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Hammerspace Product Architecture

A Global File System Engineered for Distributed AI Pipelines

Stop letting traditional storage bottlenecks starve your compute. By separating metadata from the data path, Hammerspace delivers linear throughput and sub-millisecond file lookups directly to your GPU clusters, maximizing utilization at exabyte scale.

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A New Architecture for AI, HPC, and Globally Distributed Accelerated Computing

AI and accelerated computing are exposing the limitations of traditional storage architectures. Data now spans GPU clusters, clouds, regions, research environments, and enterprise infrastructure, but legacy NAS and proprietary HPC file systems were never designed to operate as a unified global data environment.

  • NAS doesn’t provide sufficient performance or scale.

  • Legacy HPC file systems are too complex and lack enterprise data services.

  • Neither architecture enables the multi-site and hybrid-cloud operations required by so many of today’s enterprises and research institutions.

Features

NAS

HPC File Systems

Hammerspace

Easy to Connect, Plug-N-Play

Easy to Connect, Plug-N-Play

Enterprise Data Services

Enterprise Data Services

HPC-Class Performance

HPC-Class Performance

Cost-Effective at Scale

Cost-Effective at Scale

Multi-Site, Hybrid-Cloud

Multi-Site, Hybrid-Cloud

The First Standards-Based Parallel File System Architecture

Unlike legacy parallel file systems that rely on proprietary clients to deliver high-throughput low-latency data access, Hammerspace uses capabilities built into the NFSv4.2 client that are now part of every modern Linux OS. Hammerspace engineered key Parallel NFS Flex Files capabilities and contributed them upstream to Linux years ago, enabling an intelligent standards-based parallel file system client built directly into the operating system.

High-Speed Network ... ... Scale to Thousands of GPU/Compute Nodes No Special Software - Just Linux Scale to Thousands of Storage Nodes No Special Software - Just Linux Metadata Server Every Client can Read/Write to any Volume in Parallel Metadata Data
High-Speed Network ... ... Scale to Thousands of GPU/Compute Nodes No Special Software - Just Linux Scale to Thousands of Storage Nodes No Special Software - Just Linux Metadata Server Metadata Data Every Client can Read/Write to any Volume in Parallel
This standards-based parallel file system architecture:

  • Delivers the high-throughput, low-latency performance required for AI, GPU data pipelines, and HPC workflows.

  • Does not require any proprietary client software.

  • Scales linearly to thousands of nodes.

  • Allows any file (NFS) and object (S3) storage system to be used as storage by Hammerspace - including SSD and HDD storage servers and server-local NVMe storage.

  • Spans multiple sites and clouds as a global file system.

Unlike scale-out NAS architectures that require a controller layer in the datapath, Hammerspace’s architecture decouples the metadata control plane from the data path, enabling a global namespace and policy control layer without introducing data-path latency. Policies, metadata services, and orchestration occur independently from the direct client-to-storage data path.
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Enabling a Global Namespace Without Introducing Data Path Latency

Scale-Out Architecture

Hammerspace Parallel File System Architecture

Turn Stranded NVMe Into the Fastest Storage in Your Cluster

AI and HPC environments increasingly deploy large amounts of high-performance NVMe storage inside GPU and compute servers, but that storage typically remains isolated to individual nodes. Hammerspace enables server-local NVMe to operate as a coordinated shared Tier 0 storage layer within the global file system, transforming previously stranded local storage into high-performance shared infrastructure for distributed AI and accelerated computing workloads.

4.4x
Higher Throughput
56%
Lower Latency 
66%
Faster Checkpointing
Because Hammerspace separates metadata orchestration from the direct data path, distributed local NVMe can be coordinated globally without introducing centralized storage bottlenecks.
Tier 0 Architecture

Enable Multi-Site and Hybrid-Cloud Operations with a Global File System

Join multiple Hammerspace clusters together to create a unified global file system that spans sites, cloud regions, and cloud providers. Hammerspace creates a global namespace with metadata-driven data orchestration policies, enabling organizations to leverage elastic cloud compute, accelerate distributed AI and HPC workflows, enable global collaboration, and enforce governance and data sovereignty policies across distributed infrastructure.
Hammerspace Global Namespace

Hammerspace Architecture Attributes and Benefits

High-Throughput Data Infrastructure for AI and HPC

To maximize GPU/CPU utilization and accelerate AI, HPC, and distributed data pipelines.

Linear Scalability to Thousands of Nodes

To support massive unstructured data environments without performance bottlenecks.

Standards-Based Connectivity, No Proprietary Clients

To simplify deployment and integration into existing Linux, AI, and HPC environments.

Decoupled Metadata and Data Paths

To enable metadata-driven orchestration and policy control without introducing data-path latency.

Infrastructure Independence

To leverage existing storage investments and maintain flexibility across on-premises and cloud environments.

Global Data Operations Across Sites and Clouds

To operationalize distributed data, accelerate collaboration, and support hybrid-cloud AI and HPC workflows.

Ready to See it in Action?

Hammerspace delivers the performance, scalability, and global reach that AI and HPC workloads demand. Talk to a solutions engineer and see how the architecture fits your environment.
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