You can use Alluxio to speed up machine learning training and inference pipelines by placing a distributed cache between your compute resources and persistent object storage. It eliminates network bottlenecks by keeping frequently accessed datasets in memory or local NVMe drives across hybrid or multi-cloud environments. The system connects directly to frameworks like PyTorch, TensorFlow, and Ray using standard APIs like S3 and POSIX without requiring code changes. This reduces cloud egress fees, cuts down checkpoint write latency, and keeps your GPUs fully utilized.
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