Reorganize source tree: kernel/, v3/, v4/ split and board infrastructure

Source tree reorganization:
- Move StarForth v3 engine to v3/ (src/, include/, Makefile)
- Move kernel to kernel/ (src/, include/, linker/, Makefile)
- Create v4/ skeleton for F18-ISA golden model (DECOMPOSITION.md, JUSTIFICATION.md)
- Move FABRIC-0..4.md to docs/fabric/
- Move ONTOLOGY.md and ROADMAP.md to docs/

Board infrastructure:
- Add boards/ser5/, boards/raspi/, boards/milkv/, boards/zynq7020/
- Each board has board.mk (ISA, CPU flags, boot recipe) and README.md
- Root Makefile becomes thin dispatcher: boot_image, all, clean, docs take TARGET
- make boot_image TARGET=SER5|RASPI|MILKV builds one GPT/MBR image per board
- ZYNQ7020 target exists but stops with clear error (ARMv7 port not built yet)
- scripts/mkdiskimage.sh builds disk images for all boards

Docs pipeline:
- docs/book/ with LaTeX master (main.tex) and Makefile
- pandoc converts Markdown to LaTeX at build time
- Two Lua filters: table-widths.lua (wide tables wrap), code-breaks.lua (inline code breaks)
- make docs builds single PDF (754 pages, 0 missing characters)
- make docs TARGET=<board> adds board appendix
- build/docs/<book|board>/meta.tex stamps git commit into PDF

Bug fixes:
- 42 include paths that only worked by accident now use correct relative paths
- clang-18 hardcode replaced with configurable CC variable (fixed aarch64 build)
- Pi 5: kernel_2712.img linked at 0x80000, .bss zeroed, memory reserved
- Doxyfile, .clang-tidy, README.md, Kconfig paths updated

Verified:
- Hosted v3 build passes 1012 tests, 0 failures
- SER5 image boots in QEMU (OVMF), POST passes, K exact (65536 = Q48_ONE)
- Milk-V image boots in QEMU (OpenSBI + U-Boot + bootefi), POST passes
- make clean TARGET=<board> removes only that board and its ISA objects
- make all builds all boards, hosted v3, and docs in one run

Co-authored-by: Junie <junie@jetbrains.com>
This commit is contained in:
rajames
2026-10-01 15:40:09 -04:00
co-authored by Junie
parent 3c709c115b
commit a8b70e88d3
630 changed files with 2646 additions and 2036 deletions
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/*
StarForth — Steady-State Virtual Machine Runtime
Copyright (c) 2023–2025 Robert A. James
All rights reserved.
This file is part of the StarForth project.
Licensed under the StarForth License, Version 1.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at:
https://github.com/star.4th@proton.me/StarForth/LICENSE.txt
This software is provided "AS IS", WITHOUT WARRANTY OF ANY KIND,
express or implied, including but not limited to the warranties of
merchantability, fitness for a particular purpose, and noninfringement.
See the License for the specific language governing permissions and
limitations under the License.
StarForth — Steady-State Virtual Machine Runtime
Copyright (c) 2023–2025 Robert A. James
All rights reserved.
This file is part of the StarForth project.
Licensed under the StarForth License, Version 1.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at:
https://github.com/star.4th@proton.me/StarForth/LICENSE.txt
This software is provided "AS IS", WITHOUT WARRANTY OF ANY KIND,
express or implied, including but not limited to the warranties of
merchantability, fitness for a particular purpose, and noninfringement.
See the License for the specific language governing permissions and
limitations under the License.
*/
/*
*** StarForth ***
dictionary_heat_optimization.h - Phase 2: Heat-Aware Dictionary Lookup
Inference-driven optimizations for dictionary lookup based on execution heat
patterns from the Rolling Window of Truth:
1. Heat percentile thresholds (25th, 50th, 75th)
2. Bucket reorganization by co-execution patterns
3. Heat-aware lookup strategy (search hot words first)
*/
#ifndef DICTIONARY_HEAT_OPTIMIZATION_H
#define DICTIONARY_HEAT_OPTIMIZATION_H
#include "vm.h"
/**
* @brief Calculate heat percentile thresholds for all words in dictionary
*
* Computes 25th, 50th, 75th percentiles of execution_heat across all
* dictionary entries. Used to partition lookup search order.
*/
void dict_update_heat_percentiles(VM *vm);
/**
* @brief Reorganize dictionary buckets by inference-driven priorities
*
* Uses rolling window co-execution patterns to reorder words within buckets.
* Hot/frequently co-executing words are placed first for faster lookup.
*/
void dict_reorganize_buckets_by_heat(VM *vm);
/**
* @brief Find word with heat-aware search strategy
*
* Instead of newest-first, searches buckets in order:
* 1. Top 25% by heat (likely hits)
* 2. Middle 50% by heat
* 3. Bottom 25% (rarely executed)
*/
DictEntry *dict_find_word_heat_aware(VM *vm, const char *name, size_t len);
/**
* @brief Periodically reoptimize dictionary based on latest heat patterns
*
* Called every ~1 second or every N executions to adapt lookup strategy
* to current workload patterns from rolling window.
*/
void dict_adaptive_optimization_pass(VM *vm);
/* Frequency-class (fc) buckets — shared between dictionary_management.c and
dictionary_heat_optimization.c. Declared here once to give LTO a single
canonical type definition and avoid -Werror=lto-type-mismatch. */
#ifndef SF_FC_BUCKETS
#define SF_FC_BUCKETS 256
#endif
extern DictEntry **sf_fc_list[SF_FC_BUCKETS];
extern size_t sf_fc_count[SF_FC_BUCKETS];
extern size_t sf_fc_cap[SF_FC_BUCKETS];
#endif /* DICTIONARY_HEAT_OPTIMIZATION_H */