fb_scroll_rows() hardcoded the pixel distance it physically shifts the framebuffer by as char_rows * 16 * scale -- the bitmap-font (font_8x16.c) cell height -- regardless of which glyph mode vt100.c actually had active. In TTF mode (the REPL's default, cell height 24px via VT100_TTF_CELL_H_PX) this meant every scroll_up(1) call physically shifted the framebuffer by only 16px while the text model (g_vt.rows, py_of()) placed each row 24px apart. That 8px-per-scroll shortfall compounds with every subsequent scroll: a few scrolls barely show it, but enough scrolls -- or scrolling quickly, which is just many scrolls in a short span -- accumulates into visible pixel overlap between rows, with newer lines drawn on top of the tail end of older ones. fb_scroll_rect() (the box-confined scroll added later for 4.4t) already carried a doc comment calling this out explicitly, describing its own explicit pixel_rows parameter as the fix for fb_scroll_rows()'s "fixed 16px-row assumption" -- fb_scroll_rows() itself was just never updated to match. Fixed by changing fb_scroll_rows()'s parameter from an implicit char_rows count to an explicit pixel_rows count (matching fb_scroll_rect()'s existing convention), and having its one caller (vt100.c's scroll_up()) pass lines * cell_h() -- the real active cell height -- instead of a raw line count for the callee to guess at. Verified: booted amd64 to the REPL (TTF mode active per sk_repl()'s own console_fb_enable_ttf() call), let boot chatter + WORDS output scroll the screen through thousands of accumulated scroll_up() calls, then measured every visible line's y-position via a QMP screendump. Spacing held at a perfectly consistent 24px (TTF cell height) top to bottom with zero drift -- the old hardcoded-16px bug could not have produced that after this many scrolls. Re-verified boot to ok> on all three architectures (amd64/aarch64/riscv64) per repo acceptance policy. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Bare-Metal DoE Experiment
This directory holds data and analysis from the LithosAnanke kernel's Design of Experiments (DoE) runs — blind full-factorial 2⁴ experiments that measure the L8 Jacquard mode selector's effect on the Steady-State Machine across all three supported architectures (amd64, aarch64, riscv64).
Directory Layout
experiments/bare_metal/
├── runs/ ← timestamped canonical CSVs from every acceptance run
├── latest/ ← arch-named copies of the most recent run (human-readable)
│ ├── amd64.csv
│ ├── aarch64.csv
│ └── riscv64.csv
└── analysis/
├── charts/ ← generated SVG/PNG charts
├── report/ ← timestamped LaTeX / Markdown reports
└── tables/ ← generated summary tables
runs/ is the canonical archive. latest/ is the eyeball-friendly shortcut
— always the most recent run per architecture, overwritten on each new run.
Running the DoE
The DoE runs automatically when the kernel boots because init.4th calls it.
The standard acceptance command runs all three architectures sequentially:
make -f Makefile.starkernel ARCH=amd64 clean qemu
make -f Makefile.starkernel ARCH=aarch64 clean qemu
make -f Makefile.starkernel ARCH=riscv64 clean qemu
Each run executes 48 trials (16 L8 configs × 3 reps, Fisher-Yates shuffled), captures ~1.27 million heartbeat rows per architecture, and writes two files:
| File | Path |
|---|---|
| Timestamped canonical CSV | experiments/bare_metal/runs/doe-<arch>-<YYYYMMDD-HHMMSS>.csv |
| Latest convenience copy | experiments/bare_metal/latest/<arch>.csv |
Run architectures sequentially, never in parallel. All three QEMU
instances use accel=tcg (software emulation). Concurrent runs compete for
host CPU and corrupt the timing signal that the DoE is measuring.
Disabling the DoE
To boot into the REPL without running the experiment, comment out the last
two lines of capsules/init.4th:
Block 2049
( first init.4th )
: STAR 42 EMIT ;
: STARS 0 DO STAR LOOP ;
: MARGIN 30 SPACES ;
: BAR MARGIN 5 STARS CR ;
: BLIP MARGIN STAR CR ;
: F CR BAR BLIP BAR BLIP BLIP CR ;
( S" Hermes" BIRTH )
( S" Artemis" BIRTH )
( S" doe.4th" EXEC ) ← comment this out
( 123456 3 L8-DOE ) ← comment this out
The kernel will boot to the ok> REPL with no experiment running.
Commenting both lines leaves doe.4th unloaded so none of its words
(L8-DOE, WL-NAME, etc.) are defined, which is the cleanest state for
interactive sessions.
Changing the Seed and Rep Count
The DoE entry point is L8-DOE ( seed reps -- ).
The call in init.4th is:
123456 3 L8-DOE
-
Seed — any non-zero integer. The same seed always produces the same shuffled run order, so results are reproducible. Change the seed to explore a different permutation; different seeds are statistically equivalent but verify shuffle-independence.
-
Reps — trials per L8 configuration (1–200). 3 reps × 16 configs = 48 runs, which takes roughly 25–30 minutes per architecture under TCG. Increase for higher statistical power; decrease for quick smoke checks.
( quick smoke check — 1 rep, 16 runs total )
42 1 L8-DOE
( full study — 10 reps, 160 runs )
987654 10 L8-DOE
What Are Capsules?
A capsule is a named blob of FORTH-79 source text stored in capsules/.
The kernel's EXEC word loads a capsule by filename and interprets it as
FORTH source. BIRTH (commented out in init.4th) would instead spawn an
isolated child VM whose sole personality is that capsule's code.
There are two roles:
| Role | Who uses it | What it does |
|---|---|---|
| Init capsule | Mama VM at boot | Defines the VM's vocabulary and behavior |
| Workload capsule | DoE machinery | Provides a computational task to time |
init.4th is the Mama VM's init capsule — executed exactly once at kernel
boot. The numbered files (init-0.4th … init-9.4th) and the L8 variant
files (init-l8-*.4th) are workload capsules used by the DoE.
.4th File Structure
Every .4th file must follow StarForth's block format. The block system
maps source text to 1024-byte logical blocks; the Block NNNN header tells
the loader which block slot to fill.
Mandatory rules:
- The first line of each logical block must be
Block NNNN(capital B, single space, decimal integer). - Block numbers must be unique within a single capsule file.
- Blocks are loaded in file order and executed top-to-bottom.
- Each block can hold up to 1024 bytes of source text.
- Comments use
( ... )— parentheses with spaces inside. - Word definitions use
: NAME ... ;— standard FORTH-79.
Minimal capsule skeleton:
Block 3100
( My capsule description )
: MY-WORD ( -- )
42 . CR ;
MY-WORD
Multi-block capsule:
Block 3100
( Block 1: helpers )
: HELPER ( n -- n*2 ) 2 * ;
Block 3101
( Block 2: main logic )
: MAIN ( -- )
10 0 DO I HELPER . CR LOOP ;
MAIN
The block number namespace is shared across all loaded capsules. Convention used in this repository:
| Range | Contents |
|---|---|
| 2048–2099 | init.4th (Mama VM boot sequence) |
| 2100–2199 | doe.4th (DoE machinery) |
| 3000–3999 | Workload capsules (init-0 … init-9, init-l8-*) |
| 4000+ | User-defined capsules |
Adding a Custom Workload Capsule
Step 1 — Create the file.
Add capsules/my-workload.4th using block numbers in the 4000+ range:
Block 4000
( my-workload.4th - description of what this measures )
: MY-COMPUTE ( n -- )
0 SWAP 0 DO I 3 * + LOOP DROP ;
Block 4001
( main entry point )
: RUN-MY-WORKLOAD ( -- )
500 0 DO I MY-COMPUTE LOOP ;
RUN-MY-WORKLOAD
The last line should execute the workload so EXEC runs it immediately when
the capsule is loaded.
Step 2 — Wire it into the DoE.
Open capsules/doe.4th and add your capsule to the workload dispatch table.
Find WL-HI (Block 2057) and replace one of the existing entries, or extend
the range:
Block 2057
: WL-HI ( n -- c-addr u )
CASE
0 OF S" init-8.4th" ENDOF
1 OF S" init-9.4th" ENDOF
2 OF S" init-l8-diverse.4th" ENDOF
3 OF S" init-l8-omni.4th" ENDOF
4 OF S" init-l8-stable.4th" ENDOF
5 OF S" init-l8-temporal.4th" ENDOF
6 OF S" init-l8-transition.4th" ENDOF
7 OF S" my-workload.4th" ENDOF ← replace slot 7
DROP S" init-0.4th"
ENDCASE ;
There are 16 workload slots total (0–7 in WL-LO, 0–7 in WL-HI).
The DoE machinery picks workloads blindly from these slots — your capsule
will appear in the shuffled run matrix alongside the built-in workloads.
Step 3 — Run the experiment.
make -f Makefile.starkernel ARCH=amd64 clean qemu
Your workload's heartbeat rows will appear in the CSV under whatever
CURR-WL index maps to my-workload.4th. Match by the DOE-RUN marker
lines in the CSV:
DOE-RUN,run_id,cfg,wl_id,rep
CSV Format
Each row emitted by the [HADES][DOE ] serial tag is one heartbeat tick
during a workload execution. Extract with:
grep -aP '\[HADES\]\[DOE \]' logs2/qemu-amd64-<timestamp>.log \
| sed 's/.*\[DOE \] //' > my.csv
Columns (15 total):
| # | Name | Type | Description |
|---|---|---|---|
| 1 | tick_number |
uint32 | Monotonic heartbeat counter |
| 2 | elapsed_ns |
uint64 | Nanoseconds since run start |
| 3 | tick_interval_ns |
uint64 | Interval from prior tick |
| 4 | cache_hits_delta |
uint32 | Hot-words cache hits this tick |
| 5 | bucket_hits_delta |
uint32 | Bucket hits this tick |
| 6 | word_executions_delta |
uint32 | Words executed this tick |
| 7 | hot_word_count |
uint64 | Words with heat ≥ threshold |
| 8 | avg_word_heat_q48 |
uint64 | Mean heat (raw Q48.16 integer) |
| 9 | window_width |
uint32 | L8's target rolling window size |
| 10 | actual_window_size |
uint32 | True analysis width: min(total_executions, window_width) |
| 11 | predicted_label_hits |
uint32 | ANOVA early-exit confirmations (L8 validation signal) |
| 12 | jitter_bits |
uint64 | Estimated jitter (IEEE 754 bit pattern) |
| 13 | apic_ticks |
uint64 | APIC timer monotonic count |
| 14 | time_trust_q48 |
uint64 | Time-trust score (Q48.16) |
| 15 | variance_q48 |
uint64 | Timing variance (Q48.16) |
avg_word_heat_q48 is a raw fixed-point integer. To convert to a human-readable
heat value: avg_word_heat = avg_word_heat_q48 / 65536.0.
jitter_bits is the IEEE 754 double-precision bit pattern of the jitter in
nanoseconds. In R: readBin(as.raw(…), "double"). In Python:
struct.unpack('d', struct.pack('Q', n))[0].
Interpreting predicted_label_hits
This column is the feedback-loop closure signal.
Each non-zero value means the inference engine ran ANOVA on the current execution window and confirmed the L8 selector's config choice correlated with the subsequent execution pattern — an "early exit" because the statistical test converged without needing all data.
- High rate → L8 chose well; the system settled quickly into a stable regime.
- Low rate → L8 is still searching; the workload is novel or transient.
- Zero throughout → The workload ended before the inference engine had enough data, or the window is too small to trigger ANOVA.
This is the metric that closes the loop between "L8 made a choice" and "that choice was actually validated by what the VM did next."