Frank
8212d4451a
Mechanical identity rename across the knowledge base, AGENTS.md, README, the
hermes config example, and homepage services.json. No behavior change; served
aliases on the LLM endpoints change with the deploy of commit 69f87c8.
120 lines
5.8 KiB
Markdown
120 lines
5.8 KiB
Markdown
> **SUPERSEDED 2026-08-17.** The Frank redo retired this topology.
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> See [frank-redo-2026-08-17.md](frank-redo-2026-08-17.md) and
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> [deployment.md](deployment.md) for the active configuration.
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# frank-large — Backend and Spec Benchmark
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This page records the benchmarks that chose the runtime for
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`frank-large` on Dankclaw. Every number came from the live
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llama.cpp build on that machine (upstream, b10133+).
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## Summary
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- **Backend**: **Vulkan0** (2026-08-15). At 262k ctx Vulkan decodes 48%
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faster than ROCm (5.68 vs 3.83 t/s); ROCm only wins prefill 119 vs 106
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t/s. Generation is the interactive cost, so Vulkan0.
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- **Spec (2026-08-15)**: llama.cpp `--spec-default` preset (ngram-mod,
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n_match 24 / n_min 48 / n_max 64, draftless). Replaced DSpark, which
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crashed the ROCm backend under two concurrent 16k prompts (see
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[[qwen3.8-spec-matrix]]).
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- **Parallel**: 2 slots — passes the 2x32k parallel stream test.
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- **Context**: 2 slots x 262144.
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- **KV**: `q8_0` K / `q8_0` V on GPU.
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- **Batch**: 8192 / ubatch 256.
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> The A/B tables below are retained for history but predate the 2026-08-14
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> Qwen3.8-27B `UD-Q8_K_XL` switch. The current production spec decision,
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> the DSpark parallel crash, and the high-context ROCm-vs-Vulkan bench are
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> recorded on [[qwen3.8-spec-matrix]].
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## 2026-08-14: Spec A/B (ROCm, production config, default sampling, 1.1k-token prompt)
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| Spec | Generation (t/s) | Parallel-safe |
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| ---- | ---------------- | -------------- |
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| DFlash (draft-dflash, n_max 8) | ~20.2 (from earlier 4k bench) | **NO** - premature EOS |
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| MTP (draft-mtp, n_max 3) | **15.3 - 19.5** | YES |
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| MTP + ngram-mod (n_max 3) | 12.0 - 13.6 | YES |
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| MTP (draft-mtp, n_max 2) | 12.4 - 14.3 | YES |
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| ngram-mod | 6.7 - 8.7 | YES |
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Verdict: `draft-mtp` at `n_max 3` is the winner. It nearly matches DFlash's speed, beats ngram-mod by ~2x, and does not exhibit the DFlash parallel bug. Layering ngram under MTP (12-13.6 t/s) does not pay off, the same result as layering ngram under DFlash.
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## Incident: DFlash Premature EOS Under Parallel Load (2026-08-14)
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Reproduced three times by the user. When a new task lands on a slot with high prompt-cache reuse (LCP similarity ~0.99, `f_keep` ~0.98) while another slot is generating, the generating slot is released ~1 second later with `finish_reason "stop"` and a truncated response. The client records it as a normal completion (no abort). Server log shows a `slot release` with `truncated = 0` and no `cancel task` line.
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Mechanism: DFlash's draft model uses one shared draft context (`ctx_dft`) across all parallel slots. When the new task's first DFlash draft pass runs after a large prompt-reuse operation, it corrupts the generating slot's draft state, and the target spuriously samples the EOG token. Known class of bug upstream (`server : do not default to multiple slots with speculative decoding`, PR #17017; DFlash multi-slot routing fixes in the beellama.cpp fork).
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Fix: switch away from DFlash. ngram-mod (draftless) and MTP (separate draft machinery) both pass the strict parallel test. MTP was chosen for speed.
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## Backend Comparison (llama-bench, raw target model, no draft)
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Both backends ran the same target model at 64k context in `llama-bench`
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(`-p 65536 -n 256`).
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| Device | Prefill 64k (t/s) | Generation 64k (t/s) |
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| -------- | ----------------- | -------------------- |
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| ROCm0 | 220.28 | 6.99 |
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| Vulkan0 | 72.34 | 7.00 |
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ROCm prefills 3x faster. Generation is a tie in the raw benchmark.
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## Full-Pipeline Comparison (4k context, real served chain)
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These used `bench-pipeline-64k.sh` driving `llama-server` through the API at
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4k context, reading the server's own `print_timing` lines.
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| Spec | Backend | Prefill (t/s) | Generation (t/s) | Draft acceptance |
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| --------------------------- | ------- | ------------- | ---------------- | ---------------- |
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| `draft-dflash` | ROCm | 148.2 | **20.17** | 0.50 |
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| `draft-dflash,ngram-mod` | ROCm | 149.9 | 16.93 | 0.42 |
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| `ngram-mod` | ROCm | 154.0 | 8.68 | 0.57 |
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| `ngram-mod` | Vulkan | 259.6 | 6.90 | 0.17 |
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### Interpretation
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- DFlash alone gives the fastest generation on ROCm (20.17 t/s).
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- Layering ngram-mod lowered ROCm generation (16.93 t/s), so it is not
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layered in production. llama.cpp *can* layer DFlash + ngram
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(`--spec-type draft-dflash,ngram-mod`), but it was slower here.
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- Vulkan only works without the DFlash draft. The DFlash `ctx_other`
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setup aborts the Vulkan backend (`ggml-backend.cpp:898: pre-allocated
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tensor ... cannot run the operation (NONE)`). Vulkan ngram generation is
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also slowest (6.90 t/s) with poor acceptance (0.17).
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**Verdict: ROCm + `draft-dflash`.**
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## Memory Constraint at 602100 Context
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At `3 x 200700` context the KV cache alone is ~50 GB and the model is
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29.77 GB, leaving only ~16 GB of the ~96 GB ROCm allocation for compute
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graphs. The compute graph scales with **ubatch**, so:
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- batch 12288 / ubatch 4096 -> OOM (80.7 GB prefill buffer)
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- batch 6144 / ubatch 2048 -> OOM (40.9 GB prefill buffer)
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- batch 2048 / ubatch 2048 -> OOM (ubatch 2048 too large)
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- batch 2048 / ubatch 512 -> **fits and loads**
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The requested batch 12288 / ubatch 4096 is not feasible at this context
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size on this hardware.
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## Command to Reproduce
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Raw backend bench (ROCm shown; swap `-dev` for the other):
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```
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llama-bench -m <main>.gguf -p 65536 -n 256 -c 65536 -dev ROCm0 -r 1
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```
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Full-pipeline bench:
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```
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./scripts/bench-pipeline-64k.sh ROCm0 draft-dflash
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```
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## See Also
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- [[deployment]] — deploy and update process
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- [[DFlash DSpark Speculative Decoding]] — DFlash / DSpark / layering details
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- [[index]] — knowledge base index
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