OpenMP* Offload: Solving Linear Systems Using oneMKL on GPUs
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Overview
This session addresses the challenge of speeding up the linear algebra for Intel® oneAPI Math Kernel Library (oneMKL) kernel on GPUs through OpenMP*. (This is important because it allows you to maintain the same code base for CPU and GPU OpenMP acceleration.)
You’ll learn the technique through a demonstration of how to solve a 1000 x 1000 complex number matrix by calling the GPU version of the oneMKL subroutine on Intel® Data Center GPU Max Series processors.
This session explores:
- An overview of OpenMP, including how it’s a built-in solution for Fortran users to take advantage of Intel GPU hardware and its offload capabilities
- How to dispatch a oneMKL math kernel, such as solving a complex number matrix, to the latest Intel GPU
- Compiling the code example using the latest Intel® Fortran Compiler
- Using OpenMP data construct to manage data movement between the host and target devices
- How to monitor and optimize host-target data movement by the OpenMP runtime library
Skill level: Intermediate
Featured Software
Download the following stand-alone products or as part of the Intel® oneAPI Base Toolkit:
Download Code Samples
Develop high-performance, data-centric applications for CPUs, GPUs, and FPGAs with this core set of tools, libraries, and frameworks including LLVM*-based compilers.
Accelerate math processing routines and increase performance with advanced math routines and functions for science, engineering, or financial applications.
Build applications that can scale for the future with optimized code designed for Intel® Xeon® CPUs and GPUs. Provides full standards support through Fortran 2018.
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