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32 Commits

Author SHA1 Message Date
JustVugg a5fc89e88f README: Strix Halo warm numbers (#39) — 0.16 -> 0.40 tok/s in five runs, learned pin 47.6 GB, fastest non-Apple datapoint 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-11 01:25:59 +02:00
JustVugg ae8975a009 README: Strix Halo + Optane 905p datapoint (#39) — first Ryzen AI Max+, Optane latency invisible to 19MB-chunk reads 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-11 00:13:56 +02:00
JustVugg c809bc8260 README: 9950X disk-swap datapoint (#31) — same machine, P3 vs 9100 PRO: x5.8 disk = x2.9 tokens, profile flips 66% disk -> 57% matmul 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-11 00:01:56 +02:00
ZacharyZcR 9e6e1ac327 Isolated sequence KV contexts: KVState extraction, KV_SLOTS serve contexts with per-slot persistence, budget-aware pool accounting (#29) 
* Add isolated sequence KV contexts

* Log projected multi-slot KV footprint
 2026-07-10 16:19:43 +02:00
ZacharyZcR 76e858a80f Bounded FIFO inference scheduling: admission queue, OpenAI-shaped 429/503, queued-disconnect detection (#28) 2026-07-10 12:52:07 +02:00
ZacharyZcR 3cbc52ab00 coli plan: read-only Disk/RAM/VRAM placement planner (mirrors engine budget math, versioned --json, --auto-tier) (#27) 
* Add tiered resource planner

* Apply resource plans to runner configuration

---------

Co-authored-by: JustVugg <JustVugg@users.noreply.github.com>
 2026-07-10 12:51:23 +02:00
ZacharyZcR 1453dab7ae REPIN follows live session heat (decaying heat map; .coli_usage stays the persistent signal) + disk→RAM→VRAM promotion (#26) 2026-07-10 12:48:53 +02:00
ZacharyZcR 3e4d08b6bf OpenAI-compatible HTTP API: stdlib-only gateway over SERVE with KV prefix reuse across stateless requests (#21) 
* Add OpenAI-compatible HTTP API

* Support browser API clients

* Handle missing KV cache during rewind
 2026-07-10 11:04:56 +02:00
JustVugg 1a909f3833 README: catch up with the last two days — DSA is done (was 'in progress'), KV persistence, PILOT, web/ UI section + repo layout, honest line count 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-10 10:12:40 +02:00
ZacharyZcR 13e8f09ffc Organize project tools and local workflows: c/tools, c/scripts, c/tests, root Makefile (flat C core untouched) (#22) 2026-07-10 10:08:39 +02:00
JustVugg 8f99e12b5e KV-to-disk: conversations reopen WARM across engine restarts (.coli_kv, KVSAVE=0 opts out) 
serve mode persists the compressed MLA KV-cache incrementally after every
turn (~182 KB/token appended, header count written last = crash-safe) and
resumes it at startup: the model remembers the whole conversation and zero
re-prefill happens. :reset and context-full restarts truncate the file.
The MTP layer's KV row is not saved; kv_start=-1 re-arms its decode window.

Validated: split-session answer byte-identical to an uninterrupted session
(tiny oracle, TEMP=0), and on the real 744B model a restarted chat resumed
58 tokens in 0.0s and recalled a fact from the previous session while
prefilling only the new question.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-10 10:00:19 +02:00
JustVugg 99111993a4 README: Framework 13 warm numbers (0.37 tok/s, hit 66%, MTP 52% — #12), int8-MTP mirror clone link (#2), Epyc row column fix 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-10 07:46:18 +02:00
JustVugg 077894210e LOOKA: routing predictability counters; PILOT: router-lookahead disk prefetch (async I/O thread); cap auto-raise to RAM budget (#12) 
Measured on GLM-5.2 (48 tok, greedy): next-layer routing is 71.6% predictable
one full layer ahead (79.4% skipping attention only; 41.3% previous-token).
PILOT=1 issues next-layer expert WILLNEED from a dedicated I/O thread while
the current layer computes — inline fadvise BLOCKS ~0.5ms/call on a saturated
disk queue (+92s/48 tok, measured), hence the lock-free ring + worker.
Neutral-in-noise on this dev box (disk already ~80% duty); expected to pay on
balanced machines (#12: 43% disk / 46% matmul) — opt-in, default off.

cap_for_ram now RAISES the LRU cap up to the RAM budget (ceiling n_experts,
CAP_RAISE=0 opt-out): big-RAM machines were silently running with cap=8
(#12: 128GB box using 22GB of a 110GB budget; #13: 92GB box, same).

DRAFT=3 on cold cache measured locally: 1399s vs 880s baseline for the same
48 tokens (acceptance 16%, experts/token 1809 vs 800) — confirms #8; DRAFT
re-evaluation belongs to warm-cache serve sessions.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-10 07:44:26 +02:00
ZacharyZcR 57706a0200 Tiered CUDA acceleration for routed experts (opt-in, CPU default untouched) + REPLAY fixture harness (#16) 
* feat: add experimental CUDA backend for resident tensors

* feat: promote pinned experts to a bounded VRAM tier

* feat: preload the GPU expert tier at startup

* fix: harden CUDA backend failure handling

* feat: add deterministic multi-GPU tensor placement

* test: add deterministic CUDA benchmark fixture

* perf: make routed experts the default CUDA path
 2026-07-10 07:41:09 +02:00
adapt-L 4ea9ddc0f0 README: community benchmark — Epyc 9654 ES, PCIe3 NVMe (0.31 tok/s, hit 35%) (#17) 
I think I am just disk bandwidth limited, CPU's are at like 65% average. Might consider upgrading to 4x PCIe5 x4 ssds...
 2026-07-10 07:41:06 +02:00
JustVugg ed3916b0bb README: accurate SSD note (reads don't wear the drive; swap + thermals are the real concerns) 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-10 01:39:50 +02:00
JustVugg c035f41778 MTP head is int8 by default (int4 head: 0-4% acceptance, unusable — measured in #8); README: honest MTP numbers + M5 Max community datapoint (#4, #5) 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-09 20:34:08 +02:00
DatPat 996ae0e3cd README: add measured community benchmark (WSL2, 24 GB RAM — issue #2) (#3) 
First real datapoint for the 'Got a better machine?' section: disk iobench
plus stock and --topp 0.7 inference numbers, with the RAM-bound takeaway.

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
 2026-07-08 10:20:37 +02:00
Vincenzo 4319dfdf91 Add model download huggingface section to README 
Added download instructions for the GLM-5.2 int4 model on Hugging Face.
 2026-07-08 08:42:44 +02:00
JustVugg 492c3b6f63 Revert "coli: multi-model registry + picker (coli models / chat menu); README: MoE-only model roadmap (gpt-oss-120b next)" 
This reverts commit 289befb0fd.
 2026-07-07 13:03:07 +02:00
JustVugg 289befb0fd coli: multi-model registry + picker (coli models / chat menu); README: MoE-only model roadmap (gpt-oss-120b next) 
Each architecture maps to its own engine binary (glm today; gptoss, qwenmoe
reserved). Registry in c/models.json (local, gitignored); chat shows a picker
when more than one model is installed. Dense models stay llama.cpp territory
- documented honestly in the README.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-07 12:59:56 +02:00
JustVugg b71d3884f6 coli bench: self-contained (venv python + auto-fetch datasets); README calls for a quality run on faster hardware 
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
 2026-07-07 07:29:52 +02:00
JustVugg 8d7fbef39c README: today's engine work (integer kernels, MLA absorption, readahead, sampling, DSA status) 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-06 20:24:18 +02:00
JustVugg 34fb900762 README: honest matmul-bound predictions (GFLOP math), updated sampling defaults 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-06 19:40:27 +02:00
JustVugg b2855c0da1 coli convert: one command does model + MTP head; README documents the full zero-to-chat path 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-06 16:59:27 +02:00
Vincenzo 8e8d5fb02b Update README.md 2026-07-05 23:22:23 +02:00
Vincenzo ea27cd77fb Update README.md 2026-07-05 23:18:00 +02:00
Vincenzo 1e33e9b17d Update README.md 2026-07-05 23:16:58 +02:00
JustVugg 31d91b2c5b README: TUI pixel-art hummingbird as SVG logo banner 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-05 21:15:09 +02:00
JustVugg 20008742bf README: try-it-on-better-hardware guide + predictions + support section; drop stage-0 research scripts from repo 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-05 21:02:46 +02:00
JustVugg 1ae22a6135 colibrì: pure-C GLM-5.2 (744B MoE) engine with disk-streamed experts 
Engine (c/glm.c): MLA attention with compressed KV, sigmoid noaux_tc router,
int8/int4/int2 quant kernels (AVX2), per-layer LRU expert cache + pinned
hot-store, batch-union MoE, native MTP speculative decoding (lossless),
multi-stop + official chat template, RAM auto-budget from MemAvailable.
Tokenizer: byte-level BPE in C. Tooling: coli CLI, disk-safe FP8→int4
converter, tiny-random oracle validation (TF 32/32, greedy 20/20).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-05 20:57:25 +02:00
Vincenzo a6deef8e44 Initial commit 2026-07-01 14:27:49 +02:00