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#### Developer References

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#### Intel® Math Kernel Library on Intel® Xeon Phi processors for Windows*

Intel® Math Kernel Library (Intel MKL) support on Intel® Xeon Phi has been extended to 64 bit versions of Microsoft* Windows from Intel MKL 11.1...

#### Improving Performance of Math Functions with Intel® Math Kernel Library

Introduction Intel® Math Kernel Library1 (Intel® MKL) is a product that accelerates math processing routines to increase the performance of an...

#### Which version of the Intel® IPP, Intel® MKL and Intel® TBB Libraries are Included in the Intel® Composer Bundles?

Intel IPP, Intel MKL, Intel TBB versions included in Intel Composer

#### How to Get Intel® MKL/IPP/DAAL

This page provides links to the current ways to get the Intel® performance library: Intel® Math Kernel Library, Intel® Integrated Performance...

#### Intel® MKL and C++ template libraries

There are a few existing open source C++ template libraries that can be linked with Intel® MKL. Please refer to the documentation placed on the web-...

#### Setting number_of_user_threads for Intel® Math Kernel Library FFTW3 wrappers

Consider the case when you Create a FFTW3 plan and use the plan for sequential DFT computation on each thread in your parallel region Use Intel...

#### Verbose Mode Supported in Intel® MKL

Introduction: We Introduced a useful verbose mode support feature since the Intel® Math Kernel Library (Intel® MKL) 11.2, for BLAS and LAPACK...

#### Intel® Parallel Studio XE 2018 Professional Edition for Windows

Product tour with videos and samples Learn when and how to use the Intel Parallel Studio XE components in a typical software development workflow...

#### Getting Started with Intel® Math Kernel Library 2018 for macOS*

Intel® Math Kernel Library (Intel® MKL) helps you achieve maximum performance with a computing math library of highly optimized, extensively...

#### Getting Started with Intel® Math Kernel Library 2018 for Windows*

Intel® Math Kernel Library (Intel® MKL) helps you achieve maximum performance with a computing math library of highly optimized, extensively...

#### Getting Started with Intel® Math Kernel Library 2018 for Linux*

Intel® Math Kernel Library (Intel® MKL) helps you achieve maximum performance with a computing math library of highly optimized, extensively...

#### Developer Guide for Intel® Math Kernel Library 2018 for macOS*

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Related Information
- Getting Started
- Structure of the Intel® Math Kernel Library
- Linking Your Application with the Intel® 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 Software
- Managing Behavior of the Intel(R) Math Kernel Library with Environment Variables
- Configuring Your Integrated Development Environment to Link with Intel(R) Math Kernel Library
- Intel® Math Kernel Library Benchmarks
- Appendix A: Intel® Math Kernel Library Language Interfaces Support
- Appendix B: Support for Third-Party Interfaces
- Appendix C: Directory Structure in Detail
- Legal Information

#### Developer Guide for Intel® Math Kernel Library 2018 for Windows*

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Related Information
- Getting Started
- Structure of the Intel® Math Kernel Library
- Linking Your Application with the Intel® 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 Software
- Using Intel® Math Kernel Library on Intel® Xeon Phi™ Coprocessors
- Managing Behavior of the Intel(R) Math Kernel Library with Environment Variables
- Programming with Intel® Math Kernel Library in Integrated Development Environments (IDE)
- Intel® Math Kernel Library Benchmarks
- Appendix A: Intel® Math Kernel Library Language Interfaces Support
- Appendix B: Support for Third-Party Interfaces
- Appendix C: Directory Structure in Detail
- Legal Information

#### Developer Guide for Intel® Math Kernel Library 2018 for Linux*

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Related Information
- Getting Started
- Structure of the Intel® Math Kernel Library
- Linking Your Application with the Intel® 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 Software
- Using Intel® Math Kernel Library on Intel® Xeon Phi™ Coprocessors
- Managing Behavior of the Intel(R) Math Kernel Library with Environment Variables
- Configuring Your Integrated Development Environment to Link with Intel(R) Math Kernel Library
- Intel® Math Kernel Library Benchmarks
- Appendix A: Intel® Math Kernel Library Language Interfaces Support
- Appendix B: Support for Third-Party Interfaces
- Appendix C: Directory Structure in Detail
- Legal Information

#### Developer Reference for Intel® Math Kernel Library 2018 - Fortran

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Overview
- BLAS and Sparse BLAS Routines
- LAPACK Routines
- ScaLAPACK Routines
- Sparse Solver 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 D: FFTW Interface to Intel® Math Kernel Library
- Appendix E: Code Examples
- Bibliography
- Glossary
- Legal Information

#### Developer Reference for Intel® Math Kernel Library 2018 - C

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Overview
- BLAS and Sparse BLAS Routines
- LAPACK Routines
- Deep Neural Network Functions
- ScaLAPACK Routines
- Sparse Solver 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 D: FFTW Interface to Intel® Math Kernel Library
- Appendix E: Code Examples
- Bibliography
- Glossary
- Legal Information

#### Using Intel® MKL in your C# program

This article explains how to create a DLL from the Intel® Math Kernel Library static libraries and access its functionality from within your C#...

#### Intel® Math Kernel Library Release Notes and New Features

This page provides the current Release Notes for Intel® Math Kernel Library. The notes are categorized by year, from newest to oldest, with...

#### Intel® Math Kernel Library Benchmarks (Intel® MKL Benchmarks)

Intel MKL Benchmarks package includes Intel® Distribution for LINPACK* Benchmark, Intel® Distribution for MP LINPACK* Benchmark for Clusters, and...

#### Link your Project to MKL libraries

Introduction How to link your project to MKL libraries, linking tips for MKL libraries, and Intel® Math Kernel Library compiler issues. Intel®...

#### Manufacturing Package Fault Detection Using Deep Learning

Executive Summary Intel's Software and Services Group engineers recently worked with assembly and test factory engineers on a proof of concept...

#### Intel(R) Math Kernel Library - Introducing Vectorized Compact Routines

Introduction Many high performance computing applications depend on matrix operations performed on large groups of matrices of small sizes...

#### New ILP64 ( 64-bit integer) pardiso_64 interface of PARDISO is now available

The new ILP64 ( 64-bit integer ) version of the PARDISO, namely PARDISO_64, is now available. The interface of Pardiso_64 is equal to the interface...

#### Machine Learning and Knowledge Reasoning Probing with Intel® Architecture

This article presents a performance test of Intel® tuning platform composed by Intel® processor, Intel® C++ Compiler XE and Intel® Math Kernel...

#### Build R-3.4.1 with Intel® C++ and Fortran Compilers and Intel® MKL on Linux*

R is a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical...

#### Optimize Matrix Operations Using the Intel® Math Kernel Library (Intel® MKL) for Linux*

Shows Intel® Math Kernel Library (Intel® MKL) performance by comparing a triply nested loop to a DGEMM routine.

#### Intel® Math Kernel Library (Intel® MKL) 2017 Install Guide

Please see the following links available online for the latest information regarding the Intel® Math Kernel Library (Intel® MKL): Intel® MKL Main...

#### Intel® MKL PARDISO

This is a compilation of all the Knowledge Base articles related to Intel® MKL PARDISO.

#### Intel® Math Kernel Library LAPACK Function Finding Advisor

Introduction The Intel® Math Kernel Library (Intel® MKL) LAPACK domain provides a huge variety of routines. To see what routines are recommended for...

#### Using Intel® MPI Library on Intel® Xeon Phi™ Product Family

This document is designed to help users get started writing code and running MPI applications using the Intel® MPI Library on a development platform...

#### Installing and Building MXNet with Intel® MKL

The latest version of MXNet includes built-in support for the Intel® Math Kernel Library (Intel® MKL) 2017. The latest version of the Intel MKL...

#### Get Onboard with the Intel® Parallel Studio XE 2018 Beta

Join technical experts to discuss trends in next-gen tools for AI/Machine Learning/Deep Learning, containerization, and threading on Intel platforms.

#### Performance of Classic Matrix Multiplication Algorithm on Intel® Xeon Phi™ Processor System

Matrix multiplication (MM) of two matrices is one of the most fundamental operations in linear algebra. The algorithm for MM is very simple, it could...

#### Developer Guide for Intel® Math Kernel Library 2018 (Beta) for Windows*

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Related Information
- Getting Started
- Structure of the Intel® Math Kernel Library
- Linking Your Application with the Intel® 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 Software
- Using Intel® Math Kernel Library on Intel® Xeon Phi™ Coprocessors
- Managing Behavior of the Intel(R) Math Kernel Library with Environment Variables
- Programming with Intel® Math Kernel Library in Integrated Development Environments (IDE)
- Intel® Math Kernel Library Benchmarks
- Appendix A: Intel® Math Kernel Library Language Interfaces Support
- Appendix B: Support for Third-Party Interfaces
- Appendix C: Directory Structure in Detail
- Legal Information

#### Developer Guide for Intel® Math Kernel Library 2018 (Beta) for Linux*

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Related Information
- Getting Started
- Structure of the Intel® Math Kernel Library
- Linking Your Application with the Intel® 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 Software
- Using Intel® Math Kernel Library on Intel® Xeon Phi™ Coprocessors
- Managing Behavior of the Intel(R) Math Kernel Library with Environment Variables
- Configuring Your Integrated Development Environment to Link with Intel(R) Math Kernel Library
- Intel® Math Kernel Library Benchmarks
- Appendix A: Intel® Math Kernel Library Language Interfaces Support
- Appendix B: Support for Third-Party Interfaces
- Appendix C: Directory Structure in Detail
- Legal Information

#### Developer Guide for Intel® Math Kernel Library 2018 (Beta) for macOS*

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Related Information
- Getting Started
- Structure of the Intel® Math Kernel Library
- Linking Your Application with the Intel® 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 Software
- Managing Behavior of the Intel(R) Math Kernel Library with Environment Variables
- Configuring Your Integrated Development Environment to Link with Intel(R) Math Kernel Library
- Intel® Math Kernel Library Benchmarks
- Appendix A: Intel® Math Kernel Library Language Interfaces Support
- Appendix B: Support for Third-Party Interfaces
- Appendix C: Directory Structure in Detail
- Legal Information

#### Getting Started with Intel® Math Kernel Library 2018 (Beta) for Linux*

#### Getting Started with Intel® Math Kernel Library 2018 (Beta) for macOS*

#### Getting Started with Intel® Math Kernel Library 2018 (Beta) for Windows*

#### Developer Reference for Intel® Math Kernel Library 2018 - Fortran (Beta)

Contents:

- Getting Help and Support
- What's New
- Notational Conventions
- Overview
- BLAS and Sparse BLAS Routines
- LAPACK Routines
- ScaLAPACK Routines
- Sparse Solver 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 D: FFTW Interface to Intel® Math Kernel Library
- Appendix E: Code Examples
- Bibliography
- Glossary
- Legal Information

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