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RCE 102: Spack

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Content provided by Brock Palen. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Brock Palen or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Spack is a package management tool designed to support multiple versions and configurations of software on a wide variety of platforms and environments. It was designed for large supercomputing centers, where many users and application teams share common installations of software on clusters with exotic architectures, using libraries that do not have a standard ABI. Spack is non-destructive: installing a new version does not break existing installations, so many configurations can coexist on the same system. https://github.com/scalability-llnl/spack Todd is a computer scientist in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory . His research focuses on scalable tools for measuring, analyzing, and visualizing performance the performance of massively parallel simulations. Todd works closely with production simulation teams at LLNL, and he likes to create tools that users can pick up easily. Frustrated with the complexity of building HPC performance tools, Todd started developing Spack two years ago to allow users to painlessly install software on big machines. Spack has since been adopted by Livermore Computing, other HPC centers, and LLNL application teams. The open source project now includes several core developers at LLNL and a rapidly growing community on GitHub. A 1.0 release is coming soon.
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20 episodes

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RCE 102: Spack

RCE - Super Computers

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Archived series ("Inactive feed" status)

When? This feed was archived on August 23, 2020 16:09 (4y ago). Last successful fetch was on April 07, 2020 17:04 (4+ y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 216901853 series 2442313
Content provided by Brock Palen. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Brock Palen or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Spack is a package management tool designed to support multiple versions and configurations of software on a wide variety of platforms and environments. It was designed for large supercomputing centers, where many users and application teams share common installations of software on clusters with exotic architectures, using libraries that do not have a standard ABI. Spack is non-destructive: installing a new version does not break existing installations, so many configurations can coexist on the same system. https://github.com/scalability-llnl/spack Todd is a computer scientist in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory . His research focuses on scalable tools for measuring, analyzing, and visualizing performance the performance of massively parallel simulations. Todd works closely with production simulation teams at LLNL, and he likes to create tools that users can pick up easily. Frustrated with the complexity of building HPC performance tools, Todd started developing Spack two years ago to allow users to painlessly install software on big machines. Spack has since been adopted by Livermore Computing, other HPC centers, and LLNL application teams. The open source project now includes several core developers at LLNL and a rapidly growing community on GitHub. A 1.0 release is coming soon.
  continue reading

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