Why AI/ML workloads benefit from NVMe-based flash
Beyond Big Data Storage For the AI/ML Era
The 3 critical pain points of traditional storage approaches to AI and machine learning (ML) are lack of efficiency, suboptimal performance, and insufficient orchestration.
NVMe and NVMe-oF can offer some reprieve, but they need to be implemented the right way, otherwise, the benefits are limited, and money is wasted.
This e-book highlights how AI and ML workloads will benefit from a storage infrastructure with NVMe-based flash arrays—from raw performance to improved parallel processing.
Access this e-book to see this relationship in action and to get an overview of one such solution built for the AI era: Pavilion’s Hyperparallel Flash Array (HFA).