Podcast: HPCC — Open-Source Platform High-Performance Computing on Large-Scale Data
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In this episode of the Ai X Podcast, Bob Foreman, Lead Software Engineering LexisNexis Risk Solutions, joins us to discuss the High-Performance Computer Cluster (HPCC) project, an open-source, massive parallel-processing computing platform for data processing and analytics.
Bob has spent more than a decade working with HPCC Systems and with the Enterprise Control Language as a course developer and trainer. Not only is he a highly experienced developer, but he is also the designer of the HPCC Systems online training courses and is the senior instructor for all classroom and remote-based training.
Join him for a deep dive into the HPCC project to discover how it simplifies complex data analysis at scale and why it’s an ideal tool for students, startups, or companies exploring or running POC for large-scale data-intensive computing.
Topics Include:
- What high-speed data engineering involves and why it’s important in big data solutions
- Main components of the HPCC Systems platform
- Where the HPCC Systems platform fits in the data landscape
- The role of Thor, Roxie, and ECL in the platform
- Example of how ECL (Enterprise Control Language) can be used to manipulate and analyze large datasets
- How to get started with HPCC’s open-source massive parallel system.
- Working with small sets of data before getting to large data sets
- The Machine Learning Library native to HPCC
Start listening now to get the full impact of Dr. Jon Krohn’s extensive knowledge and expertise and don’t forget to subscribe to ODSC’s Ai X Podcast to ensure you never miss an episode. Finally, like what you hear? Leave a review or share it with a friend! You can listen on Spotify, Apple, and SoundCloud.
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Originally posted on OpenDataScience.com
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