This document describes the data models that power a compute allocation management system. The system manages how projects receive, track, and consume compute resources (GPUs, CPUs, etc.) across clusters, with full auditability and fine-grained access control.
The central abstraction is the Service Unit (SU) — a common currency that normalizes heterogeneous resources (GPU hours, CPU hours, etc.) into a single comparable unit.
A User belongs to an Organization and is identified by name and email. Users interact with the system in two roles:
Project.ProjectPIID who owns and is responsible for a project.ComputeAllocationMembership, granting them permission to submit jobs against that allocation's SU budget.A Project groups one or more compute allocations (and, in the future, storage allocations) under a single umbrella. Projects carry an Origination field indicating the source system (ACCESS, NAIRR, XRASS, etc.) and a corresponding OriginatedID for cross-referencing.
A ComputeCluster represents a physical or logical cluster where resources are provisioned.
A ComputeAllocation is the primary record linking a project to a cluster. It captures:
ComputeClusterID).InitialSUAmount) that covers all resource types within the allocation.StartTime / EndTime).ACTIVE, INACTIVE, DELETED).A single project can bundle multiple compute allocations — for example, one allocation on Cluster A with GPU resources and another on Cluster B with CPU resources.
ComputeAllocationResource represents a specific type of computing unit available within a cluster — for example, “GPU B200”, “GPU RTX6000”, or “CPU”. Each resource records its type and the quantity allocated.
Resources are linked to allocations through ComputeAllocationResourceMapping, which is a many-to-many join: a single allocation can include multiple resource types, and the same resource definition can appear across allocations.
ComputeAllocationResourceRate defines the SU conversion rate for a given resource over a time window. This is the mechanism that normalizes raw resource consumption into the common SU currency. For example:
| Resource | Rate | Meaning |
|---|---|---|
| GPU H200 | 10.0 | 10 GPU-hours = 1 SU |
| CPU | 100.0 | 100 CPU-hours = 1 SU |
| GPU RTX6000 | 20.0 | 20 GPU-hours = 1 SU |
Rates are time-bounded (StartTime / EndTime), allowing rates to change over time without losing historical accuracy.
All modifications to a compute allocation are captured as ComputeAllocationDiff records, providing a complete audit trail. A diff records what changed (SU amount, status, etc.), when it changed, and why.
Diffs are created through two paths:
User-initiated changes: A user submits a ComputeAllocationChangeRequest (e.g., requesting additional SUs or a status change). A resource provider admin reviews the request, and upon approval, a corresponding ComputeAllocationDiff is generated for the target allocation. The request carries a lifecycle of its own (PENDING → APPROVED / REJECTED), tracked through ComputeAllocationChangeRequestEvent records.
Automated workflows: Systems such as ACCESS AIME can create ComputeAllocationDiff records directly, bypassing the change request flow. This supports programmatic adjustments like periodic SU top-ups or automatic deactivation.
ComputeAllocationUsage tracks resource consumption at the most granular level — per job, per user, per resource type. Each record captures both the raw amount consumed (e.g., 20 GPU-hours) and the equivalent SU cost (calculated using the effective rate at CalculatedTime).
Aggregating all ComputeAllocationUsage records for a given allocation yields the total SU consumption, which can be compared against the allocation's SU budget to determine remaining balance.
ComputeAllocationMembership controls which users can submit jobs against an allocation. Each membership has its own validity window and status, independent of the parent allocation.
By default, members of an allocation inherit access to the full SU pool. However, administrators can enforce per-user caps by setting the AllocationAmount field on a membership record. This partitions a large allocation across members — for example, giving one researcher 500 SUs and another 300 SUs out of a 1,000 SU allocation — preventing any single user from exhausting the shared budget.
Allocation state can be controlled from three independent levels:
| Level | Controlled By | Effect |
|---|---|---|
| Project | Project status / PI actions | Disabling a project disables all its allocations. |
| Allocation | ComputeAllocation.Status | An individual allocation can be deactivated independently. |
| User | ComputeAllocationMembership.MembershipStatus | A specific user's access can be revoked without affecting the allocation or other members. |
This layered approach provides flexibility: an admin can freeze an entire project, pause a single allocation, or remove one user's access — each without disturbing the other levels.
| Model | Purpose |
|---|---|
Organization | Groups users under an institution. |
User | A person who can be a PI or allocation member. |
Project | Bundles allocations; linked to an origination system. |
ComputeCluster | A cluster where resources are provisioned. |
ComputeAllocation | SU budget for a project on a specific cluster. |
ComputeAllocationResource | A specific resource type (GPU model, CPU, etc.). |
ComputeAllocationResourceMapping | Links resources to allocations (many-to-many). |
ComputeAllocationResourceRate | SU conversion rate for a resource, time-bounded. |
ComputeAllocationDiff | Audit record of any change to an allocation. |
ComputeAllocationChangeRequest | User-submitted request to modify an allocation. |
ComputeAllocationChangeRequestEvent | Lifecycle events on a change request. |
ComputeAllocationUsage | Per-job, per-user resource consumption record. |
ComputeAllocationMembership | User access to an allocation, with optional SU cap. |