YieldPowr™ brings GPU condition, job and recovery records together. It tests whether developing performance or fault risk can be seen early enough to change a maintenance, workload-placement, warranty or replacement decision. It measures useful work against current practice and keeps a dated record of the warning and what happened next.
When a GPU slows or faults mid-job, you pay twice: for the hours lost since the last checkpoint, and for the hours spent recovering. YieldPowr tests whether that loss was visible in time to act — and counts what acting would have cost, too.
Most fleets already log GPU errors, job failures and restarts — in separate systems, read after the fact. YieldPowr lines them up so a developing problem shows up before the next job lands on it.
GPU condition and error records, joined to job, scheduler, checkpoint and recovery history.
For each warning: what we saw, how sure we are, and how long there is to decide — maintain, move the workload, file a warranty claim, or replace. The operator stays in control.
The warning and recommendation are dated, what was known at the time is preserved, and the later outcome is added. When the data cannot support a call, the record says “cannot assess.”
A GPU can be “up” all month and still waste a share of its hours on work that never finishes. Goodput counts only the hours that produced accepted output.
Shape only — not measured on any fleet. The real split is what the pilot measures on your records.
Goodput is compute time that produces completed, accepted workload output.
YieldPowr’s evaluation compares goodput with your current diagnostics, scheduling and recovery practice. It counts the cost of false alerts and unnecessary action as well as the work that might be protected.
The economic result depends on the workload, the contracts, and who bears the loss — owner, operator or tenant. A theoretical gap in fleet capacity is not a savings claim, and we will not present it as one.
Every warning becomes a dated entry: what was seen, what was recommended, and — later — what actually happened. That is what makes a warranty claim or a replacement request stand up.
The pilot reviews historical records and then watches live recommendations in shadow mode. It needs approved data access — no new hardware and no automatic GPU control.
Read access to the GPU, job, scheduler, checkpoint and recovery records you already keep.
Replay past records: could the losses that happened have been seen in time to act, and at what false-alert cost?
Recommendations are issued and dated but not acted on automatically. Outcomes are recorded as they happen.
A supported verdict, with the basis for any later deployment on a defined GPU group.
Warn early, give the operator the choice, keep the record — applied to the compute inside the hall as well as the power equipment around it.
Runway per power asset — when it crosses end of life, and why.
Act now, or what waiting costs — the intervention window with its record.
What breaks, when, why, and what to do — across the facility.
A data-led pilot on records you already keep. You get a go, no-go or cannot-assess answer — and the record behind it.
