Originally published at: https://developer.nvidia.com/blog/machine-learning-frameworks-interoperability-part-2-data-loading-and-data-transfer-bottlenecks/
Introduction 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! Figure 1: Interoperability between data science and machine…