35 lines
1.4 KiB
Bash
35 lines
1.4 KiB
Bash
# Tunables for frank-default-large (HauhauCS Qwen3.6-27B Q8_K_P, DFlash+ngram-mod, dankclaw)
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# Runtime: llama.cpp llama-server; AMD Strix Halo (gfx1151) 96GB UMA; Ryzen AI MAX+ 395.
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MODEL_DIR=/home/dank/models
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ALIAS=frank-default-large
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HOST=0.0.0.0
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PORT=7770
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# 3 parallel slots x 200700 ctx each = 602100 total context pool.
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CTX_SIZE=602100
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PARALLEL=3
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# Spec: DFlash draft model. Bench (4k, ROCm) showed draft-dflash fastest
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# generation (20.2 t/s): DFlash+ngram 16.9, ngram-only 8.7. ngram layering
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# reduced throughput, so it is not layered in production.
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SPEC_TYPE=draft-dflash
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SPEC_DRAFT_N_MAX=8
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SPEC_NGRAM_MOD_N_MIN=48
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SPEC_NGRAM_MOD_N_MAX=64
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SPEC_NGRAM_MOD_N_MATCH=24
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# Backend device from --list-devices. ROCm wins on generation; Vulkan renders
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# DFlash spec unusable (NONE-op abort) and gen is slower on ngram (6.9 t/s).
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DEVICE=ROCm0
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# Dense model (Qwen3.6-27B, not MoE): no MoE CPU offload. Full offload.
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N_GPU_LAYERS=all
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# KV on GPU, quantized (K q8_0, V f16).
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CACHE_TYPE_K=q8_0
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CACHE_TYPE_V=f16
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# Batch sizing constrained by ROCm memory at 602100 ctx (3x200700):
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# KV ~50GB + model 29.77GB leave only ~16GB for compute graphs. The compute
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# graph scales with UBATCH, so ubatch must stay ~512; ubatch 2048 OOMs even
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# at batch 2048. Proven-fits config: batch 2048 / ubatch 512.
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# User-specified ubatch 4096 / batch 12288 is not feasible here (see bench).
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BATCH_SIZE=2048
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UBATCH_SIZE=512
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THREADS=8
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THREADS_HTTP=8
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