Robert Allan JamesandClaude Sonnet 5
934be5a257
Correlates every HB-ON/HB-OFF heartbeat-tick CSV row (results-20260912- with-heartbeat-csv/*-doe-raw.log) back to which trial (run_id, id_idx, id_label, rep) was active when it printed, despite the async tick printer splicing rows mid-token -- including mid a DOE-RUN marker itself -- into the trial loop's own console output on the shared serial line. Pipeline (analysis-20260912/, see its own README.md): - correlate_doe.py: two-pass reconstruction per architecture (remove atomic CSV-row spans to rebuild the clean trial-output stream, map each removed row's offset back to the nearest preceding run_id marker); identity/rep looked up from a known-clean prior run's run_id mapping rather than re-parsed, since one aarch64 marker (trial 12, rajames rep 1) lost its id_idx digit to a zero-separator collision with an adjacent CSV field and is unrecoverable from that log alone -- its rows fold into trial 11 instead, documented as a known limitation. - combine.py: merges all three architectures into combined.csv (768 rows), decoding Q48.16 fields to floats and jitter_bits' IEEE754 bit pattern to real jitter_ns. - analysis.R: per-cell (architecture x identity) means/SD and two-way ANOVA for each of 12 telemetry metrics, one boxplot SVG per metric, written up as ANALYSIS.md. Key findings: identity significantly affects word-heat/window-sizing metrics (expected -- different identities execute different word sets), architecture significantly affects timing metrics (APIC ticks/tick, timing variance, fleet heat -- expected, different QEMU targets), zero architecture x identity interaction on any metric. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EXieurDfDSsDFdnSyusuWo
std79-doe 3×9 factorial analysis (heartbeat/physics telemetry)
Read ANALYSIS.md for the report itself (key findings, per-metric cell means,
two-way ANOVA tables, boxplot SVGs). This file just documents the pipeline.
Pipeline
-
Source data:
../results-20260912-with-heartbeat-csv/{amd64,aarch64,riscv64}-doe-raw.log— raw QEMU serial logs from theHB-ON/HB-OFF-instrumented std79 DoE campaign (see../README.mdand FABRIC-3.md §XV/§XVI/§XVII for the campaign itself). -
correlate_doe.py <raw_log> <out_csv>— reconstructs which DoE trial (run_id,id_idx,id_label,rep) was active for every heartbeat-tick CSV row, despite the async tick printer splicing rows mid-token into the trial loop's own console output on the shared serial line (see the script's own docstring for the two-pass reconstruction method, and itsRUN_ID_MAPfor why identity/rep are looked up from a known-clean prior run rather than re-parsed from each log — one aarch64 marker was unrecoverable, see below). Run once per architecture:python3 correlate_doe.py ../results-20260912-with-heartbeat-csv/amd64-doe-raw.log amd64-correlated.csv python3 correlate_doe.py ../results-20260912-with-heartbeat-csv/aarch64-doe-raw.log aarch64-correlated.csv python3 correlate_doe.py ../results-20260912-with-heartbeat-csv/riscv64-doe-raw.log riscv64-correlated.csv -
combine.py <in1.csv> [in2.csv ...] <out.csv>— merges the three per-architecture correlated CSVs intocombined.csv(committed, 768 rows), decoding Q48.16 fixed-point fields to plain floats andjitter_bits' raw IEEE754 bit pattern to a realjitter_nsvalue:python3 combine.py amd64-correlated.csv aarch64-correlated.csv riscv64-correlated.csv combined.csv -
analysis.R(run from this directory) — readscombined.csv, computes per-cell (architecture × identity) summary statistics and a two-way ANOVA for each of the 12 varying telemetry metrics, renders one boxplot SVG per metric tosvg/, and writesANALYSIS.md:Rscript analysis.RRequires
dplyr,tidyr,ggplot2,svglite(all present in this environment already).
Known limitation
aarch64's raw log lost 1 of 27 DOE-RUN markers to interleaving beyond
recovery — trial 12 (identity rajames, rep 1). Its rows fold into trial 11
(identity rajames, rep 0) in combined.csv, so aarch64's rajames cell
isn't perfectly separable between those two replicates specifically. Every
other cell, on every architecture, is unaffected — see ANALYSIS.md's own
note and correlate_doe.py's docstring for the full explanation.