Machine Learning Frameworks Interoperability, Part 2: Data Loading and Data Transfer Bottlenecks – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-03-21T20:30:26Z http://www.open-lab.net/blog/feed/ Christian Hundt <![CDATA[Machine Learning Frameworks Interoperability, Part 2: Data Loading and Data Transfer Bottlenecks]]> http://www.open-lab.net/blog/?p=35948 2022-08-21T23:52:27Z 2021-08-17T16:30:00Z Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks,...]]> Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks,...

Efficient pipeline design is crucial for data scientists. When composing complex end-to-end workflows, you may choose from a wide variety of building blocks, each of them specialized for a dedicated task. Unfortunately, repeatedly converting between data formats is an error-prone and performance-degrading endeavor. Let��s change that! In this post series, we discuss different aspects of��

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