Changeset 9d3dc40 for doc/theses/mike_brooks_MMath/plots/ListCommon.py

Timestamp:

Jan 19, 2026, 11:38:54 AM (2 months ago)

Author:

Michael Brooks <mlbrooks@…>

Branches:

master, stuck-waitfor-destruct

Children:

79a8c2a

Parents:

5a95560

Message:

Various changes motivated by improving CFA score on len-1 queues.

No such CFA score improvement achieved. Each change helped only on stripped-down, "try to isolate an important factor" tests. Generally, the changes are benign refactorings. (Results substantiating "don't hurt" are forthcoming.)

Libcfa changes are

• move a read action from between the memory breaks to before them
• make the memory breaks conditionally excluded (default included, as before)

Harness changes are

• add width, a compiled-in number of lists to use in round-robin order; defaults to 1, which is what was happening all along
• make the analysis scripts tolerate (so far, ignore) the width column
• rename CLI arg NumNodes to Length (now NumNodes is Length * Width)
• factor core testing loops into helper function runtest
• switch to signal-based termination (and add uC++ work-around)
• put "iterator threading" into ITERS_SAVE, joining preexisting "save iter into elem's self ref"; make iterator threading conditional on iterators-active
• disable insertion loop counter and obs_*-variable declarations (and thus writes) when observation disabled
• generalize observation to work on multiple lists
• make observation and assertion-check-enabled mode work on stripped CFA list implementations like tagging-disabled
• through this observation, ensure correctness of multi-list versions

File:

• doc/theses/mike_brooks_MMath/plots/ListCommon.py (modified) (1 diff)

doc/theses/mike_brooks_MMath/plots/ListCommon.py

@@ -14 +14 @@
         timings = pd.read_csv(
             process.stdout,
-            names=['RunMoment', 'RunIdx', 'Args', 'Program', 'expt_ops_completed', 'expt_elapsed_sec', 'mean_op_dur_ns'],
+            names=['RunMoment', 'RunIdx', 'Args', 'Program', 'Width',
+                   'expt_ops_completed', 'expt_elapsed_sec', 'mean_op_dur_ns'],
             dtype={'RunMoment':       str,
                 'RunIdx':             np.int64,
                 'Args':               str,
                 'Program':            str,
+                'Width':              np.int64,
                 'expt_ops_completed': np.int64,
                 'expt_elapsed_sec':   np.float64,