Corespan 5090 Inference System
High-density AI inference with 8 to 12 NVIDIA GeForce RTX 5090 GPUs, hybrid liquid cooling, composable PCIe Gen5 architecture, and Docker/Kubernetes-native deployment.
Built for Inference Economics
The Corespan 5090 Inference System combines the PRU 2500, 8 to 12 NVIDIA GeForce RTX 5090 GPUs, hybrid liquid cooling, FIC 2500 connectivity, and Corespan software into a dense, composable platform for AI inference. Instead of binding GPUs to fixed servers, it turns them into a shared resource pool that can be dynamically assigned to standard hosts and consumed through familiar Docker and Kubernetes workflows. Built for neo-cloud providers and enterprise AI environments, the system is designed to improve GPU utilization, reduce stranded capacity, and simplify deployment of high-density inference infrastructure.
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Key Features
High-Density GPU Pooling
Pack 8 to 12 RTX 5090 GPUs into a single PRU 2500 for dense, shared accelerator capacity built for inference-heavy environments.
Hybrid Liquid Cooling
Direct-to-chip liquid cooling on the GPUs helps manage dense thermal loads while avoiding the complexity of full immersion infrastructure.
Composable PCIe Gen5 Architecture
Dynamically attach and reassign GPUs to hosts as workloads change, improving utilization and reducing idle accelerator capacity.
Docker and Kubernetes Native
Expose GPUs to standard container and Kubernetes environments with familiar NVIDIA tooling and existing operational models.
Use Cases
Neo-Cloud GPU Services
Deliver GPU-as-a-Service with higher utilization and more flexible tenant allocation from a shared GPU pool.
Enterprise AI Inference
Support shared inference infrastructure across teams, applications, and changing workload demand.
Elastic Multi-Tenancy
Scale from smaller inference endpoints to larger multi-GPU jobs on the same physical platform.
Burstable GPU Capacity
Recompose GPUs between hosts and workloads in real time as jobs begin, finish, and shift.

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Reduce waste, boost performance, and scale smarter.