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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
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
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
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
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Coding Tips
This section provides coding tips for managing data alignment and version-specific compilation.
- Example of Data Alignment
- Using Predefined Preprocessor Symbols for Intel® MKL Version-Dependent Compilation
See Also
Mixed-language Programming with the Intel® oneAPI Math Kernel Library Tips on language-specific programming
Managing Performance and Memory Coding tips related to performance improvement and use of memory functions
Obtaining Numerically Reproducible Results Tips for obtaining numerically reproducible results of computations