DDN EXASCALER
AI Data Storage for Extreme Performance in AI Training
From AI factories to NVIDIA DGX SuperPOD deployments to the world’s fastest supercomputers, DDN EXAScaler® is a high-performance parallel file system built for AI training at scale. Deliver multi-terabyte per second throughput, up to 99% GPU utilization, plus faster checkpointing and model loading to eliminate data bottlenecks across large scale AI clusters.
Trusted for AI Training and HPC at Scale
Why EXAScaler
Why EXAScaler Leads for AI Training Storage
EXAScaler is a high-performance parallel file system and AI data storage platform built on Lustre architecture, designed for large scale AI training infrastructure and HPC environments. It delivers deterministic performance across thousands of GPUs, enabling efficient distributed training with high throughput for modern AI workloads.
Unlike traditional storage architectures, EXAScaler provides the consistent throughput and checkpointing performance required to keep GPUs fully utilized during large scale training.
As part of the DDN Data Intelligence Platform, EXAScaler is the proven foundation for AI training infrastructure, supporting both training and production workloads without compromising performance.
Proven Performance at Scale
Up to 99% GPU Utilization
Maximize GPU efficiency with high throughput storage that eliminates idle time and keeps large scale AI clusters fully utilized.
15X Faster Checkpointing
Accelerate checkpointing performance and model loading to reduce training interruptions and improve distributed training efficiency.
Industry Leading IO500 Performance
Consistently ranked among the top HPC data storage platforms, delivering leading performance for AI training and HPC supercomputing.
ExaScale Proven Architecture
Powering 7 of the top 10 supercomputers, EXAScaler is validated for the largest AI training and HPC environments in the world.
KEY CAPABILITIES
Purpose Built for AI Training and HPC Supercomputing
Parallel File System (Lustre)
Built on Lustre architecture, enabling concurrent data access and consistent high throughput across thousands of GPUs for distributed AI training.
High-Throughput Data Delivery
Deliver multi-terabyte per second throughput to keep GPUs continuously fed with data, eliminating bottlenecks in large-scale training environments.
USE CASES
Built for AI Training and HPC Workloads
Large Language Model Training
Train foundation models across thousands of GPUs with high throughput storage that maximizes utilization and accelerates time to convergence.
Distributed AI Training Infrastructure
Enable distributed training with consistent checkpointing performance and scalable data access across large scale AI clusters.
HPC and Scientific Computing
Support data intensive simulations and research workloads with high performance file system architecture and deterministic throughput.
Data Storage for AI Training
Provide optimized GPU storage for training workloads, ensuring fast data delivery and efficient model iteration cycles.
“NVIDIA is powered by DDN. Without DDN, NVIDIA supercomputers would not be possible.”
Jensen Huang
NVIDIA / NVIDIA Founder and CEO
CUSTOMER STORIES
Real Results. Real Impact. Real Stories.
See how DDN EXAScaler helped CINECA cut tsunami forecasting times with urgent computing built for real-time disaster response.
Using Data For Early Detection
Discover how DDN A³I helped Roche accelerate genome sequencing and reduce analysis time with NVIDIA GPU-powered infrastructure.
Accelerating Science for Breakthrough Therapies
Learn how DDN data intelligence platforms supported Scripps Research in simplifying cryo-EM workflows and speeding up vaccine and drug discovery.
RELATED SOLUTIONS
Complete Your AI Training Infrastructure
Infinia
Next generation AI data platform for real time inference and advanced data services. Complements EXAScaler for full lifecycle AI deployments.
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Data Intelligence Platform
Unified platform for AI training, RAG, inference, and analytics across environments.
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Frequently Asked Questions
A parallel file system for AI is a high performance storage architecture that enables multiple GPUs and compute nodes to access data simultaneously, ensuring high throughput for distributed training workloads.
EXAScaler is a high performance parallel file system and AI data storage platform built on Lustre architecture, designed for AI training infrastructure and HPC workloads.
AI training requires high throughput storage to feed GPUs continuously. Without it, GPUs sit idle, increasing cost and slowing model development.
EXAScaler accelerates checkpointing by enabling parallel data writes and reads, reducing training interruptions and improving distributed training efficiency.
High performance parallel file systems like EXAScaler are best suited for AI training because they provide the throughput, concurrency, and reliability required for large scale GPU workloads.