Label time_data.dat and io_time_data.dat columns by what they measure

[sbryngelson]

Description

The time_data.dat header calls its second column s/step, but the value is the fastest single RK stage, i.e. one RHS evaluation. For RK3 that is about a third of a step, so anyone reading it as a per-step time underestimates cost by about 3x. The io_time_data.dat column is also labelled s/step, but it holds the mean time of one s_save_data call.

Root cause. Since #1650, s_tvd_rk sets time_avg to the minimum wall-clock time over individual RK stages, which is the right input for the grind time (ns/gp/eq/rhs). The header written in s_save_performance_metrics was never updated.

Fix. The headers become s/rhs and s/save, and each gets a one-line comment. Columns, values and formats are unchanged. The only parser in the tree (helpers.mako, which reads the last column of the last line) is unaffected. An existing time_data.dat keeps its old header, because rows are appended.

Verification

I ran a 1-rank run of a small 2D case on a Frontier CPU compute node (GNU 12.3):

time_data.dat:
     Ranks          s/rhs   ns/gp/eq/rhs
         1     0.00137424   143.82386185
io_time_data.dat:
     Ranks         s/save
         1     0.01753200

simulation compiles with CCE 19 (CPU) and GNU 12.3. Precheck passes, apart from two test_thermochem cases that fail on the Frontier login node because they compile with the system /usr/bin/gfortran (addressed by #1943). Results do not change.

Contribution Policy

We do not accept pull requests generated primarily by AI without genuine understanding or real-world usage context.

All contributions are expected to demonstrate:

• A clear understanding of the codebase
• Alignment with product direction
• Thoughtful reasoning behind changes
• Evidence of real-world usage or hands-on experience with the problem

If these expectations are not met, we would prefer to implement the changes ourselves rather than spend time reviewing low-effort submissions.

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Acknowledgement

• I confirm this PR meets the above expectations and reflects my own understanding and real-world context.

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This PR was prepared with the assistance of an AI tool (Claude Code). We hit this while reading timings from production runs on Frontier.

PR template credit: junegunn

[Copilot]

🟡 Changes recommended

The new comments omit the maximum-across-ranks aggregation used for multi-rank timings.

1 open finding

• Clarify MPI aggregation of fastest RK-stage time · New

What changed in this PR

Updates simulation performance-file headers to accurately identify per-RHS and per-save timings.

Changes:

• Renames s/step headers to s/rhs and s/save.
• Adds comments explaining both metrics.

File	Description
src/​simulation/​m_start_up.fpp	Relabels timing columns and documents their meanings.

🧠 Review effort: Balanced

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 61.42%. Comparing base (3dc5b2f) to head (fc629c8).
⚠️ Report is 8 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #1949      +/-   ##
==========================================
- Coverage   62.64%   61.42%   -1.22%     
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  Files          86       86              
  Lines       22425    22765     +340     
  Branches     3325     3350      +25     
==========================================
- Hits        14048    13984      -64     
- Misses       6119     6321     +202     
- Partials     2258     2460     +202     

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