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Solve Enhanced Math Problems on GPUs: Linear Algebra, Sparse Matrices, and RNGs

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Overview

Intel® Math Kernel Library (Intel® MKL) has been the most widely used math library in the data center compute industry†, holding that distinction since 2015.

This year, its capabilities have expanded.

Now known as the Intel® oneAPI Math Kernel Library (oneMKL), it has been optimized for cross-architecture performance, enabling complex math-processing routines to run on CPUs, GPUs, FPGAs, and other accelerators.

Join Intel software specialist Khang Nguyen to learn how oneMKL can help you develop and deploy performant math-heavy applications, with particular focus on solving heterogeneous GPU challenges.

He demonstrates:

  • New features of oneMKL, including new sparse and LAPACK functionality, and a preview of random number generator (RNG) capabilities
  • Coding examples built with Data Parallel C++ (DPC++) and oneMKL
  • CPU-to-GPU offload capabilities
  • The power of oneMKL open source domain interfaces
  • oneMKL (and other development tools with Intel hardware) in the Intel® Developer Cloud

 

Get the Software

  • Download oneMKL as part of the Intel® oneAPI Base Toolkit—includes nearly 20 development tools and libraries for creating cross-architecture applications.
  • Sign up for an Intel® Developer Cloud for oneAPI account—a free development sandbox with access to the latest Intel hardware and oneAPI software.

 

Other Resources

  • Get started with oneMKL.
  • Explore performance benchmarks.
  • Learn more about DPC++.
  • Subscribe to Code Together—an interview series that explores the challenges at the forefront of cross-architecture development. Each biweekly episode features industry VIPs who are blazing new trails through today’s data-centric world. Available wherever you get your podcasts.

† Data from Evans Data Software Developer survey, 2015-2020

 

Khang T Nguyen
Software technical consulting engineer, Intel Corporation

Khang Nguyen joined Intel in 2000 and is currently a performance library technical consulting engineer (TCE) specializing in Intel MKL. Prior to joining the TCE organization, he was an application engineer responsible for helping customers optimize their applications for performance and power on Intel architecture. Khang holds a bachelor’s degree in electrical engineering from Portland State University and in mechanical engineering from Oregon Institute of Technology.

 

Tim Allen
Product line manager, Intel Corporation

Tim is a product line manager for oneAPI performance libraries. Prior to his current role, Tim was an Intel business development manager driving enablement for enterprise software companies related to the cloud, big data, analytics, AEC, commercial VR, datacenter, and IoT. Tim has more than 20 years of industry experience including work as a systems analyst, developer, system administrator, enterprise systems trainer, product marketing engineer, and marketing program manager. Prior to Intel, Tim worked at IBM*, Tektronix*, Intersolv, Sequent, and Con-Way Logistics. Tim holds a BSEE in computer engineering from BYU and an MBA in finance from the University of Portland. Specialties include–PMP, Java*, Shell, Python*, Perl, C, and C++.

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Intel® oneAPI Base Toolkit

Develop high-performance, data-centric applications for CPUs, GPUs, and FPGAs with this core set of tools, libraries, and frameworks including LLVM*-based compilers.

 

Get It Now

 

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