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NOVA IMS DAH Business Intelligence Database-backed board view for SSSD users and GPU resource accounting.
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Tracked cluster Loading database nodes
Compute estate Loading GPU inventory
Data source MariaDB production telemetry
Billing rate Loading
Billable GiB-hours - VRAM multiplied by runtime
Estimated charge - Uses database billing rate
GPU compute hours - One row equals one active minute
Active users - Network identities with VRAM allocation
VRAM Allocation Timeline Average GiB allocated by user over the selected range.
Node Share GiB-hours by server inventory.
User Cost Ranking Computed from GiB-hours using the database billing rate.
Runtime by Server Compute hours grouped from database server records.
Compute Hours & VRAM Intensity by Researcher Compare total runtime and cumulative GiB-Hours per network account.
Accounting Model The TXT converges on normalized MariaDB storage and kernel-level ownership.
01 NVML process sampling

GPU memory is captured at PID level and grouped per GPU every minute.

02 SSSD username resolution

The PID owner UID is mapped back to the network username through NSS.

03 Normalized fact table

Users and servers are upserted once, then history rows store server, user, GPU and VRAM bytes.

04 Board metric

GiB-hours combines memory footprint and runtime, then applies the configured database rate.

Node Inventory GPU nodes observed in the production database.
Per-User Billing Audit User, server and memory used by hour.
CSV
User Server GPU Model Hours Avg VRAM Peak VRAM GiB-hours Charge
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