Developer Reference for Intel® oneAPI Math Kernel Library for C

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Date 12/16/2022
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Document Table of Contents x
Developer Reference for Intel® oneAPI Math Kernel Library - C
Developer Reference for Intel® oneAPI Math Kernel Library - C x
Getting Help and Support What's New Notational Conventions Overview OpenMP* Offload BLAS and Sparse BLAS Routines LAPACK Routines ScaLAPACK Routines Sparse Solver Routines Graph Routines Extended Eigensolver Routines Vector Mathematical Functions Statistical Functions Fourier Transform Functions PBLAS Routines Partial Differential Equations Support Nonlinear Optimization Problem Solvers Support Functions BLACS Routines Data Fitting Functions Appendix A: Linear Solvers Basics Appendix B: Routine and Function Arguments Appendix C: FFTW Interface to Intel® Math Kernel Library Appendix D: Code Examples Appendix E: Graph Basics Appendix F: oneMKL Functionality Bibliography Glossary Notices and Disclaimers
Overview x
Performance Enhancements Parallelism C Datatypes Specific to Intel MKL
OpenMP* Offload x
OpenMP* Offload for Intel® oneAPI Math Kernel Library
BLAS and Sparse BLAS Routines x
BLAS Routines Sparse BLAS Level 1 Routines Sparse BLAS Level 2 and Level 3 Routines Sparse QR Routines Compact BLAS and LAPACK Functions Inspector-executor Sparse BLAS Routines BLAS-like Extensions
BLAS Routines x
Naming Conventions for BLAS Routines C Interface Conventions for BLAS Routines Matrix Storage Schemes for BLAS Routines BLAS Level 1 Routines and Functions BLAS Level 2 Routines BLAS Level 3 Routines
BLAS Level 1 Routines and Functions x
cblas_?asum cblas_?axpy cblas_?copy cblas_?copy_batch cblas_?copy_batch_strided cblas_?dot cblas_?sdot cblas_?dotc cblas_?dotu cblas_?nrm2 cblas_?rot cblas_?rotg cblas_?rotm cblas_?rotmg cblas_?scal cblas_?swap cblas_i?amax cblas_i?amin cblas_?cabs1
BLAS Level 2 Routines x
cblas_?gbmv cblas_?gemv cblas_?ger cblas_?gerc cblas_?geru cblas_?hbmv cblas_?hemv cblas_?her cblas_?her2 cblas_?hpmv cblas_?hpr cblas_?hpr2 cblas_?sbmv cblas_?spmv cblas_?spr cblas_?spr2 cblas_?symv cblas_?syr cblas_?syr2 cblas_?tbmv cblas_?tbsv cblas_?tpmv cblas_?tpsv cblas_?trmv cblas_?trsv
BLAS Level 3 Routines x
cblas_?gemm cblas_?hemm cblas_?herk cblas_?her2k cblas_?symm cblas_?syrk cblas_?syr2k cblas_?trmm cblas_?trsm
Sparse BLAS Level 1 Routines x
Vector Arguments Naming Conventions for Sparse BLAS Routines Routines and Data Types BLAS Level 1 Routines That Can Work With Sparse Vectors cblas_?axpyi cblas_?doti cblas_?dotci cblas_?dotui cblas_?gthr cblas_?gthrz cblas_?roti cblas_?sctr
Sparse BLAS Level 2 and Level 3 Routines x
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.
Sparse BLAS Level 2 and Level 3 Routines. x
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 x
mkl_sparse_set_qr_hint mkl_sparse_?_qr mkl_sparse_qr_reorder mkl_sparse_?_qr_factorize mkl_sparse_?_qr_solve mkl_sparse_?_qr_qmult mkl_sparse_?_qr_rsolve
Compact BLAS and LAPACK Functions x
mkl_?gemm_compact mkl_?trsm_compact mkl_?potrf_compact mkl_?getrfnp_compact mkl_?geqrf_compact mkl_?getrinp_compact Numerical Limitations for Compact BLAS and Compact LAPACK Routines mkl_?get_size_compact mkl_get_format_compact mkl_?gepack_compact mkl_?geunpack_compact
Inspector-executor Sparse BLAS Routines x
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 in Inspector-Executor Sparse BLAS Routines Matrix Manipulation Routines Inspector-Executor Sparse BLAS Analysis Routines Inspector-Executor Sparse BLAS Execution Routines
Matrix Manipulation Routines x
mkl_sparse_?_create_csr mkl_sparse_?_create_csc mkl_sparse_?_create_coo mkl_sparse_?_create_bsr mkl_sparse_copy mkl_sparse_destroy mkl_sparse_convert_csr mkl_sparse_convert_bsr mkl_sparse_?_export_csr mkl_sparse_?_export_csc mkl_sparse_?_export_bsr mkl_sparse_?_set_value mkl_sparse_?_update_values mkl_sparse_order
Inspector-Executor Sparse BLAS Analysis Routines x
mkl_sparse_set_lu_smoother_hint mkl_sparse_set_mv_hint mkl_sparse_set_sv_hint mkl_sparse_set_mm_hint mkl_sparse_set_sm_hint mkl_sparse_set_dotmv_hint mkl_sparse_set_symgs_hint mkl_sparse_set_sorv_hint mkl_sparse_set_memory_hint mkl_sparse_optimize
Inspector-Executor Sparse BLAS Execution Routines x
mkl_sparse_?_lu_smoother mkl_sparse_?_mv mkl_sparse_?_trsv mkl_sparse_?_mm mkl_sparse_?_trsm mkl_sparse_?_add mkl_sparse_spmm mkl_sparse_?_spmmd mkl_sparse_sp2m mkl_sparse_?_sp2md mkl_sparse_sypr mkl_sparse_?_syprd mkl_sparse_?_symgs mkl_sparse_?_symgs_mv mkl_sparse_syrk mkl_sparse_?_syrkd mkl_sparse_?_dotmv mkl_sparse_?_sorv
BLAS-like Extensions x
cblas_?axpy_batch cblas_?axpy_batch_strided cblas_?axpby cblas_?gemmt cblas_?gemm3m cblas_?gemm_batch cblas_?gemm_batch_strided cblas_?gemm3m_batch cblas_?trsm_batch cblas_?trsm_batch_strided mkl_?imatcopy mkl_?imatcopy_batch mkl_?imatcopy_batch_strided mkl_?omatadd_batch_strided mkl_?omatcopy mkl_?omatcopy_batch mkl_?omatcopy_batch_strided mkl_?omatcopy2 mkl_?omatadd cblas_?gemm_pack_get_size, cblas_gemm_*_pack_get_size cblas_?gemm_pack cblas_gemm_*_pack cblas_?gemm_compute cblas_gemm_*_compute cblas_gemm_bf16bf16f32_compute cblas_?gemm_free cblas_gemm_bf16bf16f32 cblas_gemm_* cblas_?gemv_batch_strided cblas_?gemv_batch cblas_?dgmm_batch_strided cblas_?dgmm_batch mkl_jit_create_?gemm mkl_jit_get_?gemm_ptr mkl_jit_destroy
LAPACK Routines x
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 Least Squares and Eigenvalue Problem Routines LAPACK Auxiliary Routines LAPACK Utility Functions and Routines LAPACK Test Functions and Routines Additional LAPACK Routines (Included for Compatibility with Netlib LAPACK)
LAPACK Linear Equation Routines x
LAPACK Linear Equation Computational Routines LAPACK Linear Equation Driver Routines
LAPACK Linear Equation Computational Routines x
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
Matrix Factorization: LAPACK Computational Routines x
?getrf mkl_?getrfnp mkl_?getrfnpi ?getrf2 ?gbtrf ?gttrf ?dttrfb ?potrf ?potrf2 ?pstrf ?pftrf ?pptrf ?pbtrf ?pttrf ?sytrf ?sytrf_aa ?sytrf_rook ?sytrf_rk ?hetrf ?hetrf_aa ?hetrf_rook ?hetrf_rk ?sptrf ?hptrf mkl_?spffrt2, mkl_?spffrtx
Solving Systems of Linear Equations: LAPACK Computational Routines x
?getrs ?gbtrs ?gttrs ?dttrsb ?potrs ?pftrs ?pptrs ?pbtrs ?pttrs ?sytrs ?sytrs_aa ?sytrs_rook ?hetrs ?hetrs_aa ?hetrs_rook ?sytrs2 ?hetrs2 ?sytrs_3 ?hetrs_3 ?sptrs ?hptrs ?trtrs ?tptrs ?tbtrs
Estimating the Condition Number: LAPACK Computational Routines x
?gecon ?gbcon ?gtcon ?pocon ?ppcon ?pbcon ?ptcon ?sycon ?sycon_3 ?hecon ?hecon_3 ?spcon ?hpcon ?trcon ?tpcon ?tbcon
Refining the Solution and Estimating Its Error: LAPACK Computational Routines x
?gerfs ?gerfsx ?gbrfs ?gbrfsx ?gtrfs ?porfs ?porfsx ?pprfs ?pbrfs ?ptrfs ?syrfs ?syrfsx ?herfs ?herfsx ?sprfs ?hprfs ?trrfs ?tprfs ?tbrfs
Matrix Inversion: LAPACK Computational Routines x
?getri mkl_?getrinp ?potri ?pftri ?pptri ?sytri ?hetri ?sytri2 ?hetri2 ?sytri2x ?hetri2x ?sytri_3 ?hetri_3 ?sptri ?hptri ?trtri ?tftri ?tptri
Matrix Equilibration: LAPACK Computational Routines x
?geequ ?geequb ?gbequ ?gbequb ?poequ ?poequb ?ppequ ?pbequ ?syequb ?heequb
LAPACK Linear Equation Driver Routines x
?gesv ?gesvx ?gesvxx ?gbsv ?gbsvx ?gbsvxx ?gtsv ?gtsvx ?dtsvb ?posv ?posvx ?posvxx ?ppsv ?ppsvx ?pbsv ?pbsvx ?ptsv ?ptsvx ?sysv ?sysv_aa ?sysv_rook ?sysv_rk ?sysvx ?sysvxx ?hesv ?hesv_aa ?hesv_rk ?hesvx ?hesvxx ?spsv ?spsvx ?hpsv ?hpsvx
LAPACK Least Squares and Eigenvalue Problem Routines x
LAPACK Least Squares and Eigenvalue Problem Computational Routines LAPACK Least Squares and Eigenvalue Problem Driver Routines
LAPACK Least Squares and Eigenvalue Problem Computational Routines x
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
Orthogonal Factorizations: LAPACK Computational Routines x
?geqrf ?geqrfp ?geqrt ?gemqrt ?geqpf ?geqp3 ?orgqr ?ormqr ?ungqr ?unmqr ?gelqf ?orglq ?ormlq ?unglq ?unmlq ?geqlf ?orgql ?ungql ?ormql ?unmql ?gerqf ?orgrq ?ungrq ?ormrq ?unmrq ?tzrzf ?ormrz ?unmrz ?ggqrf ?ggrqf ?tpqrt ?tpmqrt
Singular Value Decomposition: LAPACK Computational Routines x
?gebrd ?gbbrd ?orgbr ?ormbr ?ungbr ?unmbr ?bdsqr ?bdsdc
Symmetric Eigenvalue Problems: LAPACK Computational Routines x
?sytrd ?orgtr ?ormtr ?hetrd ?ungtr ?unmtr ?sptrd ?opgtr ?opmtr ?hptrd ?upgtr ?upmtr ?sbtrd ?hbtrd ?sterf ?steqr ?stemr ?stedc ?stegr ?pteqr ?stebz ?stein ?disna
Generalized Symmetric-Definite Eigenvalue Problems: LAPACK Computational Routines x
?sygst ?hegst ?spgst ?hpgst ?sbgst ?hbgst ?pbstf
Nonsymmetric Eigenvalue Problems: LAPACK Computational Routines x
?gehrd ?orghr ?ormhr ?unghr ?unmhr ?gebal ?gebak ?hseqr ?hsein ?trevc ?trevc3 ?trsna ?trexc ?trsen ?trsyl
Generalized Nonsymmetric Eigenvalue Problems: LAPACK Computational Routines x
?gghrd ?ggbal ?ggbak ?gghd3 ?hgeqz ?tgevc ?tgexc ?tgsen ?tgsyl ?tgsna
Generalized Singular Value Decomposition: LAPACK Computational Routines x
?ggsvp ?ggsvp3 ?ggsvd3 ?tgsja
Cosine-Sine Decomposition: LAPACK Computational Routines x
?bbcsd ?orbdb/?unbdb
LAPACK Least Squares and Eigenvalue Problem Driver Routines x
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
Linear Least Squares (LLS) Problems: LAPACK Driver Routines x
?gels ?gelsy ?gelss ?gelsd
Generalized Linear Least Squares (LLS) Problems: LAPACK Driver Routines x
?gglse ?ggglm
Symmetric Eigenvalue Problems: LAPACK Driver Routines x
?syev ?heev ?syevd ?heevd ?syevx ?heevx ?syevr ?heevr ?spev ?hpev ?spevd ?hpevd ?spevx ?hpevx ?sbev ?hbev ?sbevd ?hbevd ?sbevx ?hbevx ?stev ?stevd ?stevx ?stevr
Nonsymmetric Eigenvalue Problems: LAPACK Driver Routines x
?gees ?geesx ?geev ?geevx
Singular Value Decomposition: LAPACK Driver Routines x
?gesvd ?gesdd ?gejsv ?gesvj ?ggsvd ?gesvdx ?bdsvdx
Cosine-Sine Decomposition: LAPACK Driver Routines x
?orcsd/?uncsd ?orcsd2by1/?uncsd2by1
Generalized Symmetric Definite Eigenvalue Problems: LAPACK Driver Routines x
?sygv ?hegv ?sygvd ?hegvd ?sygvx ?hegvx ?spgv ?hpgv ?spgvd ?hpgvd ?spgvx ?hpgvx ?sbgv ?hbgv ?sbgvd ?hbgvd ?sbgvx ?hbgvx
Generalized Nonsymmetric Eigenvalue Problems: LAPACK Driver Routines x
?gges ?ggesx ?gges3 ?ggev ?ggevx ?ggev3
LAPACK Auxiliary Routines x
?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 ?lasd0 ?lasd1 ?lasd2 ?lasd3 ?lasd4 ?lasd5 ?lasd6 ?lasd7 ?lasd8 ?lasd9 ?lasda ?lasdq ?lasdt ?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 x
ilaver ilaenv ?lamch
LAPACK Test Functions and Routines x
?lagge ?laghe ?lagsy ?latms
ScaLAPACK Routines x
Overview of ScaLAPACK Routines ScaLAPACK Array Descriptors Naming Conventions for ScaLAPACK Routines ScaLAPACK Computational Routines ScaLAPACK Driver Routines ScaLAPACK Auxiliary Routines ScaLAPACK Utility Functions and Routines ScaLAPACK Redistribution/Copy Routines
ScaLAPACK Computational Routines x
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
Matrix Factorization: ScaLAPACK Computational Routines x
p?getrf p?gbtrf p?dbtrf p?dttrf p?potrf p?pbtrf p?pttrf
Solving Systems of Linear Equations: ScaLAPACK Computational Routines x
p?getrs p?gbtrs p?dbtrs p?dttrs p?potrs p?pbtrs p?pttrs p?trtrs
Estimating the Condition Number: ScaLAPACK Computational Routines x
p?gecon p?pocon p?trcon
Refining the Solution and Estimating Its Error: ScaLAPACK Computational Routines x
p?gerfs p?porfs p?trrfs
Matrix Inversion: ScaLAPACK Computational Routines x
p?getri p?potri p?trtri
Matrix Equilibration: ScaLAPACK Computational Routines x
p?geequ p?poequ
Orthogonal Factorizations: ScaLAPACK Computational Routines x
p?geqrf p?geqpf p?orgqr p?ungqr p?ormqr p?unmqr p?gelqf p?orglq p?unglq p?ormlq p?unmlq p?geqlf p?orgql p?ungql p?ormql p?unmql p?gerqf p?orgrq p?ungrq p?ormr3 p?unmr3 p?ormrq p?unmrq p?tzrzf p?ormrz p?unmrz p?ggqrf p?ggrqf
Symmetric Eigenvalue Problems: ScaLAPACK Computational Routines x
p?syngst p?syntrd p?sytrd p?ormtr p?hengst p?hentrd p?hetrd p?unmtr p?stebz p?stedc p?stein
Nonsymmetric Eigenvalue Problems: ScaLAPACK Computational Routines x
p?gehrd p?ormhr p?unmhr p?lahqr p?trevc
Singular Value Decomposition: ScaLAPACK Driver Routines x
p?gebrd p?ormbr p?unmbr
Generalized Symmetric-Definite Eigenvalue Problems: ScaLAPACK Computational Routines x
p?sygst p?hegst
ScaLAPACK Driver Routines x
p?geevx p?gesv p?gesvx p?gbsv p?dbsv p?dtsv p?posv p?posvx p?pbsv p?ptsv p?gels p?syev p?syevd p?syevr p?syevx p?heev p?heevd p?heevr p?heevx p?gesvd p?sygvx p?hegvx
ScaLAPACK Auxiliary Routines x
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 x
p?labad p?lachkieee p?lamch p?lasnbt descinit numroc
ScaLAPACK Redistribution/Copy Routines x
p?gemr2d p?trmr2d
Sparse Solver Routines x
oneMKL PARDISO - Parallel Direct Sparse Solver Interface 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
oneMKL PARDISO - Parallel Direct Sparse Solver Interface x
pardiso pardisoinit pardiso_64 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 oneMKL PARDISO Parameters in Tabular Form pardiso iparm Parameter PARDISO_DATA_TYPE
Parallel Direct Sparse Solver for Clusters Interface x
cluster_sparse_solver cluster_sparse_solver_64 cluster_sparse_solver_get_csr_size cluster_sparse_solver_set_csr_ptrs cluster_sparse_solver_set_ptr cluster_sparse_solver_export cluster_sparse_solver iparm Parameter
Direct Sparse Solver (DSS) Interface Routines x
DSS Interface Description DSS Implementation Details DSS Routines
DSS Routines x
dss_create dss_define_structure dss_reorder dss_factor_real, dss_factor_complex dss_solve_real, dss_solve_complex dss_delete dss_statistics
Iterative Sparse Solvers based on Reverse Communication Interface (RCI ISS) x
CG Interface Description FGMRES Interface Description RCI ISS Routines RCI ISS Implementation Details
RCI ISS Routines x
dcg_init dcg_check dcg dcg_get dcgmrhs_init dcgmrhs_check dcgmrhs dcgmrhs_get dfgmres_init dfgmres_check dfgmres dfgmres_get
Preconditioners based on Incomplete LU Factorization Technique x
ILU0 and ILUT Preconditioners Interface Description dcsrilu0 dcsrilut
Sparse Matrix Checker Routines x
sparse_matrix_checker sparse_matrix_checker_init
Graph Routines x
Graph Functionality Graph Objects Graph API Glossary
Graph Functionality x
Creating/Destroying Graph Objects Importing/Exporting Data to or from the Graph Objects Graph Operations Auxiliary Routines Manipulating Graph Objects
Creating/Destroying Graph Objects x
mkl_graph_descriptor_create mkl_graph_descriptor_destroy mkl_graph_matrix_create mkl_graph_matrix_destroy mkl_graph_vector_create mkl_graph_vector_destroy
Importing/Exporting Data to or from the Graph Objects x
mkl_graph_matrix_set_csr mkl_graph_matrix_get_csr mkl_graph_matrix_set_csc mkl_graph_matrix_get_csc mkl_graph_vector_set_dense mkl_graph_vector_get_dense mkl_graph_vector_set_sparse mkl_graph_vector_get_sparse
Graph Operations x
mkl_graph_mxv mkl_graph_vxm mkl_graph_mxm mkl_graph_transpose
Auxiliary Routines x
mkl_graph_optimize_mxv mkl_graph_optimize_mxm mkl_graph_matrix_get_property mkl_graph_vector_get_property
Manipulating Graph Objects x
mkl_graph_descriptor_set_field
Extended Eigensolver Routines x
The FEAST Algorithm Extended Eigensolver Functionality Extended Eigensolver Interfaces for Eigenvalues within Interval Extended Eigensolver Interfaces for Extremal Eigenvalues/Singular Values
Extended Eigensolver Functionality x
Parallelism in Extended Eigensolver Routines Achieving Performance With Extended Eigensolver Routines
Extended Eigensolver Interfaces for Eigenvalues within Interval x
Extended Eigensolver Naming Conventions feastinit Extended Eigensolver Input Parameters Extended Eigensolver Output Details Extended Eigensolver RCI Routines Extended Eigensolver Predefined Interfaces
Extended Eigensolver RCI Routines x
Extended Eigensolver RCI Interface Description ?feast_srci/?feast_hrci
Extended Eigensolver Predefined Interfaces x
Matrix Storage ?feast_syev/?feast_heev ?feast_sygv/?feast_hegv ?feast_sbev/?feast_hbev ?feast_sbgv/?feast_hbgv ?feast_scsrev/?feast_hcsrev ?feast_scsrgv/?feast_hcsrgv
Extended Eigensolver Interfaces for Extremal Eigenvalues/Singular Values x
Extended Eigensolver Interfaces to find largest/smallest eigenvalues Extended Eigensolver Interfaces to find largest/smallest singular values mkl_sparse_ee_init Extended Eigensolver Input Parameters for Extremal Eigenvalue Problem
Extended Eigensolver Interfaces to find largest/smallest eigenvalues x
mkl_sparse_?_ev mkl_sparse_?_gv
Extended Eigensolver Interfaces to find largest/smallest singular values x
mkl_sparse_?_svd
Vector Mathematical Functions x
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
VM Naming Conventions x
VM Function Interfaces
VM Function Interfaces x
VM Mathematical Function Interfaces VM Pack Function Interfaces VM Unpack Function Interfaces VM Service Function Interfaces VM Input Parameters VM Output Parameters
VM Mathematical Functions x
Special Value Notations Arithmetic Functions Power and Root Functions Exponential and Logarithmic Functions Trigonometric Functions Hyperbolic Functions Special Functions Rounding Functions
Arithmetic Functions x
v?Add v?Sub v?Sqr v?Mul v?MulByConj v?Conj v?Abs v?Arg v?LinearFrac v?Fmod v?Remainder
Power and Root Functions x
v?Inv v?Div v?Sqrt v?InvSqrt v?Cbrt v?InvCbrt v?Pow2o3 v?Pow3o2 v?Pow v?Powx v?Powr v?Hypot
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Hyperbolic Functions x
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Special Functions x
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Rounding Functions x
v?Floor v?Ceil v?Trunc v?Round v?NearbyInt v?Rint v?Modf v?Frac
VM Pack/Unpack Functions x
v?Pack v?Unpack
VM Service Functions x
vmlSetMode vmlGetMode MKLFreeTls vmlSetErrStatus vmlGetErrStatus vmlClearErrStatus vmlSetErrorCallBack vmlGetErrorCallBack vmlClearErrorCallBack
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Random Number Generators Convolution and Correlation Summary Statistics
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Random Number Generators Conventions Basic Generators Error Reporting VS RNG Usage ModelIntel® oneMKL RNG Usage Model Service Routines Distribution Generators Advanced Service Routines
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Continuous Distributions Discrete Distributions
Continuous Distributions x
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Convolution and Correlation Task Constructors x
vslConvNewTask/vslCorrNewTask vslConvNewTask1D/vslCorrNewTask1D vslConvNewTaskX/vslCorrNewTaskX vslConvNewTaskX1D/vslCorrNewTaskX1D
Convolution and Correlation Task Editors x
vslConvSetMode/vslCorrSetMode vslConvSetInternalPrecision/vslCorrSetInternalPrecision vslConvSetStart/vslCorrSetStart vslConvSetDecimation/vslCorrSetDecimation
Task Execution Routines x
vslConvExec/vslCorrExec vslConvExec1D/vslCorrExec1D vslConvExecX/vslCorrExecX vslConvExecX1D/vslCorrExecX1D
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vslConvDeleteTask/vslCorrDeleteTask
Convolution and Correlation Task Copiers x
vslConvCopyTask/vslCorrCopyTask
Summary Statistics x
Summary Statistics Naming Conventions Summary Statistics Data Types Summary Statistics Parameters Summary Statistics Task Status and Error Reporting Summary Statistics Task Constructors Summary Statistics Task Editors Summary Statistics Task Computation Routines Summary Statistics Task Destructor Summary Statistics Usage Examples Summary Statistics Mathematical Notation and Definitions
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vslSSNewTask
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vslSSCompute
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vslSSDeleteTask
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FFT Functions Cluster FFT Functions
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Routines for the Spherical Solver x
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ipar dpar and spar Caveat on Parameter Modifications Parameters That Define Boundary Conditions
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xerbla pxerbla LAPACKE_xerbla
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mkl_set_exit_handler
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lsame lsamen
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second/dsecnd mkl_get_cpu_clocks mkl_get_cpu_frequency mkl_get_max_cpu_frequency mkl_get_clocks_frequency
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BLACS Point To Point Communication x
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blacs_pinfo blacs_setup blacs_get blacs_set blacs_gridinit blacs_gridmap
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blacs_freebuff blacs_gridexit blacs_abort blacs_exit
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blacs_gridinfo blacs_pnum blacs_pcoord
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blacs_barrier
Data Fitting Functions x
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df?NewTask1D
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df?EditPPSpline1D df?EditPtr dfiEditVal df?EditIdxPtr df?QueryPtr dfiQueryVal df?QueryIdxPtr
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df?Construct1D df?Interpolate1D/df?InterpolateEx1D df?Integrate1D/df?IntegrateEx1D df?SearchCells1D/df?SearchCellsEx1D df?InterpCallBack df?IntegrCallBack df?SearchCellsCallBack
Data Fitting Task Destructors x
dfDeleteTask
Appendix A: Linear Solvers Basics x
Sparse Linear Systems Sparse Matrix Storage Formats
Sparse Linear Systems x
Matrix Fundamentals Direct Method
Sparse Matrix Storage Formats x
DSS Symmetric Matrix Storage DSS Nonsymmetric Matrix Storage DSS Structurally Symmetric Matrix Storage DSS Distributed Symmetric Matrix Storage Sparse BLAS CSR Matrix Storage Format Sparse BLAS CSC Matrix Storage Format Sparse BLAS Coordinate Matrix Storage Format Sparse BLAS Diagonal Matrix Storage Format Sparse BLAS Skyline Matrix Storage Format Sparse BLAS BSR Matrix Storage Format
Appendix B: Routine and Function Arguments x
Vector Arguments in BLAS Vector Arguments in Vector Math Matrix Arguments
Appendix C: FFTW Interface to Intel® Math Kernel Library x
FFTW Notational Conventions FFTW2 Interface to Intel® oneAPI Math Kernel Library FFTW3 Interface to Intel® oneAPI Math Kernel Library
FFTW2 Interface to Intel® oneAPI Math Kernel Library x
Wrappers Reference Limitations of the FFTW2 Interface to Intel® oneAPI Math Kernel Library Installing FFTW2 Interface Wrappers MPI FFTW2 Wrappers
Wrappers Reference x
One-dimensional Complex-to-complex FFTs Multi-dimensional Complex-to-complex FFTs One-dimensional Real-to-half-complex/Half-complex-to-real FFTs Multi-dimensional Real-to-complex/Complex-to-real FFTs Multi-threaded FFTW FFTW Support Functions
Installing FFTW2 Interface Wrappers x
Creating the Wrapper Library Application Assembling Running FFTW2 Interface Wrapper Examples
MPI FFTW2 Wrappers x
MPI FFTW Wrappers Reference Creating MPI FFTW2 Wrapper Library Application Assembling with MPI FFTW Wrapper Library Running MPI FFTW2 Wrapper Examples
MPI FFTW Wrappers Reference x
Complex MPI FFTW Real MPI FFTW
FFTW3 Interface to Intel® oneAPI Math Kernel Library x
Using FFTW3 Wrappers Building Your Own FFTW3 Interface Wrapper Library Building an Application With FFTW3 Interface Wrappers Running FFTW3 Interface Wrapper Examples MPI FFTW3 Wrappers
MPI FFTW3 Wrappers x
Building Your Own Wrapper Library Building an Application Running Examples
Appendix D: Code Examples x
BLAS Code Examples Fourier Transform Functions Code Examples
Fourier Transform Functions Code Examples x
FFT Code Examples Examples for Cluster FFT Functions Auxiliary Data Transformations
FFT Code Examples x
Examples of Using OpenMP* Threading for FFT Computation
Appendix E: Graph Basics x
Graphs in Linear Algebra Graph Fundamentals
Appendix F: oneMKL Functionality x
BLAS Functionality Transposition Functionality LAPACK Functionality DFT Functionality Sparse BLAS Functionality Sparse Solvers Functionality Graphs Functionality Random Number Generators Functionality Vector Math Functionality Data Fitting Functionality Summary Statistics Functionality
Developer Reference for Intel® oneAPI Math Kernel Library - C

?upgtr

Generates the complex unitary matrix Q determined by ?hptrd.

Syntax

lapack_int LAPACKE_cupgtr (int matrix_layout, char uplo, lapack_int n, const lapack_complex_float* ap, const lapack_complex_float* tau, lapack_complex_float* q, lapack_int ldq);

lapack_int LAPACKE_zupgtr (int matrix_layout, char uplo, lapack_int n, const lapack_complex_double* ap, const lapack_complex_double* tau, lapack_complex_double* q, lapack_int ldq);

Include Files
  • mkl.h
Description

The routine explicitly generates the n-by-n unitary matrix Q formed by hptrd when reducing a packed complex Hermitian matrix A to tridiagonal form: A = Q*T*QH. Use this routine after a call to ?hptrd.

Input Parameters
matrix_layout

Specifies whether matrix storage layout is row major (LAPACK_ROW_MAJOR) or column major (LAPACK_COL_MAJOR).

uplo

Must be 'U' or 'L'. Use the same uplo as supplied to ?hptrd.

n

The order of the matrix Q (n≥ 0).

ap, tau

Arrays ap and tau, as returned by ?hptrd.

The dimension of ap must be at least max(1, n(n+1)/2).

The dimension of tau must be at least max(1, n-1).

ldq

The leading dimension of the output array q;

at least max(1, n).

Output Parameters
q

Array, size (size max(1, ldq*n)) .

Contains the computed matrix Q.

Return Values

This function returns a value info.

If info=0, the execution is successful.

If info = -i, the i-th parameter had an illegal value.

Application Notes

The computed matrix Q differs from an exactly orthogonal matrix by a matrix E such that ||E||2 = O(ε), where ε is the machine precision.

The approximate number of floating-point operations is (16/3)n3.

The real counterpart of this routine is opgtr.

Parent topic: Symmetric Eigenvalue Problems: LAPACK Computational Routines
Level Two Title