The insatiable demand for compute resources continues to drive the need for ever larger on-premise systems. Simultaneously, the use of public cloud compute resources has also grown with companies like Amazon Web Services (AWS)*, Google Cloud Platform* service, Microsoft Azure*, and others.

In both cases, the key to great application performance is twofold: optimized parallel code and optimized use of the appropriate system resources.

This webinar shows you how it is done.

Join Intel technical consulting engineer Jennifer DiMatteo to learn the best practices of preparing, analyzing, setting up, and running HPC applications on-premise and in the cloud. Topics include:

  • Overview of parallelizing your code to exploit the power of modern hardware
  • Overview of public cloud resources—AWS, Google Cloud Platform service, and Microsoft Azure
  • A walkthrough of performance analysis tools—Intel® VTune™ Profiler and Intel® Advisor
  • How to get and use the latest runtimes for your cloud service provider
  • Large cloud service provider optimizations and how to set them up using Intel® Distribution for Python* and associated packages optimized by Intel

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Jennifer DiMatteo
Technical consulting engineer, Intel Corporation

Jennifer DiMatteo is part of the developer tools organization at Intel, and provides customer support with a focus on performance optimization using the analyzer tools. Prior to joining Intel in 2015, she spent 14 years developing public safety software and two years doing a little of everything. Jennifer holds a bachelor of science degree in software engineering technology from the Oregon Institute of Technology.

 

Intel® Advisor

Design code for efficient vectorization, threading, memory usage, and GPU offloading. Intel Advisor is included as part of the Intel® oneAPI Base Toolkit.

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