Resources

Why the PRU 2500 With RTX 5090s Is the Smartest Inference Node You Can Buy Right Now

A 4× RTX 5090 PRU 2500 out-throughputs a fully optimized H100 SXM on Qwen-32B FP8 — at roughly one-tenth the cost per million tokens. The numbers, and why the chassis matters.

Corespan PRU 2500 with 8x RTX 5090 vs. an 8x B200 HGX Server

A practical capex, TCO, throughput, and utilization comparison of a Corespan PRU 2500 with 8x RTX 5090 GPUs versus an 8x B200 HGX server.

Architecture diagram showing CPU racks on the left connected through a central optical circuit switch to disaggregated GPU accelerator clusters and NVMe flash storage pools on the right, with high-speed optical interconnects carrying PCIe and RDMA traffic between the analog and digital optical domains.

From Server Silos to Resource Pooling: Why AI Infrastructure Needs a New Architecture

AI workloads have broken the fixed-server model. Resource pooling, optical switching, and PCIe over optical turn scarcity into a manageable, dynamic system.

Corespan’s Disaggregated NVMe Architecture Changes the Shape of AI Infrastructure

Corespan's disaggregated NVMe architecture delivers native PCIe Gen 5 over optics, letting hosts dynamically compose local storage from shared pools without SAN or NVMe-oF overhead.

Rack-Scale AI Inference Without the Data-Center Price Tag

Corespan pairs NVIDIA RTX PRO 6000 GPUs with DynamicXcelerator to deliver rack-scale AI inference with lower cost, higher utilization, and standard data-center deployment flexibility.