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NetApp's Novus architecture addresses a critical infrastructure bottleneck by enabling zettabyte-scale storage with high-bandwidth parallel NFS, directly supporting the massive data throughput required for training large-scale AI models across thousands of GPUs. By resolving metadata latency issues, this hardware and software stack removes a key constraint on scaling generative AI workloads in enterprise environments.

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NetApp Eliminates Metadata Bottleneck for Zettascale Storage with New Novus Architecture

HPCwire1 octombrie 20261 min de cititArticolul și perspectiva sunt în engleză.

NetApp this week rolled out Novus, a new class of storage architecture that it says can store zettabytes worth of data and deliver 100 TB/second of aggregate bandwidth over NFS and parallel NFS, enough to keep hundreds of thousands of GPUs productive simultaneously. “AI Factory math is unforgiving,” writes Arindam Banerjee, the chief platform and […] The post NetApp Eliminates Metadata Bottleneck for Zettascale Storage with New Novus Architecture appeared first on HPCwire.

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