供应商更新：WEKA.pdf

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1、 WEKA 2026WEKA UpdateHPC User Forum May 2026 Bob VassarSr.Systems Engineer,Federal WEKA 2026NeuralMesh one parallel filesystem,every workloadParallel filesystem for HPC simulation,AI training,inference,and data lake same software,same namespace.HPC SimulationMPI scratch checkpoint/restart post-proce

2、ssingStreamlined read&write paths.Direct client-to-drive on large I/O.Parallel parity writes for checkpoint throughput.Sub-file parallelism,automatic.Large files distributed across servers at extent boundaries no manual striping.AI TrainingGPU pipelines checkpoints at scaleDistributed metadata at sc

3、ale.Millions of small-file reads/sec without metadata bottlenecks.Keeps GPU pipelines fed.Checkpoint throughput at line rate.Large sequential writes streamed in parallel out of the critical path.AI InferenceModel serving RAG retrieval KV-cache extensionToken-level latency,persistent context.Microsec

4、ond-class data path.KV-cache extension via Augmented Memory Grid.Cost-efficient TTFT.Reuse KV-cache across sessions instead of recomputing prefill on every long context.Data LakeAnalytics shared data S3 mixed POSIX+objectOne namespace,every protocol.POSIX,S3,NFS,SMB same data,no copies.Compute,query

5、,archive concurrent.Same data accessible to compute,analytics,and archive workflows simultaneously.NeuralMesh by WEKA one parallel filesystem,every workloadUserspace kernel bypass client Distributed metadata Single namespace across POSIX,NFS,SMB,S3Same software on enterprise x86 or ARM+NVMe,WEKApod

6、appliance,and natively on AWS,Azure,GCP,OCI2 WEKA 2026Three deployment options same softwarePick the one that matches your hardware reality.NeuralMesh architecture is identical across all three.NeuralMesh AxonConverged on GPU serversWHAT IT ISNeuralMesh runs in containers on Compute servers themselv