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ISC 2026: Toshiba Demonstrated Storage Infrastructure for Scientific AI and Research

25 d ago

DDN, a leader in AI and data intelligence solutions, announced a major expansion of its AI & HPC data platform portfolio at ISC 2026, delivering innovations in performance, efficiency, security, and cloud-scale AI infrastructure. Key launches include the AI400X3M high-performance appliance, the official release of DDN’s distributed KV Cache acceleration technology integrated with Nvidia Dynamo, and new security, observability, and infrastructure efficiency enhancements for large-scale AI environments. The AI400X3M, the latest evolution of DDN’s EXAScaler platform, offers up to 35% higher read throughput than the previous generation, up to 190GB/s throughput, exceptional performance density (up to 30 PB in a single rack), and hybrid disk support for optimized economics. General availability is expected by Q3 2026. DDN also launched its distributed KV Cache acceleration architecture integrated with Nvidia Dynamo, available across DDN Infinia and EXAScaler platforms. This solution accelerates large-scale AI inference by eliminating memory bottlenecks, enabling up to 55x faster KV cache loading, and improving GPU utilization and cost per token. It supports agentic AI, reasoning models, RAG, and multi-step inference pipelines. Additional platform enhancements include security features like bare-metal multi-tenancy, KMIP-based encryption, and VictoriaLogs integration for operational visibility, as well as efficiency features such as intelligent file pinning and NAND-accelerated Hot Pools for tiering data from flash to HDDs. DDN also highlighted cloud AI momentum, including new Managed Lustre innovations with Google Cloud and a Salesforce deployment that achieved 1.5x faster model training, 75% reduction in I/O latency, and 42% reduction in training costs. These results demonstrate how DDN helps remove data bottlenecks and improve GPU productivity. DDN’s AI data intelligence platform powers many of the world’s largest AI environments, including hyperscalers, sovereign AI initiatives, cloud providers, research institutions, and enterprise AI factories. The company continues to focus on maximizing GPU ROI, reducing cost per token, and accelerating business outcomes across the full AI lifecycle. CEO Alex Bouzari emphasized that AI infrastructure now depends on efficiently moving, managing, securing, and operationalizing data.