Developer Guide

Developer Guide for Intel® oneAPI Math Kernel Library Windows*

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Date 3/22/2024
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Document Table of Contents
Document Table of Contents x
Developer Guide for Intel® oneAPI Math Kernel Library for Windows*
Developer Guide for Intel® oneAPI Math Kernel Library for Windows* x
Getting Help and Support What's New Notational Conventions Related Information Getting Started Structure of the Intel® oneAPI Math Kernel Library Linking Your Application with the Intel® oneAPI Math Kernel Library Managing Performance and Memory Language-specific Usage Options Obtaining Numerically Reproducible Results Coding Tips Managing Output Working with the Intel® oneAPI Math Kernel Library Cluster Software Managing Behavior of the Intel® oneAPI Math Kernel Library with Environment Variables Programming with Intel® Math Kernel Library in Integrated Development Environments (IDE) Intel® oneAPI Math Kernel Library Benchmarks Appendix A: Intel® oneAPI Math Kernel Library Language Interfaces Support Appendix B: Support for Third-Party Interfaces Appendix C: Directory Structure in Detail Notices and Disclaimers
Getting Started x
Shared Library Versioning CMake Config for oneMKL Checking Your Installation Setting Environment Variables Compiler Support Using Code Examples What You Need to Know Before You Begin Using the Intel® oneAPI Math Kernel Library
Structure of the Intel® oneAPI Math Kernel Library x
Architecture Support High-Level Directory Structure Layered Model Concept
Linking Your Application with the Intel® oneAPI Math Kernel Library x
Linking Quick Start Linking Examples Linking in Detail Building Custom Dynamic-link Libraries Building a Universal Windows Driver
Linking Quick Start x
Using the /Qmkl Compiler Option Using the /Qmkl-ilp64 Compiler Option Automatically Linking a Project in the Visual Studio* Integrated Development Environment with Intel® oneAPI Math Kernel Library Using the Single Dynamic Library Selecting Libraries to Link with Using the Link-line Advisor Using the Command-Line Link Tool
Automatically Linking a Project in the Visual Studio* Integrated Development Environment with Intel® oneAPI Math Kernel Library x
Automatically Linking Your Microsoft Visual C/C++* Project with oneMKL Automatically Linking Your Intel® Visual Fortran Project with oneMKL
Linking Examples x
Linking on IA-32 Architecture Systems Linking on Intel(R) 64 Architecture Systems
Linking in Detail x
Dynamically Selecting the Interface and Threading Layer Linking with Interface Libraries Linking with Threading Libraries Linking with Computational Libraries Linking with Compiler Run-time Libraries Linking with System Libraries
Linking with Interface Libraries x
Using the ILP64 Interface vs. LP64 Interface Linking with Fortran 95 Interface Libraries
Building Custom Dynamic-link Libraries x
Using the Custom Dynamic-link Library Builder in the Command-line Mode Composing a List of Functions Specifying Function Names Building a Custom Dynamic-link Library in the Visual Studio* Development System Distributing Your Custom Dynamic-link Library
Managing Performance and Memory x
Improving Performance with Threading Improving Performance for Small Size Problems Other Tips and Techniques to Improve Performance Using Memory Functions
Improving Performance with Threading x
OpenMP* Threaded Functions and Problems Functions Threaded with Intel® Threading Building Blocks Avoiding Conflicts in the Execution Environment Techniques to Set the Number of Threads Setting the Number of Threads Using an OpenMP* Environment Variable Changing the Number of OpenMP* Threads at Run Time Using Additional Threading Control Calling oneMKL Functions from Multi-threaded Applications Using Intel® Hyper-Threading Technology Managing Multi-core Performance Managing Performance with Heterogeneous Cores
Using Additional Threading Control x
oneMKL-specific Environment Variables for OpenMP Threading Control MKL_DYNAMIC MKL_DOMAIN_NUM_THREADS MKL_NUM_STRIPES Setting the Environment Variables for Threading Control
Improving Performance for Small Size Problems x
Using MKL_DIRECT_CALL in C Applications Using MKL_DIRECT_CALL in Fortran Applications Limitations of the Direct Call
Other Tips and Techniques to Improve Performance x
Coding Techniques Improving oneMKL Performance on Specific Processors Operating on Denormals
Using Memory Functions x
Avoiding Memory Leaks in oneMKL Redefining Memory Functions
Language-specific Usage Options x
Using Language-Specific Interfaces with Intel® oneAPI Math Kernel Library Mixed-language Programming with the Intel Math Kernel Library
Using Language-Specific Interfaces with Intel® oneAPI Math Kernel Library x
Interface Libraries and Modules Fortran 95 Interfaces to LAPACK and BLAS Compiler-dependent Functions and Fortran 90 Modules
Mixed-language Programming with the Intel Math Kernel Library x
Calling LAPACK, BLAS, and CBLAS Routines from C/C++ Language Environments Using Complex Types in C/C++ Calling BLAS Functions That Return the Complex Values in C/C++ Code
Obtaining Numerically Reproducible Results x
Getting Started with Conditional Numerical Reproducibility Specifying Code Branches Reproducibility Conditions Setting the Environment Variable for Conditional Numerical Reproducibility Code Examples
Coding Tips x
Example of Data Alignment Using Predefined Preprocessor Symbols for Intel® MKL Version-Dependent Compilation
Managing Output x
Using oneMKL Verbose Mode
Using oneMKL Verbose Mode x
Version Information Line Call Description Line
Working with the Intel® oneAPI Math Kernel Library Cluster Software x
Message-Passing Interface Support Linking with oneMKL Cluster Software Determining the Number of OpenMP* Threads Using DLLs Setting Environment Variables on a Cluster Interaction with the Message-passing Interface Using a Custom Message-Passing Interface Examples of Linking for Clusters
Examples of Linking for Clusters x
Examples for Linking a C Application Examples for Linking a Fortran Application
Managing Behavior of the Intel® oneAPI Math Kernel Library with Environment Variables x
Managing Behavior of Function Domains with Environment Variables Instruction Set–Specific Dispatching on Intel® Architectures
Managing Behavior of Function Domains with Environment Variables x
Setting the Default Mode of Vector Math with an Environment Variable Managing Performance of the Cluster Fourier Transform Functions Managing Invalid Input Checking in LAPACKE Functions
Programming with Intel® Math Kernel Library in Integrated Development Environments (IDE) x
Configuring Your Integrated Development Environment to Link with Intel® oneAPI Math Kernel Library Getting Assistance for Programming in the Microsoft Visual Studio* IDE
Configuring Your Integrated Development Environment to Link with Intel® oneAPI Math Kernel Library x
Configuring the Microsoft Visual C/C++* Development System to Link with Intel® MKL Configuring Intel® Visual Fortran to Link with oneMKL
Getting Assistance for Programming in the Microsoft Visual Studio* IDE x
Using Context-Sensitive Help Using the IntelliSense* Capability
Intel® oneAPI Math Kernel Library Benchmarks x
Intel Optimized LINPACK Benchmark for Windows* Intel® Distribution for LINPACK* Benchmark and Intel® Optimized HPL-AI* Benchmark
Intel Optimized LINPACK Benchmark for Windows* x
Contents of the Intel® Optimized LINPACK Benchmark Running the Software Known Limitations of the Intel® Optimized LINPACK Benchmark
Intel® Distribution for LINPACK* Benchmark and Intel® Optimized HPL-AI* Benchmark x
Overview of the Intel® Distribution for LINPACK* Benchmark Overview of the Intel® Optimized HPL-AI* Benchmark Contents of the Intel® Distribution for LINPACK* Benchmark and the Intel® Optimized HPL-AI* Benchmark Building the Intel® Distribution for LINPACK* Benchmark and the Intel® Optimized HPL-AI* Benchmark for a Customized MPI Implementation Building the Netlib HPL from Source Code Configuring Parameters Ease-of-use Command-line Parameters Running the Intel® Distribution for LINPACK* Benchmark and the Intel® Optimized HPL-AI* Benchmark Heterogeneous Support in the Intel® Distribution for LINPACK* Benchmark Environment Variables Improving Performance of Your Cluster
Appendix A: Intel® oneAPI Math Kernel Library Language Interfaces Support x
Language Interfaces Support, by Function Domain Include Files
Appendix B: Support for Third-Party Interfaces x
FFTW Interface Support
Appendix C: Directory Structure in Detail x
Detailed Structure of the IA-32 Architecture Directories Detailed Structure of the Intel® 64 Architecture Directories
Detailed Structure of the IA-32 Architecture Directories x
Static Libraries in the lib32 Directory Dynamic Libraries in the lib32 Directory Contents of the bin32 Directory
Detailed Structure of the Intel® 64 Architecture Directories x
Static Libraries in the lib Directory Dynamic Libraries in the lib Directory Contents of the bin Directory
Developer Guide for Intel® oneAPI Math Kernel Library for Windows*

Static Libraries in the lib Directory

Some of the libraries in this directory are optional. However, some optional libraries are installed by default, while the rest are not. To get those libraries that are not installed by default, explicitly select the specified optional component during installation.

File

Contents

Optional Component

Name

Installed by Default

SYCL API Layer

      

mkl_sycl.lib

SYCL library for the Intel DPC++ compilers. Required if SYCL-specific functionality is needed.

This library includes BLAS, LAPACK, DFT, Data Fitting, Vector Math, Sparse BLAS, RNG and Summary Statistic domains.

   

mkl_sycld.lib

SYCL library with debug runtime (/MDd) for the Intel DPC++ compilers. Required if SYCL-specific functionality with debug runtime (/MDd) is needed.

This library includes BLAS, LAPACK, DFT, Data Fitting, Vector Math, Sparse BLAS, RNG and Summary Statistic domains.

   

Interface Layer

      

mkl_intel_lp64.lib

LP64 interface library for the Intel compilers.

All Intel® oneAPI Math Kernel Library (oneMKL) function domains support LP64 programming. Read more about LP64 in Using the ILP64 Interface vs. LP64 Interface.

   

mkl_intel_ilp64.lib

ILP64 interface library for the Intel compilers.

All oneMKL function domains support ILP64 programming with some limitations for FFT. Read more about ILP64 and limitations in Using the ILP64 Interface vs. LP64 Interface.

   

mkl_blas95_lp64.lib

Fortran 95 interface library for BLAS. Supports the Intel® Fortran compiler and LP64 interface

Fortran 95 interfaces for BLAS and LAPACK

Yes

mkl_blas95_ilp64.lib

Fortran 95 interface library for BLAS. Supports the Intel® Fortran compiler and ILP64 interface

Fortran 95 interfaces for BLAS and LAPACK

Yes

mkl_lapack95_lp64.lib

Fortran 95 interface library for LAPACK. Supports the Intel® Fortran compiler and LP64 interface

Fortran 95 interfaces for BLAS and LAPACK

Yes

mkl_lapack95_ilp64.lib

Fortran 95 interface library for LAPACK. Supports the Intel® Fortran compiler and ILP64 interface

Fortran 95 interfaces for BLAS and LAPACK

Yes

Threading Layer

      

mkl_intel_thread.lib

OpenMP threading library for the Intel compilers.

All oneMKL function domains support Intel OpenMP threading.

   

mkl_tbb_thread.lib

Intel TBB threading library for the Intel compilers.

All oneMKL function domains support Intel TBB threading.

Intel TBB threading support

Yes

mkl_tbb_threadd.lib

Intel® Threading Building Blocks (Intel® TBB) threading library for the Intel compilers compatible with mkl_sycld.lib.

Intel TBB threading support

Yes

mkl_pgi_thread.lib (DEPRECATED)

OpenMP threading library for the PGI* compiler.

All oneMKL function domains except cluster domains (CDFT, CPARDISO, HPCG, BLACS) support PGI threading.

PGI* Compiler support

 

mkl_sequential.lib

Sequential library.

All oneMKL function domains support sequential mode.

   

Computational Layer

      

mkl_core.lib

All non–architecture-specific implementation and library dispatcher for architecture-specific kernels.

Read more about how to work with mkl_enable_instructions and mkl_cbwr_set in the developer reference.

mkl_core is required for any link configurations.

   

Cluster Libraries

      

mkl_scalapack_lp64.lib

ScaLAPACK routine library supporting the LP64 interface.

Cluster support

 

mkl_scalapack_ilp64.lib

ScaLAPACK routine library supporting the ILP64 interface.

Cluster support

 

mkl_cdft_core.lib

Cluster version of FFTs.

Cluster support

 

mkl_blacs_intelmpi_lp64.lib

LP64 version of BLACS routines supporting Intel® MPI Library.

Cluster support

 

mkl_blacs_intelmpi_ilp64.lib

ILP64 version of BLACS routines supporting Intel MPI Library.

Cluster support

 

mkl_blacs_msmpi_lp64.lib

LP64 version of BLACS routines supporting Microsoft* MPI.

Cluster support

 

mkl_blacs_msmpi_ilp64.lib

ILP64 version of BLACS routines supporting Microsoft* MPI.

Cluster support

 
NOTE:

In case any functionality from a specific library is needed, this library should be added to the link line. For example, if you want to use oneMKL with the Intel compiler + ILP64 interface + Intel OpenMP threading, the link line should contain:

  1. mkl_intel_ilp64_dll for ILP64 interface
  2. mkl_intel_thread_dll for Intel OpenMP threading
  3. mkl_core_dll for all other oneMKL functionality

Details about what should be linked in different cases can be found in the oneMKL Link Line Advisor.

Parent topic: Detailed Structure of the Intel® 64 Architecture Directories
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