High-Performance Data Analytics with Julia* and Intel® Math Kernel Library (Intel® MKL)

Overview

Although relatively new, Julia* (free and open source) is quickly gaining popularity as a programming language that helps HPC coding practitioners solve challenges specific to high-performance and high-scalability applications in Deep Learning and Numerical Computations.

Join us for a fast-paced, information-packed hour that will:

  • Discuss the benefits of Julia
  • Showcase how developers are using Julia in finance, bioscience, astronomy, autonomous vehicles, and other emerging fields
  • Demonstrate how performance libraries such as Intel® Math Kernel Library (Intel® MKL) + Julia can boost developer performance and productivity

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Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804