Threaded with Intel® Threading Building Blocks

In this section,
?
 stands for a precision prefix or suffix of the routine name and may have the value of
s, d, c
, or
z
.
The following
Intel® oneAPI Math Kernel Library
 function domains are threaded with Intel® Threading Building Blocks (Intel® TBB):
  • LAPACK.
    For a list of threaded routines, see LAPACK Routines.
  • Entire Level3 BLAS.
  • Fast Poisson, Laplace, and Helmholtz Solver (Poisson Library).
  • All Vector Mathematics functions (except service functions).
  • Intel® oneAPI Math Kernel Library
     PARDISO, a direct sparse solver based on Parallel Direct Sparse Solver (PARDISO*).
    For details, see
    oneMKL
     PARDISO Steps    .
  • Sparse BLAS.
    For a list of threaded routines, see Sparse BLAS Routines.
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.
Notice revision #20201201

LAPACK Routines

The following LAPACK routines are threaded with Intel TBB:
?geqrf
,
?gelqf
,
?getrf
,
?potrf
,
?unmqr*
,
?ormqr*
,
?unmrq*
,
?ormrq*
,
?unmlq*
,
?ormlq*
,
?unmql*
,
?ormql*
,
?sytrd
,
?hetrd
,
?syev
,
?heev
, and
?latrd
.
A number of other LAPACK routines, which are based on threaded LAPACK or BLAS routines, make effective use of Intel TBB threading:
?getrs
,
?gesv
,
?potrs
,
?bdsqr
, and
?gels
.

oneMKL
 PARDISO Steps

Intel® oneAPI Math Kernel Library
 PARDISO is threaded with Intel TBB in the reordering and factorization steps. However, routines performing the solving step are still called sequentially when using Intel TBB.

Sparse BLAS Routines

The Sparse BLAS inspector-executor application programming interface routines
mkl_sparse_?_mv
 are threaded with Intel TBB for the general compressed sparse row (CSR) and block sparse row (BSR) formats.
The following Sparse BLAS inspector-executor application programming routines are threaded with Intel TBB:
  • mkl_sparse_?_mv
     using the general compressed sparse row (CSR) and block sparse row (BSR) matrix formats.
  • mkl_sparse_?_mm
     using the general CSR sparse matrix format and both row and column major storage formats for the dense matrix.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.