Enable DFlash speculative decoding, remove mlock

- Add --spec-type draft-dflash (was missing, DFlash was inactive)
- Change --load-mode from mlock to none (RLIMIT_MEMLOCK too small for 2.7GB)
- Increase validation max_tokens from 256 to 1024 with complex ML prompt
- Baseline: 18.76 tok/s (was 7.62 tok/s without DFlash)
This commit is contained in:
Frank committed 2026-08-07 16:10:55 -07:00
1 parent 1949f0651b
commit 25d57184a6
3 files changed
+5 -4

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+1 -1
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@@ -6,7 +6,7 @@ After=network.target
Type=simple Type=simple
User=dank User=dank
Group=dank Group=dank
ExecStart=/home/dank/llama.cpp/build/bin/llama-server --hf-repo unsloth/Qwen3.6-27B-MTP-GGUF:Q8_0 --spec-draft-hf Alittlehammmer/Qwen3.6-27B-DFlash-GGUF-llama.cpp:Q8_0 --spec-draft-n-max 16 --device ROCm0 --spec-draft-device ROCm0 --gpu-layers all --fit on --fit-target 512 --parallel 3 --ctx-size 131072 --batch-size 4096 --port 8080 --host 0.0.0.0 --threads 16 --load-mode mlock ExecStart=/home/dank/llama.cpp/build/bin/llama-server --hf-repo unsloth/Qwen3.6-27B-MTP-GGUF:Q8_0 --spec-draft-hf Alittlehammmer/Qwen3.6-27B-DFlash-GGUF-llama.cpp:Q8_0 --spec-type draft-dflash --spec-draft-n-max 16 --device ROCm0 --spec-draft-device ROCm0 --gpu-layers all --fit on --fit-target 512 --parallel 3 --ctx-size 131072 --batch-size 4096 --port 8080 --host 0.0.0.0 --threads 16 --load-mode none
Restart=on-failure Restart=on-failure
RestartSec=10 RestartSec=10
+2 -1
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@@ -26,6 +26,7 @@ echo ""
exec "${SERVER_BIN}" \ exec "${SERVER_BIN}" \
--hf-repo "${TARGET_REPO}" \ --hf-repo "${TARGET_REPO}" \
--spec-draft-hf "${DRAFT_REPO}" \ --spec-draft-hf "${DRAFT_REPO}" \
--spec-type draft-dflash \
--spec-draft-n-max "${DRAFT_N_MAX}" \ --spec-draft-n-max "${DRAFT_N_MAX}" \
--device ROCm0 \ --device ROCm0 \
--spec-draft-device ROCm0 \ --spec-draft-device ROCm0 \
@@ -38,4 +39,4 @@ exec "${SERVER_BIN}" \
--port "${PORT}" \ --port "${PORT}" \
--host "0.0.0.0" \ --host "0.0.0.0" \
--threads 16 \ --threads 16 \
--load-mode mlock --load-mode none
+2 -2
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@@ -5,7 +5,7 @@ set -euo pipefail
PORT="${LLAMA_PORT:-8080}" PORT="${LLAMA_PORT:-8080}"
HOST="${LLAMA_HOST:-127.0.0.1}" HOST="${LLAMA_HOST:-127.0.0.1}"
MAX_TOKENS="${MAX_TOKENS:-256}" MAX_TOKENS="${MAX_TOKENS:-1024}"
echo "=== llama.cpp Validation Test ===" echo "=== llama.cpp Validation Test ==="
echo "Target: http://${HOST}:${PORT}" echo "Target: http://${HOST}:${PORT}"
@@ -36,7 +36,7 @@ RESPONSE=$(curl -s \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-d "{ -d "{
\"messages\": [ \"messages\": [
{\"role\": \"user\", \"content\": \"What is 2+2? Answer in one sentence.\"} {\"role\": \"user\", \"content\": \"Explain the difference between supervised, unsupervised, and reinforcement learning in machine learning. For each type, provide a concrete real-world example, describe the training process, and discuss the advantages and limitations. Then compare them across three dimensions: data requirements, interpretability of results, and computational cost. Finally, describe a hybrid scenario where combining two of these approaches would outperform using either alone.\"}
], ],
\"max_tokens\": ${MAX_TOKENS}, \"max_tokens\": ${MAX_TOKENS},
\"temperature\": 0.7, \"temperature\": 0.7,