Selecting Libraries to Link with

Developer Guide

Developer Guide for Intel® oneAPI Math Kernel Library macOS*

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ID 766688

Date 11/07/2023

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Document Table of Contents

Document Table of Contents x

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

Developer Guide for Intel® oneAPI Math Kernel Library for macOS* 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 Configuring Your Integrated Development Environment to Link with Intel® oneAPI Math Kernel Library 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 Dynamically Linked Shared Libraries

Linking Quick Start x

Using the -qmkl Compiler Option Using the Single Dynamic Library Selecting Libraries to Link with See Also 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 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 Dynamically Linked Shared Libraries x

Using the Custom Dynamically Linked Shared Library Builder Composing a List of Functions Specifying Function Names Distributing Your Custom Dynamically Linked Shared 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

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

Linking with oneMKL Cluster 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 Apple Xcode* Developer Software to Link with Intel® Math Kernel Library

Intel® oneAPI Math Kernel Library Benchmarks x

Intel Optimized LINPACK Benchmark for macOS*

Intel Optimized LINPACK Benchmark for macOS* x

Contents of the Intel® Optimized LINPACK Benchmark Running the Software Known Limitations of the Intel® Optimized LINPACK Benchmark

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 for macOS*

Getting Help and Support

What's New

Notational Conventions

Related Information

Getting Started

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

Architecture Support

High-Level Directory Structure

Layered Model Concept

Linking Your Application with the Intel® oneAPI Math Kernel Library

Linking Quick Start

Using the -qmkl Compiler Option

Using the Single Dynamic Library

Selecting Libraries to Link with

See Also

Using the Link-line Advisor

Using the Command-Line Link Tool

Linking Examples

Linking on Intel(R) 64 Architecture Systems

Linking in Detail

Listing Libraries on a Link Line

Dynamically Selecting the Interface and Threading Layer

Linking with Interface Libraries

Using the ILP64 Interface vs. LP64 Interface

Linking with Fortran 95 Interface Libraries

Linking with Threading Libraries

Linking with Compiler Run-time Libraries

Linking with System Libraries

Building Custom Dynamically Linked Shared Libraries

Using the Custom Dynamically Linked Shared Library Builder

Composing a List of Functions

Specifying Function Names

Distributing Your Custom Dynamically Linked Shared Library

Managing Performance and Memory

Improving Performance with Threading

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

oneMKL-specific Environment Variables for OpenMP Threading Control

MKL_DYNAMIC

MKL_DOMAIN_NUM_THREADS

MKL_NUM_STRIPES

Setting the Environment Variables for Threading Control

Calling oneMKL Functions from Multi-threaded Applications

Using Intel® Hyper-Threading Technology

Improving Performance for Small Size Problems

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

Coding Techniques

Improving oneMKL Performance on Specific Processors

Operating on Denormals

Using Memory Functions

Avoiding Memory Leaks in oneMKL

Redefining Memory Functions

Language-specific Usage Options

Using Language-Specific Interfaces with Intel® oneAPI Math Kernel Library

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

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

Getting Started with Conditional Numerical Reproducibility

Specifying Code Branches

Reproducibility Conditions

Setting the Environment Variable for Conditional Numerical Reproducibility

Code Examples

Coding Tips

Example of Data Alignment

Using Predefined Preprocessor Symbols for Intel® MKL Version-Dependent Compilation

Managing Output

Using oneMKL Verbose Mode

Version Information Line

Call Description Line

Working with the Intel® oneAPI Math Kernel Library Cluster Software

Linking with oneMKL Cluster 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 for Linking a C Application

Examples for Linking a Fortran Application

Managing Behavior of the Intel® oneAPI Math Kernel Library with Environment Variables

Managing Behavior of Function Domains with Environment Variables

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

Instruction Set Specific Dispatching on Intel® Architectures

Configuring Your Integrated Development Environment to Link with Intel® oneAPI Math Kernel Library

Configuring the Apple Xcode* Developer Software to Link with Intel® Math Kernel Library

Intel® oneAPI Math Kernel Library Benchmarks

Intel Optimized LINPACK Benchmark for macOS*

Contents of the Intel® Optimized LINPACK Benchmark

Running the Software

Known Limitations of the Intel® Optimized LINPACK Benchmark

Appendix A: Intel® oneAPI Math Kernel Library Language Interfaces Support

Language Interfaces Support, by Function Domain

Include Files

Appendix B: Support for Third-Party Interfaces

FFTW Interface Support

Appendix C: Directory Structure in Detail

Static Libraries in the lib directory

Dynamic Libraries in the lib directory

Notices and Disclaimers

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Selecting Libraries to Link with

To link with Intel® oneAPI Math Kernel Library (oneMKL):

Choose one library from the Interface layer and one library from the Threading layer
Add the only library from the Computational layer and run-time libraries (RTL)

The following table lists Intel® oneAPI Math Kernel Library (oneMKL) libraries to link with your application.

	Interface layer	Threading layer	Computational layer	RTL
Intel® 64 architecture, static linking	libmkl_intel_lp64.a	libmkl_intel_thread.a	libmkl_core.a	libiomp5.dylib
Intel® 64 architecture, dynamic linking	libmkl_intel_lp64. dylib	libmkl_intel_thread.dylib	libmkl_core.dylib	libiomp5.dylib

The Single Dynamic Library (SDL) automatically links interface, threading, and computational libraries and thus simplifies linking. The following table lists Intel® oneAPI Math Kernel Library (oneMKL) libraries for dynamic linking using SDL. SeeDynamically Selecting the Interface and Threading Layer for how to set the interface and threading layers at run time through function calls or environment settings.

	SDL			RTL
Intel® 64 architecture	libmkl_rt.dylib			libiomp5.dylib^†

^†Use the Link-line Advisor to check whether you need to explicitly link the libiomp5.dylib RTL.

For exceptions and alternatives to the libraries listed above, see Linking in Detail.

Parent topic: Linking Quick Start

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Selecting Libraries to Link with

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