GPU nodes and pools
Represent accelerator capacity by node, pool, capability and location.
GPU & AI · accelerator infrastructure
Operate accelerators as a governed cloud estate.
Register GPU nodes and pools across sites with the storage, network, health and allocation context needed to deliver them as customer services.
- Estate
- GPU-first
- Accelerators as native capacity
- Pools
- Capability-aware
- Grouped by service eligibility
- Context
- Complete
- Storage and network included
- Reach
- Multi-site
- Location retained
Scope
The infrastructure model behind a GPU cloud.
Accelerators become schedulable and sellable only when their dependencies and operational state are explicit.
Storage context
Connect data services required by training and inference workloads.
Network context
Keep workload connectivity and eligible network services visible.
Health and allocation
See what is healthy, available, reserved and consumed.
Operating workflow
Turn installed accelerators into controlled capacity.
The estate is classified before customer services are published.
- 01
Register nodes
Discover accelerator and host capacity.
- 02
Build pools
Group resources by capability, site and purpose.
- 03
Attach dependencies
Connect storage, network and image eligibility.
- 04
Expose selectively
Make approved pools available to service definitions.
Two connected responsibilities
Operator control and customer action stay explicit.
What GPU operations control
- Node and accelerator lifecycle
- Pool membership and capability
- Health, reservations and availability
- Site and dependency context
What cloud services inherit
- Accurate accelerator choices
- Eligible location and pool
- Storage and network compatibility
- Capacity-backed availability
Operational outcome
What this changes in the working model.
One GPU estate
Accelerators across sites share an operating model.
Service-ready context
Dependencies travel with capacity into delivery.
Commercial visibility
Allocation can be tied to tenant and plan.
Continue in this section
Partner with us
Map your accelerator estate into a GPU cloud.
We will map nodes, pools, sites and dependencies into the LayerOne capacity model.