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.
View: Maximizing GPU Utilization with HPE Alletra Storage MP X10000