AI-Ready Storage

Solutions

Accelerate AI Workloads with High-Performance, Scalable Storage

Atipa Technologies delivers storage solutions engineered for the demands of modern AI, HPC, and data analytics environments. Whether you're training large-scale models, processing real-time data, or managing massive datasets, our AI-ready storage platforms ensure your infrastructure keeps pace with innovation.

We offer two powerful options tailored to different performance and scalability needs: BeeGFS and VAST Data.

BeeGFS, a parallel file system optimized for performance and flexibility, is ideal for HPC environments requiring high-throughput access to distributed datasets. It scales seamlessly across compute nodes, delivering low-latency I/O and dynamic metadata handling for workloads such as genomics, CFD, and seismic processing. Atipa’s BeeGFS deployments are tuned for maximum efficiency with RDMA support, NVMe tiers, and integrated monitoring tools to ensure consistent performance under heavy load.

VAST Data, built on a disaggregated shared-everything architecture, combines QLC flash with persistent memory to deliver exabyte-scale storage with all-flash performance. Its support for NFS, SMB, and S3 protocols makes it a versatile choice for AI pipelines, real-time analytics, and multi-protocol data lakes. Atipa integrates VAST with GPU-accelerated compute clusters, enabling ultra-fast data access for training large models and running inference workloads without bottlenecks.

storage platforms

BeeGFS: High-Performance Parallel File System

BeeGFS (the BeeGFS File System) is designed for environments where I/O throughput and scalability are critical. Ideal for AI training, simulation, and scientific computing, BeeGFS distributes data across multiple servers to eliminate bottlenecks and maximize performance.

Key Features:

• Distributed metadata and data architecture
• Scales linearly with additional storage and compute nodes
• POSIX-compliant for seamless integration

Architecture:

• Clients: Compute nodes accessing storage via BeeGFS client modules
• Metadata Servers: Manage file system structure and access control
• Storage Servers: Host actual data blocks, distributed across nodes
• InfiniBand or Ethernet: High-speed interconnects for low-latency access

Use Cases:

• AI model training with large datasets
• Real-time analytics and simulation
• Multi-user HPC clusters
  

VAST Data: Unified Storage for AI and Deep Learning

VAST Data  offers a disaggregated, all-flash architecture that combines performance, scalability, and simplicity. Built for AI and deep learning workloads, VAST eliminates tiered storage complexity by delivering universal storage with QLC flash and persistent memory.

Key Features:

• Disaggregated compute and storage architecture
• Global namespace with support for NFS, SMB, S3, and RDMA
• Data reduction, encryption, and snapshot capabilities
• Ideal for GPU-accelerated environments

Architecture:

• Compute Nodes: AI/ML workloads running on CPU/GPU clusters
• VAST Servers: Stateless front-end nodes managing I/O
• Storage Enclosures: QLC flash and persistent memory pools
• RDMA Fabric: Enables ultra-fast data movement across nodes

Use Cases:

• Deep learning pipelines and inference workloads
• Video and image processing
• Genomics and life sciences
  

why Atipa for ai storage

Expert Integration

Performance-Driven

Optimized for GPU clusters, large-scale training, and real-time inference.



Secure & Reliable

Enterprise-grade components with built-in redundancy and data protection.



Flexible Deployment

Bare metal or turnkey solutions available.



Flexible Deployment

Bare metal or turnkey solutions available.



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