Frank
193034fdb8
0.55 measured: 36 blocks (0-35) -> 9th FA block, KV 9216 MiB, cudaMalloc OOM by ~740 MiB, crash loop. Exact GGUF math: layer pool 27720 MB + MTP head; split assigns blocks while cumulative <= fraction x pool; cum(34)= 53.83%, cum(35)=55.31%. 0.54 lands 35 blocks (0-34), 8 FA layers, KV 8192 MiB, ~0.66 GiB free.
83 lines
3.1 KiB
Bash
83 lines
3.1 KiB
Bash
# Head tunables — Qwen3.8-27B pipeline-parallel head (Dankclaw).
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#
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# The head is the LOCAL side of the split. It runs llama-server (b10433,
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# HIP+Vulkan+RPC build in /home/dank/llama.cpp/build) with --rpc pointing at
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# the worker on Dankserver. The model file lives on this machine only; the
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# worker receives its tensor share over the network at load time.
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#
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# CRITICAL: this script must NOT pass --device. When --device is set,
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# llama.cpp uses exactly that device list and silently drops the RPC device
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# (src/llama.cpp llama_prepare_model_devices). Default device selection
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# inserts RPC servers at the FRONT of the device list, so the split becomes
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# [RPC0, iGPU] and --tensor-split index 0 is the worker.
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#
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# WARNING: do not name any variable here TEMP, HOST, or GPU_MAX_HEAP_SIZE
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# (HIP runtime collision, see the 2026-08-13 TEMP incident).
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MODEL_DIR=/home/dank/models
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MODEL_FILE=Qwen3.8-27B-UD-Q8_K_XL.gguf
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HEAD_BIN=/home/dank/llama.cpp/build/bin/llama-server
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ALIAS=frank-default-large
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BIND_ADDR=0.0.0.0
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LISTEN_PORT=7770
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# Comma-separated RPC endpoints (host:port). One worker here.
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RPC_SERVERS=192.168.0.235:50052
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# Model split fractions, one per device in order [RPC0, iGPU].
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# 0.54,0.46 = 35 of 65 blocks on the 3090 (blocks 0-34) - the maximum.
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# Split math (exact GGUF sizes, 2026-08-17): layer pool 27720 MB + MTP
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# head; llama.cpp assigns RPC0 the blocks while cumulative weight <= the
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# fraction of the pool. cum(34) = 53.83%, cum(35) = 55.31%. Measured:
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# 0.50 -> 32 blocks, 0.55 -> 36 blocks (9th FA block 35 -> KV 9216 MiB
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# -> cudaMalloc OOM by ~740 MiB). FA blocks at 3,7,...,63; KV stays
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# 8192 MiB (8 FA) at 35 blocks. Predicted free ~0.65 GiB.
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TENSOR_SPLIT=0.54,0.46
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# Context pool. 262144 total = 1 parallel slot x 262144 per slot
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# (n_ctx_seq = n_ctx / n_seq_max, llama-context.cpp:293).
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CTX_SIZE=262144
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PARALLEL=1
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# Speculative decoding. Matches production frank-default-large: MTP (bundled
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# head, n_max 4 per the published tuning curve) with the ngram-mod fallback.
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# Set SPEC_NONE=1 for a raw baseline with no speculation.
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SPEC_NONE=0
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SPEC_DEFAULT=1
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MTP=1
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SPEC_DRAFT_N_MAX=4
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# Optional standalone MTP draft head (e.g. the Q4_0 ggml-org file). When set,
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# it replaces the bundled in-model head via --spec-draft-model.
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SPEC_DRAFT_MODEL=
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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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# KV on GPU, unquantized (f16). 16 full-attention layers x 2 (K,V) x 4 heads
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# x 256 dim x 2 bytes = 64 KiB/token -> 262144 tokens = 16.6 GiB total,
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# held in proportion to the full-attention layers each device holds.
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# Keep K == V so Flash Attention stays enabled.
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CACHE_TYPE_K=f16
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CACHE_TYPE_V=f16
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# Batch sizing: production-verified values (2026-08-14).
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BATCH_SIZE=8192
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UBATCH_SIZE=256
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# Sampling — Qwen3.8 thinking-mode defaults.
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TEMPERATURE=1.0
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TOP_K=20
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TOP_P=0.95
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MIN_P=0.0
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THREADS=12
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THREADS_HTTP=1
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# 4 (info): clean journal for interactive use. Raise to 10 only when
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# debugging the layer split (the per-layer assignment lines are debug-level).
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VERBOSITY=4
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# 1: --direct-io model load. Required in practice for large models loaded
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# over RPC (load hangs otherwise; visorcraft Strix RPC finding).
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DIRECT_IO=1
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