Learn the best practices for performance analytics and maintenance of a deep learning system. As GPU technology continues to advance, the demand for faster data continues to grow. In deep learning, input pipelines are responsible for a complex chain of actions that ultimately feed data into GPU memory, including reading from storage and pre-processing data. These pipelines bring together multiple hardware systems, networking, CPUs, and storage along with sophisticated software systems to drive the data movement and transformation.
- AI is a Data Pipeline
- Don’t Throw Your Data into Data Lake
- Cloud or Not to Cloud?