Which NetApp technology can preload a subset of data to accelerate AI workloads?

• A. FlexCache
• B. Flash Cache
• C. SnapVault
• D. Flash Pool

Answer: (A)

Caching data close to the compute nodes to reduce latency for AI workloads. FlexCache creates a caching layer that stores frequently accessed data from a source ONTAP volume in a cache location near the AI compute, allowing you to preload or warm a subset of the dataset into the cache so the AI jobs read from fast storage instead of the primary array each time. This reduces latency, speeds up training or inference, and can lower bandwidth needs to the origin since the cache serves the repeatedly accessed data and stays coherent with the source.

While Flash Cache and Flash Pool speed up IO by keeping hot data on flash, they’re primarily internal to the primary storage path rather than a separate near-compute cache designed to preload a specific data subset for AI workloads. SnapVault is focused on data protection and backup, not acceleration. FlexCache is the option that best matches the goal of preloading a subset of data to speed AI tasks.