Developer Guide

Developer Guide for Intel® oneAPI Math Kernel Library Linux*

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ID 766690
Date 6/30/2025
Public
Document Table of Contents
Document Table of Contents x
Developer Guide for Intel® oneAPI Math Kernel Library for Linux*
Developer Guide for Intel® oneAPI Math Kernel Library 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 Obtaining Numerically Reproducible Results 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 Configuring Your Integrated Development Environment to Link with Intel® oneAPI Math Kernel Library 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
Scripts to Set Environment Variables 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 -qmkl Compiler Option Using the -qmkl-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(R) 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 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 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 C Example of CNR Fortran Example of CNR Use of CNR with Unaligned Data in C Use of CNR with Unaligned Data in Fortran
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 Setting the Number of 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
Configuring Your Integrated Development Environment to Link with Intel® oneAPI Math Kernel Library x
Configuring the Eclipse* IDE CDT to Link with 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 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
Intel® Optimized High Performance Conjugate Gradient Benchmark x
Overview of the Intel Optimized HPCG 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
Detailed Structure of the Intel® 64 Architecture Directories
Detailed Structure of the Intel® 64 Architecture Directories x
Static Libraries in the lib Directory Dynamic Libraries in the lib Directory
Developer Guide for Intel® oneAPI Math Kernel Library for Linux*

Code Examples

The following simple programs show how to obtain reproducible results from run to run of Intel® oneAPI Math Kernel Library (oneMKL) functions. See the Intel® oneAPI Math Kernel Library (oneMKL) Developer Reference for more examples.

C Example of CNR

#include <mkl.h>
int main(void) {
    int my_cbwr_branch;
    /* Align all input/output data on 64-byte boundaries */
    /* for best performance of Intel® oneAPI Math Kernel Library (oneMKL) */
    void *darray;
    int darray_size=1000;
    /* Set alignment value in bytes */
    int alignment=64;
    /* Allocate aligned array */
    darray = mkl_malloc (sizeof(double)*darray_size, alignment);
    /* Find the available MKL_CBWR_BRANCH automatically */
    my_cbwr_branch = mkl_cbwr_get_auto_branch();
    /* User code without oneMKL calls */
    /* Piece of the code where CNR of oneMKL is needed */
    /* The performance of oneMKL functions might be reduced for CNR mode */
/* If the "IF" statement below is commented out, Intel® oneAPI Math Kernel Library (oneMKL) will run in a regular mode, */
    /* and data alignment will allow you to get best performance */
    if (mkl_cbwr_set(my_cbwr_branch)) {
        printf("Error in setting MKL_CBWR_BRANCH! Aborting…\n");
        return;
    }
    /* CNR calls to oneMKL + any other code */
    /* Free the allocated aligned array */
    mkl_free(darray);
}

Fortran Example of CNR

PROGRAM MAIN
    INCLUDE 'mkl.fi'
    INTEGER*4 MY_CBWR_BRANCH
! Align all input/output data on 64-byte boundaries
! for best performance of Intel® oneAPI Math Kernel Library (oneMKL)
! Declare oneMKL memory allocation routine
    DOUBLE PRECISION DARRAY
    POINTER (P_DARRAY,DARRAY(1))
    INTEGER DARRAY_SIZE
    PARAMETER (DARRAY_SIZE=1000)
! Set alignment value in bytes
    INTEGER ALIGNMENT
    PARAMETER (ALIGNMENT=64)
! Allocate aligned array
    INTEGER*8 ALLOC_SIZE
    ALLOC_SIZE = 8*DARRAY_SIZE
    P_DARRAY = MKL_MALLOC (ALLOC_SIZE, ALIGNMENT);
! Find the available MKL_CBWR_BRANCH automatically
    MY_CBWR_BRANCH = MKL_CBWR_GET_AUTO_BRANCH()
! User code without oneMKL calls
! Piece of the code where CNR of oneMKL is needed
! The performance of oneMKL functions may be reduced for CNR mode
! If the "IF" statement below is commented out,
! Intel® oneAPI Math Kernel Library (oneMKL) will run in a
! regular mode, and data alignment will enable you to get the best performance
    IF (MKL_CBWR_SET (MY_CBWR_BRANCH) .NE. MKL_CBWR_SUCCESS) THEN
        PRINT *, 'Error in setting MKL_CBWR_BRANCH! Aborting…'
        STOP 0
    ENDIF
! CNR calls to oneMKL + any other code
! Free the allocated aligned array
    CALL MKL_FREE(P_DARRAY)
END

Use of CNR with Unaligned Data in C

#include <mkl.h>
int main(void) {
     int my_cbwr_branch;
     /* If it is not possible to align all input/output data on 64-byte boundaries */
     /* to achieve performance, use unaligned IO data with possible performance */ 
     /* penalty */
     /* Using unaligned IO data */
     double *darray;
     int darray_size=1000;
     /* Allocate array, malloc aligns data on 8/16-byte boundary only */
     darray = (double *)malloc (sizeof(double)*darray_size);
     /* Find the available MKL_CBWR_BRANCH automatically */
     my_cbwr_branch = mkl_cbwr_get_auto_branch();
     /* User code without oneMKL calls */
     /* Piece of the code where CNR of oneMKL is needed */
     /* The performance of oneMKL functions might be reduced for CNR mode */
     /* If the "IF" statement below is commented out, oneMKL will run in a regular mode, */ 
     /* and you will NOT get best performance without data alignment */
     if (mkl_cbwr_set(my_cbwr_branch)) {
          printf("Error in setting MKL_CBWR_BRANCH! Aborting…\n");
          return;
}
     /* CNR calls to oneMKL + any other code */
     /* Free the allocated array */
     free(darray);

Use of CNR with Unaligned Data in Fortran

     PROGRAM MAIN
     INCLUDE 'mkl.fi'
     INTEGER*4 MY_CBWR_BRANCH
! If it is not possible to align all input/output data on 64-byte boundaries 
! to achieve performance, use unaligned IO data with possible performance 
! penalty 
     DOUBLE PRECISION, DIMENSION(:), ALLOCATABLE :: DARRAY
     INTEGER DARRAY_SIZE, STATUS
     PARAMETER (DARRAY_SIZE=1000)
! Allocate array with undefined alignment
     ALLOCATE(DARRAY(DARRAY_SIZE));
! Find the available MKL_CBWR_BRANCH automatically
     MY_CBWR_BRANCH = MKL_CBWR_GET_AUTO_BRANCH()
! User code without oneMKL calls
! Piece of the code where CNR of oneMKL is needed
! The performance of oneMKL functions might be reduced for CNR mode
! If the "IF" statement below is commented out, oneMKL will run in a regular mode, 
! and you will NOT get best performance without data alignment 
     IF (MKL_CBWR_SET(MY_CBWR_BRANCH) .NE. MKL_CBWR_SUCCESS) THEN
          PRINT *, 'Error in setting MKL_CBWR_BRANCH! Aborting…'
          RETURN
     ENDIF
! CNR calls to oneMKL + any other code
! Free the allocated array
     DEALLOCATE(DARRAY)
     END
Parent topic: Obtaining Numerically Reproducible Results
Level Two Title