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

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ID 766690
Date 10/15/2026
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Document Table of Contents
Document Table of Contents x
Developer Guide for Intel® oneAPI Math Kernel Library (oneMKL) for Linux*
Developer Guide for Intel® oneAPI Math Kernel Library (oneMKL) for Linux* 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 Coding Tips Managing Output Working with the Intel® Math Kernel Library Cluster Edition Software Managing Behavior of the Intel® oneAPI Math Kernel Library with Environment Variables Programming with Intel® Math Kernel Library in an Integrated Development Environment (IDE) Intel® 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
Setting Environment Variables x
Modulefiles to Set Environment Variables Automating the Process of Setting Environment Variables Using the CMake Config File
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 Shared Objects
Linking Quick Start x
Using the q mkl Compiler Options Using the mkl-ilp64 Compiler Option Using the Single Dynamic Library Selecting Libraries to Link With Using the Link-line Advisor Using the Command-Line Link Tool
Linking Examples x
Linking on Intel ® 64 Architecture Systems
Linking in Detail x
Listing Libraries on a Link Line 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 Shared Objects x
Using the Custom Shared Object Builder in the Command-Line Mode Composing a List of Functions Specifying Function Names Distributing Your Custom Shared Object
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 Intel® 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
Intel® 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 Intel® 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
Coding Tips x
Example of Data Alignment Using Predefined Preprocessor Symbols for Intel® oneMKL Version-Dependent Compilation Querying oneMATH Specification Version Compliance
Managing Output x
Using oneMKL Verbose Mode
Using oneMKL Verbose Mode x
Version Information Line Call Description Line
Working with the Intel® Math Kernel Library Cluster Edition Software x
Linking with Intel® Math Kernel Library Cluster Edition Software Working with OpenMP* Threads Using Shared Libraries 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 an Integrated Development Environment (IDE) x
Configuring the Eclipse* IDE CDT to Link with Intel® oneMKL
Intel® Math Kernel Library Benchmarks x
Intel Optimized LINPACK Benchmark for Linux* Intel® Distribution for LINPACK* Benchmark and Intel® Optimized HPL-AI* Benchmark Intel® Optimized High Performance Conjugate Gradient Benchmark
Intel Optimized LINPACK Benchmark for Linux* 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 Intel® Optimized HPL-AI* Benchmark Building the Intel® Distribution for LINPACK* Benchmark and 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 Intel® Optimized HPL-AI* Benchmark Heterogeneous Support in the Intel® Distribution for LINPACK* Benchmark Environment Variables Improving Performance of Your Cluster
Intel® Optimized High Performance Conjugate Gradient Benchmark x
Versions of the Intel® CPU Optimized HPCG Versions of the Intel® GPU Optimized HPCG Getting Started with Intel® CPU Optimized HPCG Getting Started with Intel® GPU Optimized HPCG Choosing the Best Configuration and Problem Sizes for CPUs Choosing the Best HPCG Configuration for GPUs
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
Static Libraries in the lib Directory Dynamic Libraries in the lib Directory
Developer Guide for Intel® oneAPI Math Kernel Library (oneMKL) for Linux*

Using MKL_DIRECT_CALL in C Applications

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