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DDN has announced a deepened technical collaboration with NVIDIA, focusing on optimizing data infrastructure for the next generation of AI factory architectures. This partnership ensures DDN's AI data intelligence platform is engineered to support the newly unveiled NVIDIA Rubin platform and NVIDIA BlueField-4 DPU, aiming to eliminate data bottlenecks and maximize performance at scale for enterprise and hyperscale AI deployments.
DDN aligns its AI data platform with NVIDIA's new Rubin and BlueField-4 architectures.
The collaboration targets the elimination of data bottlenecks in large-scale AI factories.
Key outcomes include up to 99% GPU utilization and reduced inference latency.
The platform supports the NVIDIA Inference Context Memory Storage Platform for long-context AI.
DDN powers over 1,000,000 GPUs globally and is certified for NVIDIA DGX SuperPOD.
The integration aims to translate architectural innovation into faster time-to-value for AI projects.
As AI models grow more complex with longer context windows and distributed inference, moving data efficiently becomes as critical as raw compute power. The collaboration between DDN and NVIDIA is designed to address this exact challenge within the unified architecture of an AI factory. Alex Bouzari, CEO and co-founder at DDN, emphasized the critical role of data, stating, “AI factories succeed or fail based on data efficiency. Our collaboration with NVIDIA is focused on a single outcome: ensuring that the world’s most advanced AI platforms—powered by NVIDIA Rubin and BlueField-4—are fed with data at full speed, at full scale, and with predictable performance.”
The NVIDIA Rubin platform represents a shift to rack-scale design, tightly integrating CPUs, GPUs, and networking. The BlueField-4 DPU offloads critical infrastructure services, creating a programmable layer for AI operations. DDN's platform is engineered to operate natively within this stack, aiming to deliver measurable business impacts such as higher GPU utilization, faster time-to-first-token in inference, and lower infrastructure overhead.
DDN's platform is specifically optimized for NVIDIA's latest innovations, including NVIDIA Spectrum-X Ethernet for Storage and DOCA-accelerated services on BlueField-4. This enables exascale data access to feed dense GPU configurations and provides a distributed key-value (KV) cache tier. This cache supports the NVIDIA Inference Context Memory Storage Platform, allowing AI models to access context data beyond GPU memory limits while maintaining low latency.
The integration leverages BlueField-4 acceleration engines for metadata processing and telemetry, enabling dynamic, intelligence-driven data placement as workloads shift. This design is intended to simplify data pipelines and reduce operational friction as models scale in size and complexity.
Beyond raw speed, the partnership addresses the need for secure, governable, and efficient production AI. The combined capabilities of DDN's data intelligence and BlueField-4 offload allow organizations to secure AI data end-to-end, enforce multi-tenant isolation, and gain real-time visibility into performance bottlenecks. DDN claims these integrations can reduce audit and compliance preparation time by up to 70% through unified observability.
With experience powering over a million GPUs in the world's most demanding environments, DDN positions its collaboration with NVIDIA as essential for transforming AI infrastructure into outcome-driven AI factories. The shared vision is to ensure data becomes a definitive competitive advantage, not a constraint, in the new era of scalable AI.
About DDN
DDN is the world’s leading provider of AI data storage and data management platforms, powering over 20 years of innovation across HPC, enterprise, and the largest AI deployments on Earth. With its EXA, Infinia, and intelligent data management platforms, DDN delivers unmatched performance, scale, and business value for customers building next-generation AI factories, hyperscale clouds, and Sovereign AI initiatives. DDN is the trusted partner for thousands of the world’s most data-intensive organizations, including the leading national labs, research institutions, enterprises, hyperscalers, financial firms, and autonomous vehicle innovators.
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