Description
Distributed RAFT workflows help Python and Dask users run accelerated vector-search and data-processing tasks across larger workloads. They are useful for analytics clusters, machine-learning experiments, and GPU-backed batch processing.
This is a Python library for distributed computation, not a finished service. Correct use depends on cluster setup, GPU resources, data partitioning, and workflow validation.