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Comparing Jobs
The Compare tab puts two jobs side by side: a metrics table with the change between them, and an overlaid chart with a selector for CPU efficiency, memory, or process and thread counts.
The pickers list every discovered job, including running jobs and jobs whose state is unknown. The comparison needs a merged whole-run summary for each job; a still-running job normally has no summary yet. If either summary is missing, the tab says which one.
Efficiency going from 37% to 58% reports +21.3pp, not "+57%".
Those are different claims. "+57%" is the relative change and sounds like a transformation; "+21.3 percentage points" is what actually happened. The tab uses points for anything already expressed as a percentage, and relative change only for absolute quantities like core-hours.
A change from a zero baseline has no meaningful relative percentage, so the table shows the absolute difference instead of an infinite percentage.
Both lines are drawn from elapsed time, not wall-clock time, so runs days apart line up at zero. A shorter run's line simply stops where it ended rather than being bridged across time the job did not run.
The two series are resampled onto a shared grid. Merging their timestamps instead would leave each line with gaps wherever the other job happened to have a sample, which renders as dots rather than lines.
The chart has a Time window menu and zoom controls. Like the job charts, its sample series is bounded in memory, so a very long run may show only its recent portion. The metrics table still uses the complete merged summaries.
The tab tells you what makes a pair hard to compare rather than declaring a winner:
- different core or node counts
- different job names
- different queues
- missing or partly reported nodes in either run
- a non-zero or unrecorded exit status
It cannot know the two runs did the same work. A lower total may just mean less of it — a job that crashed at hour two will look wonderfully cheap.
That is the whole reason it does not pick a winner. The comparison is a tool for you to reason with, not a verdict.
The useful pairs are ones where you changed one thing:
- the same case at two core counts, to see whether it scales
- the same case before and after a code change
- the same case on two queues or two node types
Comparing two unrelated jobs will produce numbers, and they will not mean much.
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