Developer Reference for Intel® Math Kernel Library - C
Submitted May 23, 2019
- Getting Help and Support
- What's New
- Notational Conventions
- Overview
- BLAS and Sparse BLAS Routines
- BLAS Routines
- Sparse BLAS Level 1 Routines
- Sparse BLAS Level 2 and Level 3 Routines
- Naming Conventions in Sparse BLAS Level 2 and Level 3
- Sparse Matrix Storage Formats for Sparse BLAS Routines
- Routines and Supported Operations
- Interface Consideration
- Sparse BLAS Level 2 and Level 3 Routines.
- mkl_?csrgemv
- mkl_?bsrgemv
- mkl_?coogemv
- mkl_?diagemv
- mkl_?csrsymv
- mkl_?bsrsymv
- mkl_?coosymv
- mkl_?diasymv
- mkl_?csrtrsv
- mkl_?bsrtrsv
- mkl_?cootrsv
- mkl_?diatrsv
- mkl_cspblas_?csrgemv
- mkl_cspblas_?bsrgemv
- mkl_cspblas_?coogemv
- mkl_cspblas_?csrsymv
- mkl_cspblas_?bsrsymv
- mkl_cspblas_?coosymv
- mkl_cspblas_?csrtrsv
- mkl_cspblas_?bsrtrsv
- mkl_cspblas_?cootrsv
- mkl_?csrmv
- mkl_?bsrmv
- mkl_?cscmv
- mkl_?coomv
- mkl_?csrsv
- mkl_?bsrsv
- mkl_?cscsv
- mkl_?coosv
- mkl_?csrmm
- mkl_?bsrmm
- mkl_?cscmm
- mkl_?coomm
- mkl_?csrsm
- mkl_?cscsm
- mkl_?coosm
- mkl_?bsrsm
- mkl_?diamv
- mkl_?skymv
- mkl_?diasv
- mkl_?skysv
- mkl_?diamm
- mkl_?skymm
- mkl_?diasm
- mkl_?skysm
- mkl_?dnscsr
- mkl_?csrcoo
- mkl_?csrbsr
- mkl_?csrcsc
- mkl_?csrdia
- mkl_?csrsky
- mkl_?csradd
- mkl_?csrmultcsr
- mkl_?csrmultd
- Sparse QR Routines
- BLAS and LAPACK Compact Routines
- Inspector-executor Sparse BLAS Routines
- Naming conventions in Inspector-executor Sparse BLAS Routines
- Sparse Matrix Storage Formats for Inspector-executor Sparse BLAS Routines
- Supported Inspector-executor Sparse BLAS Operations
- Two-stage Algorithm for Inspector-executor Sparse BLAS routines
- Matrix Manipulation Routines
- Inspector-executor Sparse BLAS Analysis Routines
- Inspector-Executor Sparse BLAS Execution Routines
- BLAS-like Extensions
- cblas_?axpby
- cblas_?gemmt
- cblas_?gemm3m
- cblas_?gemm_batch
- cblas_?gemm3m_batch
- mkl_?imatcopy
- mkl_?omatcopy
- mkl_?omatcopy2
- mkl_?omatadd
- cblas_?gemm_pack_get_size, cblas_gemm_*_pack_get_size
- cblas_?gemm_alloc
- cblas_?gemm_pack
- cblas_gemm_*_pack
- cblas_?gemm_compute
- cblas_gemm_*_compute
- cblas_?gemm_free
- cblas_gemm_*
- mkl_jit_create_?gemm
- mkl_jit_get_?gemm_ptr
- mkl_jit_destroy
- LAPACK Routines
- Choosing a LAPACK Routine
- C Interface Conventions for LAPACK Routines
- Matrix Layout for LAPACK Routines
- Matrix Storage Schemes for LAPACK Routines
- Mathematical Notation for LAPACK Routines
- Error Analysis
- LAPACK Linear Equation Routines
- LAPACK Linear Equation Computational Routines
- Matrix Factorization: LAPACK Computational Routines
- Solving Systems of Linear Equations: LAPACK Computational Routines
- Estimating the Condition Number: LAPACK Computational Routines
- Refining the Solution and Estimating Its Error: LAPACK Computational Routines
- Matrix Inversion: LAPACK Computational Routines
- Matrix Equilibration: LAPACK Computational Routines
- LAPACK Linear Equation Driver Routines
- LAPACK Linear Equation Computational Routines
- LAPACK Least Squares and Eigenvalue Problem Routines
- LAPACK Least Squares and Eigenvalue Problem Computational Routines
- Orthogonal Factorizations: LAPACK Computational Routines
- Singular Value Decomposition: LAPACK Computational Routines
- Symmetric Eigenvalue Problems: LAPACK Computational Routines
- Generalized Symmetric-Definite Eigenvalue Problems: LAPACK Computational Routines
- Nonsymmetric Eigenvalue Problems: LAPACK Computational Routines
- Generalized Nonsymmetric Eigenvalue Problems: LAPACK Computational Routines
- Generalized Singular Value Decomposition: LAPACK Computational Routines
- Cosine-Sine Decomposition: LAPACK Computational Routines
- LAPACK Least Squares and Eigenvalue Problem Driver Routines
- Linear Least Squares (LLS) Problems: LAPACK Driver Routines
- Generalized Linear Least Squares (LLS) Problems: LAPACK Driver Routines
- Symmetric Eigenvalue Problems: LAPACK Driver Routines
- Nonsymmetric Eigenvalue Problems: LAPACK Driver Routines
- Singular Value Decomposition: LAPACK Driver Routines
- Cosine-Sine Decomposition: LAPACK Driver Routines
- Generalized Symmetric Definite Eigenvalue Problems: LAPACK Driver Routines
- Generalized Nonsymmetric Eigenvalue Problems: LAPACK Driver Routines
- LAPACK Least Squares and Eigenvalue Problem Computational Routines
- LAPACK Auxiliary Routines
- ?lacgv
- ?lacrm
- ?syconv
- ?syr
- i?max1
- ?sum1
- ?gelq2
- ?geqr2
- ?geqrt2
- ?geqrt3
- ?getf2
- ?lacn2
- ?lacpy
- ?lakf2
- ?lange
- ?lansy
- ?lanhe
- ?lantr
- LAPACKE_set_nancheck
- LAPACKE_get_nancheck
- ?lapmr
- ?lapmt
- ?lapy2
- ?lapy3
- ?laran
- ?larfb
- ?larfg
- ?larft
- ?larfx
- ?large
- ?larnd
- ?larnv
- ?laror
- ?larot
- ?lartgp
- ?lartgs
- ?lascl
- ?laset
- ?lasrt
- ?laswp
- ?latm1
- ?latm2
- ?latm3
- ?latm5
- ?latm6
- ?latme
- ?latmr
- ?lauum
- ?syswapr
- ?heswapr
- ?sfrk
- ?hfrk
- ?tfsm
- ?tfttp
- ?tfttr
- ?tpqrt2
- ?tprfb
- ?tpttf
- ?tpttr
- ?trttf
- ?trttp
- ?lacp2
- ?larcm
- mkl_?tppack
- mkl_?tpunpack
- LAPACK Utility Functions and Routines
- LAPACK Test Functions and Routines
- Additional LAPACK Routines (Included for Compatibility with Netlib LAPACK)
- Deep Neural Network Functions
- Enumerated Types
- Handling Array Layouts
- Handling Attributes of DNN Operations
- DNN Operations
- dnnConvolutionCreate, dnnGroupsConvolutionCreate
- dnnInnerProductCreate
- dnnReLUCreate
- dnnLRNCreate
- dnnPoolingCreate
- dnnBatchNormalizationCreate
- dnnBatchNormalizationCreate_v2
- dnnSplitCreate
- dnnConcatCreate
- dnnSumCreate
- dnnScaleCreate
- dnnConversionCreate
- dnnExecute
- dnnConversionExecute
- dnnDelete
- dnnAllocateBuffer
- dnnReleaseBuffer
- ScaLAPACK Routines
- Overview of ScaLAPACK Routines
- ScaLAPACK Array Descriptors
- Naming Conventions for ScaLAPACK Routines
- ScaLAPACK Computational Routines
- Systems of Linear Equations: ScaLAPACK Computational Routines
- Matrix Factorization: ScaLAPACK Computational Routines
- Solving Systems of Linear Equations: ScaLAPACK Computational Routines
- Estimating the Condition Number: ScaLAPACK Computational Routines
- Refining the Solution and Estimating Its Error: ScaLAPACK Computational Routines
- Matrix Inversion: ScaLAPACK Computational Routines
- Matrix Equilibration: ScaLAPACK Computational Routines
- Orthogonal Factorizations: ScaLAPACK Computational Routines
- Symmetric Eigenvalue Problems: ScaLAPACK Computational Routines
- Nonsymmetric Eigenvalue Problems: ScaLAPACK Computational Routines
- Singular Value Decomposition: ScaLAPACK Driver Routines
- Generalized Symmetric-Definite Eigenvalue Problems: ScaLAPACK Computational Routines
- ScaLAPACK Driver Routines
- ScaLAPACK Auxiliary Routines
- p?lacgv
- p?max1
- pilaver
- pmpcol
- pmpim2
- ?combamax1
- p?sum1
- p?dbtrsv
- p?dttrsv
- p?gebal
- p?gebd2
- p?gehd2
- p?gelq2
- p?geql2
- p?geqr2
- p?gerq2
- p?getf2
- p?labrd
- p?lacon
- p?laconsb
- p?lacp2
- p?lacp3
- p?lacpy
- p?laevswp
- p?lahrd
- p?laiect
- p?lamve
- p?lange
- p?lanhs
- p?lansy, p?lanhe
- p?lantr
- p?lapiv
- p?lapv2
- p?laqge
- p?laqr0
- p?laqr1
- p?laqr2
- p?laqr3
- p?laqr5
- p?laqsy
- p?lared1d
- p?lared2d
- p?larf
- p?larfb
- p?larfc
- p?larfg
- p?larft
- p?larz
- p?larzb
- p?larzc
- p?larzt
- p?lascl
- p?lase2
- p?laset
- p?lasmsub
- p?lasrt
- p?lassq
- p?laswp
- p?latra
- p?latrd
- p?latrs
- p?latrz
- p?lauu2
- p?lauum
- p?lawil
- p?org2l/p?ung2l
- p?org2r/p?ung2r
- p?orgl2/p?ungl2
- p?orgr2/p?ungr2
- p?orm2l/p?unm2l
- p?orm2r/p?unm2r
- p?orml2/p?unml2
- p?ormr2/p?unmr2
- p?pbtrsv
- p?pttrsv
- p?potf2
- p?rot
- p?rscl
- p?sygs2/p?hegs2
- p?sytd2/p?hetd2
- p?trord
- p?trsen
- p?trti2
- ?lahqr2
- ?lamsh
- ?lapst
- ?laqr6
- ?lar1va
- ?laref
- ?larrb2
- ?larrd2
- ?larre2
- ?larre2a
- ?larrf2
- ?larrv2
- ?lasorte
- ?lasrt2
- ?stegr2
- ?stegr2a
- ?stegr2b
- ?stein2
- ?dbtf2
- ?dbtrf
- ?dttrf
- ?dttrsv
- ?pttrsv
- ?steqr2
- ?trmvt
- pilaenv
- pilaenvx
- pjlaenv
- Additional ScaLAPACK Routines
- ScaLAPACK Utility Functions and Routines
- ScaLAPACK Redistribution/Copy Routines
- Sparse Solver Routines
- Intel MKL PARDISO - Parallel Direct Sparse Solver Interface
- pardiso
- pardisoinit
- pardiso_64
- pardiso_getenv, pardiso_setenv
- mkl_pardiso_pivot
- pardiso_getdiag
- pardiso_export
- pardiso_handle_store
- pardiso_handle_restore
- pardiso_handle_delete
- pardiso_handle_store_64
- pardiso_handle_restore_64
- pardiso_handle_delete_64
- Intel MKL PARDISO Parameters in Tabular Form
- pardiso iparm Parameter
- PARDISO_DATA_TYPE
- Parallel Direct Sparse Solver for Clusters Interface
- Direct Sparse Solver (DSS) Interface Routines
- Iterative Sparse Solvers based on Reverse Communication Interface (RCI ISS)
- Preconditioners based on Incomplete LU Factorization Technique
- Sparse Matrix Checker Routines
- Intel MKL PARDISO - Parallel Direct Sparse Solver Interface
- Extended Eigensolver Routines
- The FEAST Algorithm
- Extended Eigensolver Functionality
- Extended Eigensolver Interfaces for Eigenvalues within Interval
- Extended Eigensolver Interfaces for Extremal Eigenvalues/Singular Values
- Vector Mathematical Functions
- VM Data Types, Accuracy Modes, and Performance Tips
- VM Naming Conventions
- Vector Indexing Methods
- VM Error Diagnostics
- VM Mathematical Functions
- VM Pack/Unpack Functions
- VM Service Functions
- Miscellaneous VM Functions
- Statistical Functions
- Random Number Generators
- Convolution and Correlation
- Convolution and Correlation Naming Conventions
- Convolution and Correlation Data Types
- Convolution and Correlation Parameters
- Convolution and Correlation Task Status and Error Reporting
- Convolution and Correlation Task Constructors
- Convolution and Correlation Task Editors
- Task Execution Routines
- Convolution and Correlation Task Destructors
- Convolution and Correlation Task Copiers
- Convolution and Correlation Usage Examples
- Convolution and Correlation Mathematical Notation and Definitions
- Convolution and Correlation Data Allocation
- Summary Statistics