Overview: A highly scalable, highly durable, low cost object store. It's suitable for storing vast datasets required for training and model checkpoints, as well as hosting the final trained models. Cloud Storage with Cloud Storage FUSE is the recommended storage solution for most AI and ML use cases because it lets you scale your data storage with more cost efficiency than file system services.
Supports large scale (up to EBs) training data for GPU and TPU clusters.
Supports high-throughput (up to 1.25TB/s bandwidth or greater). To maximize your throughput in Cloud Storage, request more bandwidth.
Through integration with Cloud Storage FUSE, Cloud Storage buckets can be mounted as local file systems. The Cloud Storage FUSE CSI driver also lets you mount buckets as local file systems in Google Kubernetes Engine (GKE) for scaled AI and ML workloads.
Use Anywhere Cache to colocate storage in the same zone as compute workloads, providing higher throughput (up to 2.5TB/s), lower latency, and location flexibility when used with a multi-region bucket.
Overview: A high performance, fully managed parallel file system optimized for AI and high performance computing (HPC) applications. Suited for environments in which multiple compute nodes need fast and consistent access to shared data for simulations, modeling, and analysis.
Scales to 8 PB capacity and up to 1 TB/s of throughput.
Supports thousands of IOPS/TiB.
Delivers ultra low sub-ms latency.
Has full POSIX support which enables out of the box migration of on-premises AI workloads to Google Cloud.
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