NVIDIA introduced that the NVIDIA BlueField-4 knowledge processor, a part of the full-stack NVIDIA BlueField platform, powers NVIDIA Inference Context Reminiscence Storage Platform, a brand new class of AI-native storage infrastructure for the subsequent frontier of AI.
As AI fashions scale to trillions of parameters and multistep reasoning, they generate huge quantities of context knowledge represented by a key-value (KV) cache, vital for accuracy, person expertise and continuity.
A KV cache can’t be saved on GPUs long run, as this could create a bottleneck for real-time inference in multi-agent methods. AI-native purposes require a brand new sort of scalable infrastructure to retailer and share this knowledge.
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NVIDIA Inference Context Reminiscence Storage Platform offers the infrastructure for context reminiscence by extending GPU reminiscence capability, enabling high-speed sharing throughout nodes, boosting tokens per seconds by as much as 5x and delivering as much as 5x better energy effectivity in contrast with conventional storage.
“AI is revolutionizing the complete computing stack and now, storage,” stated Jensen Huang, founder and CEO of NVIDIA. “AI is not about one-shot chatbots however clever collaborators that perceive the bodily world, purpose over lengthy horizons, keep grounded in information, use instruments to do actual work, and retain each short- and long-term reminiscence. With BlueField-4, NVIDIA and our software program and {hardware} companions are reinventing the storage stack for the subsequent frontier of AI.”
NVIDIA Inference Context Reminiscence Storage Platform boosts KV cache capability and accelerates the sharing of context throughout clusters of rack-scale AI methods, whereas persistent context for multi-turn AI brokers improves responsiveness, will increase AI manufacturing facility throughput and helps environment friendly scaling of long-context, multi-agent inference.
Key capabilities of the NVIDIA BlueField-4-powered platform embody:
- NVIDIA Rubin cluster-level KV cache capability, delivering the dimensions and effectivity required for long-context, multi-turn agentic inference.
- As much as 5x better energy effectivity than conventional storage.
- Good, accelerated sharing of KV cache throughout AI nodes, enabled by the NVIDIA DOCA framework and tightly built-in with the NVIDIA NIXL library and NVIDIA Dynamo software program to maximise tokens per second, scale back time to first token and enhance multi-turn responsiveness.
- {Hardware}-accelerated KV cache placement managed by NVIDIA BlueField-4 eliminates metadata overhead, reduces knowledge motion and ensures safe, remoted entry from the GPU nodes.
- Environment friendly knowledge sharing and retrieval enabled by NVIDIA Spectrum-X™ Ethernet serves because the high-performance community material for RDMA-based entry to AI-native KV cache.
Storage innovators together with AIC, Cloudian, DDN, Dell Applied sciences, HPE, Hitachi Vantara, IBM, Nutanix, Pure Storage, Supermicro, VAST Knowledge and WEKA are among the many first constructing next-generation AI storage platforms with BlueField-4, which might be obtainable within the second half of 2026.
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