Huawei officially releases the full-stack AI DC data infrastructure solution, with OceanStor Pacific all-flash distributed storage reaching 11PB/2U, high density, lower TCO, supporting massive data processing. For ultra-large-scale inference clusters, a heterogeneous computing power context memory storage CMS is introduced, supporting KV semantic passthrough or DPU offloading, scalable to PB-level shared KV Cache pools, with the first token latency reduced by 90%. Aiming at enterprise AI inference, a 3+1 AI data platform is proposed, integrating a knowledge base with approximately 95% retrieval accuracy, KV Cache acceleration, and a continuously evolving memory database, managed by UCM, with inference accuracy improved by about 30%.

MarsBitNews

2026-05-22 06:03:48

Abstract generation in progress

Mars Finance News: On May 22, Huawei officially released the AI DC data infrastructure full-stack solution. The OceanStor Pacific all-flash distributed storage, with 11PB/2U industry-leading high capacity density, achieves optimal TCO for storing massive data. For ultra-large-scale inference cluster scenarios, Huawei launched the industry's first context memory storage CMS (Context Memory Storage) supporting heterogeneous computing power, supporting direct semantic access for KV or semantic offloading using dedicated DPU, scalable to PB-level shared KV Cache pools, reducing inference first token latency by 90%. For enterprise AI inference scenarios, Huawei pioneered the "3+1" AI data platform, integrating a knowledge base with over 95% retrieval accuracy, KV Cache acceleration, and a continuously evolving memory library, managed and scheduled by UCM technology, improving inference accuracy by 30%. (Wide-angle observation)

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ColdBrewYield

· 3h ago

Huawei's full-stack solution this time, integrating storage and computing context, further advances domestic substitution.

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GateUser-8ca669fd

· 3h ago

The 95% retrieval accuracy of the 3+1 platform should help enterprises avoid many pitfalls during implementation.

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YieldYeti

· 4h ago

KV Cache pooling sharing, multi-GPU inference efficiency can be significantly improved.

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PineNeedlesAndColdWind

· 4h ago

DPU offloads KV semantics, hardware-level optimization, detail enthusiasts rejoice

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MevTeaTime

· 4h ago

The company's reasoning accuracy has increased by 30%, and the implementation ROI is now justifiable.

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OldKeyboardTraitor

· 4h ago

The point about the memory bank continuously evolving feels like it's building long-term memory.

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0xSideQuest

· 4h ago

Waiting to see actual deployment cases, the technical parameters look good, but engineering implementation is the real challenge.

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NekoOnCall

· 4h ago

OceanStor Pacific sounds powerful just by the name, all-flash + distributed, a performance beast

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NeonVortexTunnel

· 4h ago

Managing context in ultra-large-scale clusters has always been a pain point; CMS is a targeted solution.

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Frost-ColoredCubeCity

· 4h ago

From training to inference, full-chain coverage, Huawei's AI infrastructure has big ambitions

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