AI Storage Infrastructure
Parallel file systems, NVMe, object storage, and data management for AI. Complete guides for designing storage that keeps GPUs fed and training jobs running at full throughput.
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Reference
Key Concepts
Parallel File Systems
Lustre, GPFS, and BeeGFS — the parallel file systems that deliver the aggregate bandwidth required for large-scale AI training workloads.
NVMe
NVMe SSDs and NVMe-oF — the storage technology that provides the low latency and high IOPS required for AI training data pipelines.
Object Storage
S3-compatible object storage for AI — dataset repositories, model artifact storage, and checkpoint management at petabyte scale.
Data Management
Dataset versioning, lineage tracking, and lifecycle policies — the practices that keep AI data pipelines organized and reproducible.
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