178 lines
7.4 KiB
Markdown
178 lines
7.4 KiB
Markdown
# Qwen3.8-27B UD-Q8_K_XL Speculative-Decoding Matrix
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This page records the speculative-decoding benchmark and the production
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tuning for the unsloth Qwen3.8-27B `UD-Q8_K_XL` service on Dankclaw
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(`frank-default-large`).
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## Result (applied, 2026-08-15: --spec-default)
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- Model: `Qwen3.8-27B-UD-Q8_K_XL.gguf` (29.29 GiB, bundled MTP).
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- Spec: llama.cpp **`--spec-default`** preset = **ngram-mod** (n_match 24,
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n_min 48, n_max 64). No draft model. Chosen 2026-08-15 after DSpark
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crashed under parallel load (see below).
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- **PARALLEL=2** — passes the 2x32k parallel stream test (both streams
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complete 256/256 concurrently, no crash). ngram-mod is draftless and
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parallel-safe.
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- **Backend: Vulkan0** — at 262144 ctx (~200k prompt) Vulkan decodes
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5.68 t/s vs ROCm 3.83 t/s (48% faster); ROCm only wins prefill (119 vs
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106 t/s). See the high-context bench table below.
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- Batch 8192 / ubatch 256, ctx 524288 (262144 per slot).
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## Result (superseded 2026-08-15: DSpark)
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- Model: `Qwen3.8-27B-UD-Q8_K_XL.gguf` (29.29 GiB, bundled MTP).
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- Spec: **DSpark sidecar draft** `magnitudedev/Qwen3.8-27B-DSpark-GGUF`
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(`Qwen3.8-27B-DSpark-Q8_0.gguf`, 1.36B, block_size 7), `--spec-type
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draft-dspark`, `--spec-draft-n-max 7` (clamps to block_size).
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- **PARALLEL=1.** Two concurrent 16k prose prompts crashed the ROCm backend
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with `ROCm error: an illegal memory access` during per-sequence block
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sampling. See the DSpark parallel incident below.
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- Retired the same day in favor of `--spec-default`.
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- Batch 8192 / ubatch 256, ctx 524288 (262144 per slot).
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## Result (superseded 2026-08-14: bundled MTP)
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- Model: `Qwen3.8-27B-UD-Q8_K_XL.gguf` (29.29 GiB, bundled MTP).
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- Spec: `draft-mtp`, `--spec-draft-n-max 5`, no `--spec-draft-p-min`.
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- Batch 8192 / ubatch 256, parallel 2, ctx 524288 (262144 per slot).
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- Realistic-prompt generation: ~13.3 t/s single, ~8 t/s per slot under
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2 concurrent streams. No premature stop.
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## Incident: DSpark ROCm Crash Under Parallel Load (2026-08-15)
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A two-stream parallel acceptance test crashed `frank-default-large`.
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```mermaid
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graph TD
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A[Two concurrent 16k prose prompts<br>high prompt-cache reuse] --> B[ROCm illegal memory access<br>in common_speculative_impl_draft_dflash::draft]
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B --> C[status 6/ABRT core dump]
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C --> D[systemd auto-restart, 503 during reload]
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D --> E[pinned PARALLEL=1]
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```
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Trigger: two distinct-but-overlapping ~16k-token realistic prose prompts
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started simultaneously on PARALLEL=2. The ROCm backend aborted at
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`ggml-cuda.cu:106` with `ROCm error: an illegal memory access was
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encountered`, surfacing in `hipStreamSynchronize` inside
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`common_speculative_impl_draft_dflash::draft` (the class used by
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`draft-dspark`). `systemd` caught it (status 6/ABRT) and restarted the
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unit; in-flight streams saw `Remote end closed connection without response`
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until the ~reload finished.
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Mechanism: DSpark reuses the DFlash block-diffusion draft machinery. The
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DFlash draft model uses one shared draft context (`ctx_dft`) across all
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parallel slots; under concurrent block drafting on ROCm it performs an
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illegal memory access (HIP stream sync). This is the same multi-slot
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class of bug that retired `draft-dflash` for premature EOS; here it is a
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hard ROCm crash instead of a bad sample.
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Fix: pin **PARALLEL=1** (single slot). With one slot, concurrent requests
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queue safely and each completes to `max_tokens`. Revisit after an upstream
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multi-slot DSpark fix (DSpark is known-good single-slot). Single-slot 16k
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prose generation was ~steady (measuring only the correct-size signal, not
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this page).
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## Parallel results by stream count (2026-08-15, correct-size tests)
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| Parallel | Two 16k prose prompts | Two 67k prose prompts |
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| -------- | -------------------- | --------------------- |
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| 2 | crashes (illegal mem access) | passes |
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| 1 | queues, both complete | n/a |
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Note: the crash manifests on the smaller (16k) concurrent streams, not the
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larger 67k pair. Size is not the trigger; concurrent block drafting on the
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shared draft context is.
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## How MTP works on Qwen3.8
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The unsloth `UD-*` GGUFs keep the MTP (Multi-Token Prediction) head inside
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the model file. llama.cpp b10411+ auto-detects it and creates the draft
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context from the target model. Do not pass `--spec-draft-model`.
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The stock llama.cpp build must be b10411 or newer. The 2026-08-14 rebuild
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on Dankclaw is b10433 (`9b05354ec`) with `GGML_HIP` + `gfx1151` + Vulkan.
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## Benchmark Method
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The matrix ran 54 configurations: 3 spec types (`draft-mtp,ngram-mod`,
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`draft-mtp`, `ngram-mod`) x `--spec-draft-n-max` 2..10 x
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`--spec-draft-p-min` {off, 0.8}. Each config loaded `llama-server`,
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then ran 3 generations. The tool is `scripts/spec-matrix-bench.sh`;
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analysis is `scripts/analyze-spec-matrix.py`.
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## Matrix Caveat: Benchmark Prompt
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The matrix used a repetitive 1100-token prompt
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(`scripts/bench_live.sh` style). MTP drafts that repeated sentence almost
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perfectly, which inflated the numbers for long drafts. The matrix reported
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`draft-mtp` n_max=10 at ~30 t/s. A realistic story prompt gave very
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different results:
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| n_max | median t/s (realistic) |
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| ----- | ----------------------- |
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| 4 | 12.5 |
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| 5 | 13.3 (peak) |
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| 6 | 10.6 |
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| 7 | 10.1 |
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| 10 | 8.6 |
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| none (baseline) | 7.2 |
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Long drafts collapse to ~18% acceptance on real writing. n_max=5 balances
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acceptance against draft cost.
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## Premature Stop Investigation
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Two failure patterns appeared during early production tests:
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1. Speed collapse. `ubatch >= 512` reduced MTP acceptance to ~25% and
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generation to ~9 t/s. `ubatch 128` with `batch >= 2048` triggered a
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premature instant-EOS under 2 concurrent slots. `ubatch 256` avoids
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both: ~30 t/s single, concurrent-safe.
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2. Apparent premature-EOS. The repetitive benchmark prompt with `temp 1.0`
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sometimes stops after 1-2 tokens because the model legitimately emits an
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EOS on a wall of repeated text. This is sampling variance, not a
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corruption bug. Realistic prompts never stop early.
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## High-Context Backend Comparison (2026-08-15)
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Tool: `scripts/bench-high-ctx.sh <device> <ctx>`. Both runs at ctx 262144
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with a ~200k-token realistic-prose prompt, `--spec-default`, batch 8192 /
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ubatch 256, single slot, on scratch port 7892.
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| Device | Prompt tokens | Prefill (t/s) | Generation (t/s) | Wall (single req) |
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| ------ | ------------- | ------------- | ---------------- | ----------------- |
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| ROCm0 | 202822 | **119.1** | 3.83 | **1770 s** |
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| Vulkan0 | 200235 | 106.3 | **5.68** | 1929 s |
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Verdict: at very high context, Vulkan0 decodes **48% faster** (5.68 vs
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3.83 t/s); ROCm0 prefills 12% faster. Generation is the interactive cost
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(users stream tokens), so **Vulkan0** is the production backend. Both
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`tg_3s` values were rock-steady across the run (3.83 and 5.67 t/s).
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High-context decode collapses on both backends versus ~25 t/s at 16k ctx;
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that is the long-context attention penalty, not a spec artifact.
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## Production Configuration
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`scripts/frank-default-large.env`:
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```ini
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SPEC_DEFAULT=1 # llama.cpp preset = ngram-mod (48/64/24)
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SPEC_TYPE=
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DRAFT_FILE=
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BATCH_SIZE=8192
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UBATCH_SIZE=256
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CTX_SIZE=524288
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PARALLEL=2 # passes 2x32k parallel stream test (2026-08-15)
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DEVICE=Vulkan0 # 48% faster decode at 262k ctx
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```
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Window: computed at 262144 per slot (the pi `models.json` contextWindow for
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`frank-default-large`). The unit reports `n_ctx_slot = 262144`; CTX_SIZE is
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a pool ceiling and per-slot stays 262144 regardless of the slot count.
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## See Also
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- [[frank-default-large-benchmark]]
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- [[ling-3.0-flash-trial]]
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- [[deployment]]
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