Maximizing GPU Utilization with HPE Alletra Storage MP X10000

If you're serving large language models at scale, this week's HPE content on Signal65's testing of HPE Alletra Storage MP X10000 is worth your time. You'll see how moving KV-cache off GPUs and system memory to HPE Alletra Storage MP X10000 can reimagine GPU efficiency for real-world, multi-turn workloads. In Signal65 and Kamiwaza's tests, using HPE Alletra Storage MP X10000 as a secondary KV-cache delivered significant improvements in GPU efficiency. You'll also learn how GPU Direct Storage, NVIDIA BlueField-3 DPUs, and HPE Alletra's scale-out object architecture help you support more concurrent sessions per GPU, stabilize latency under load, and improve cost per token--often instead of buying more GPUs. As your HPE Partner, we can help you assess your current GPU utilization, model your KV-cache demands, and design an Alletra Storage MP X10000 deployment that fits your AI roadmap. Contact us to learn more and get started with HPE Alletra Storage MP solutions.

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