Revert "feat(p800): parameterize GLM5.2 single-node tuning"

This reverts commit ba20973beaed07e6f5ccf1be10e9a78e31d614e0.
2026-08-20 07:33:38 +00:00 · 2026-08-20 07:33:38 +00:00 · 9cdbc1fd22
commit 9cdbc1fd22
parent ba20973bea
6 changed files with 20 additions and 138 deletions
--- a/experiments/p800/glm52_w4a8_sglang_tp8_single_node/README.md
+++ b/experiments/p800/glm52_w4a8_sglang_tp8_single_node/README.md
@ -1,26 +1,11 @@
-# GLM-5.2 W4A8 P800 single-node benchmark
+# GLM-5.2 W4A8 P800 single-node smoke benchmark

- Validated hosts: `sskj-P800-2` (`gpu049`) and `sskj-P800-4` (`gpu051`)
+- Host: `sskj-P800-4` (`gpu051`)
 - Image: `iregistry.baidu-int.com/xpu/sglang-p800-pd-disagg-0510:20260715_5746`
- Default model: `/data2/glm52_deploy/models/GLM-5.2-w4a8`
+- Model: `/data2/GLM-5.2-w4a8`
 - Parallelism: TP=8, EP=8, DP=1
 - Quantization: `w4a8_int4`; KV cache: `int8`
- Default dataset: `/data2/ShareGPT_V3_unfiltered_cleaned_split.json`
+- Dataset: `/data1/wxy/sskj/datasets/ShareGPT_V3_unfiltered_cleaned_split.json`
 - Benchmark: ShareGPT, 64 prompts, concurrency 8, output length 128, request rate unlimited

 Run `bash start_glm52_w4a8.sh`, wait for `http://127.0.0.1:30000/health`, then run `bash run_bench.sh`.
-
-The launcher accepts environment overrides so that tuning runs change one
-variable at a time. Supported knobs include `CUDA_GRAPH_MAX_BS`,
-`CHUNKED_PREFILL_SIZE`, `MAX_PREFILL_TOKENS`, `MEM_FRACTION_STATIC`,
-`MAX_RUNNING_REQUESTS`, `KV_CACHE_DTYPE`, and `ENABLE_SPECULATIVE`.
-
-Run the fixed four-point tuning smoke suite with:
-
-```bash
-RUN_ID=<name> bash run_tuning_smoke.sh
-```
-
-For EAGLE/MTP, start the service with `ENABLE_SPECULATIVE=1`. The default
-speculative settings follow the vendor deployment document: 3 steps, top-k 1,
-and 4 draft tokens.
--- a/experiments/p800/glm52_w4a8_sglang_tp8_single_node/run_bench.sh
+++ b/experiments/p800/glm52_w4a8_sglang_tp8_single_node/run_bench.sh
@ -3,7 +3,7 @@ set -Eeuo pipefail

 CONTAINER="glm52-w4a8-tp8"
 PORT="${PORT:-30000}"
-RUN_DIR="/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_single_node"
+RUN_DIR="/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_smoke"
 RUN_ID="${RUN_ID:-$(date '+%Y%m%d-%H%M%S')}"
 RESULT_DIR="${RUN_DIR}/results/${RUN_ID}"
 PYTHON="/root/miniconda/envs/python310_torch25_cuda/bin/python"
--- a/experiments/p800/glm52_w4a8_sglang_tp8_single_node/run_concurrency_sweep.sh
+++ b/experiments/p800/glm52_w4a8_sglang_tp8_single_node/run_concurrency_sweep.sh
@ -3,7 +3,7 @@ set -Eeuo pipefail

 CONTAINER="glm52-w4a8-tp8"
 PORT="${PORT:-30000}"
-RUN_DIR="/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_single_node"
+RUN_DIR="/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_smoke"
 RUN_ID="${RUN_ID:-$(date '+%Y%m%d-%H%M%S')-sharegpt-sweep}"
 RESULT_DIR="${RUN_DIR}/results/${RUN_ID}"
 PYTHON="/root/miniconda/envs/python310_torch25_cuda/bin/python"
--- a/experiments/p800/glm52_w4a8_sglang_tp8_single_node/run_full_matrix.sh
+++ b/experiments/p800/glm52_w4a8_sglang_tp8_single_node/run_full_matrix.sh
@ -3,7 +3,7 @@ set -Eeuo pipefail

 CONTAINER="glm52-w4a8-tp8"
 PORT="${PORT:-30000}"
-RUN_DIR="/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_single_node"
+RUN_DIR="/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_smoke"
 REFERENCE_DIR="/data1/wxy/sskj/experiments/p800/dsv4_p800_sglang_tp_dp_matrix"
 RUN_ID="${RUN_ID:-$(date '+%Y%m%d-%H%M%S')-full-matrix}"
 RESULT_DIR="${RUN_DIR}/results/${RUN_ID}"
--- a/experiments/p800/glm52_w4a8_sglang_tp8_single_node/run_tuning_smoke.sh
+++ b/experiments/p800/glm52_w4a8_sglang_tp8_single_node/run_tuning_smoke.sh
@ -1,82 +0,0 @@
-#!/usr/bin/env bash
-set -Eeuo pipefail
-
-CONTAINER="${CONTAINER:-glm52-w4a8-tp8}"
-PORT="${PORT:-30000}"
-RUN_DIR="${RUN_DIR:-/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_single_node}"
-RUN_ID="${RUN_ID:-$(date '+%Y%m%d-%H%M%S')-tuning-smoke}"
-RESULT_DIR="${RUN_DIR}/results/${RUN_ID}"
-RAW_DIR="${RESULT_DIR}/raw_outputs"
-LOG_DIR="${RESULT_DIR}/logs"
-PYTHON="/root/miniconda/envs/python310_torch25_cuda/bin/python"
-SCENARIO_TIMEOUT_S="${SCENARIO_TIMEOUT_S:-2400}"
-
-SCENARIOS=(
-  "Y 1024 128 8 40"
-  "Y 1024 128 32 160"
-  "Y 8192 128 8 40"
-  "Y 16384 1024 1 5"
-)
-
-mkdir -p "${RAW_DIR}" "${LOG_DIR}"
-curl --fail --silent --show-error --max-time 10 "http://127.0.0.1:${PORT}/health" >/dev/null
-docker inspect "${CONTAINER}" >"${RESULT_DIR}/container_inspect.json"
-docker logs "${CONTAINER}" >"${RESULT_DIR}/server_before.log" 2>&1
-xpu-smi >"${RESULT_DIR}/xpu_before.txt"
-
-printf 'mark\tinput_len\toutput_len\tconcurrency\tnum_prompts\n' >"${RESULT_DIR}/scenarios.tsv"
-for scenario_row in "${SCENARIOS[@]}"; do
-  read -r mark isl osl concurrency num_prompts <<<"${scenario_row}"
-  printf '%s\t%s\t%s\t%s\t%s\n' "${mark}" "${isl}" "${osl}" "${concurrency}" "${num_prompts}" >>"${RESULT_DIR}/scenarios.tsv"
-done
-
-for scenario_row in "${SCENARIOS[@]}"; do
-  read -r mark isl osl concurrency num_prompts <<<"${scenario_row}"
-  scenario="c${concurrency}_i${isl}_o${osl}"
-  started="$(date +%s)"
-  bench_rc=0
-  echo "start ${scenario} prompts=${num_prompts}"
-  timeout "${SCENARIO_TIMEOUT_S}" docker exec "${CONTAINER}" env \
-    HF_HUB_OFFLINE=1 TRANSFORMERS_OFFLINE=1 HF_DATASETS_OFFLINE=1 \
-    "${PYTHON}" -m sglang.bench_serving \
-    --backend sglang \
-    --host 127.0.0.1 \
-    --port "${PORT}" \
-    --dataset-name random \
-    --dataset-path /workspace/ShareGPT_V3_unfiltered_cleaned_split.json \
-    --model /models \
-    --served-model-name GLM-5.2-w4a8 \
-    --tokenizer /models \
-    --random-input-len "${isl}" \
-    --random-output-len "${osl}" \
-    --random-range-ratio 1.0 \
-    --num-prompts "${num_prompts}" \
-    --max-concurrency "${concurrency}" \
-    --request-rate 10000 \
-    --seed 1 \
-    --flush-cache \
-    --output-file "/workspace/run/results/${RUN_ID}/raw_outputs/${scenario}.jsonl" \
-    --output-details \
-    >"${LOG_DIR}/${scenario}.log" 2>&1 || bench_rc=$?
-  duration=$(( $(date +%s) - started ))
-  if [[ "${bench_rc}" -eq 0 ]]; then
-    printf 'completed\trc=0\tduration_s=%s\n' "${duration}" >"${LOG_DIR}/${scenario}.status"
-  else
-    printf 'failed\trc=%s\tduration_s=%s\n' "${bench_rc}" "${duration}" >"${LOG_DIR}/${scenario}.status"
-  fi
-  echo "finish ${scenario} rc=${bench_rc} duration_s=${duration}"
-  if [[ "${bench_rc}" -ne 0 ]]; then
-    docker logs --tail 300 "${CONTAINER}" >"${LOG_DIR}/${scenario}.server_tail.log" 2>&1 || true
-    exit "${bench_rc}"
-  fi
-done
-
-python3 "${RUN_DIR}/summarize_matrix.py" \
-  --scenarios "${RESULT_DIR}/scenarios.tsv" \
-  --raw-dir "${RAW_DIR}" \
-  --log-dir "${LOG_DIR}" \
-  --output "${RESULT_DIR}/summary.tsv"
-
-docker logs "${CONTAINER}" >"${RESULT_DIR}/server_after.log" 2>&1
-xpu-smi >"${RESULT_DIR}/xpu_after.txt"
-echo "tuning_smoke_complete result_dir=${RESULT_DIR}"
--- a/experiments/p800/glm52_w4a8_sglang_tp8_single_node/start_glm52_w4a8.sh
+++ b/experiments/p800/glm52_w4a8_sglang_tp8_single_node/start_glm52_w4a8.sh
@ -1,32 +1,12 @@
 #!/usr/bin/env bash
 set -Eeuo pipefail

-IMAGE="${IMAGE:-iregistry.baidu-int.com/xpu/sglang-p800-pd-disagg-0510:20260715_5746}"
-MODEL_DIR="${MODEL_DIR:-/data2/glm52_deploy/models/GLM-5.2-w4a8}"
-DATASET="${DATASET:-/data2/ShareGPT_V3_unfiltered_cleaned_split.json}"
-RUN_DIR="${RUN_DIR:-/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_single_node}"
-CONTAINER="${CONTAINER:-glm52-w4a8-tp8}"
+IMAGE="iregistry.baidu-int.com/xpu/sglang-p800-pd-disagg-0510:20260715_5746"
+MODEL_DIR="/data2/GLM-5.2-w4a8"
+DATASET="/data1/wxy/sskj/datasets/ShareGPT_V3_unfiltered_cleaned_split.json"
+RUN_DIR="/data1/wxy/sskj/experiments/p800/glm52_w4a8_sglang_tp8_smoke"
+CONTAINER="glm52-w4a8-tp8"
 PORT="${PORT:-30000}"
-CHUNKED_PREFILL_SIZE="${CHUNKED_PREFILL_SIZE:-32768}"
-MAX_PREFILL_TOKENS="${MAX_PREFILL_TOKENS:-32768}"
-MEM_FRACTION_STATIC="${MEM_FRACTION_STATIC:-0.82}"
-MAX_RUNNING_REQUESTS="${MAX_RUNNING_REQUESTS:-64}"
-CUDA_GRAPH_MAX_BS="${CUDA_GRAPH_MAX_BS:-8}"
-KV_CACHE_DTYPE="${KV_CACHE_DTYPE:-int8}"
-ENABLE_SPECULATIVE="${ENABLE_SPECULATIVE:-0}"
-SPECULATIVE_NUM_STEPS="${SPECULATIVE_NUM_STEPS:-3}"
-SPECULATIVE_EAGLE_TOPK="${SPECULATIVE_EAGLE_TOPK:-1}"
-SPECULATIVE_NUM_DRAFT_TOKENS="${SPECULATIVE_NUM_DRAFT_TOKENS:-4}"
-
-SPECULATIVE_ARGS=()
-if [[ "${ENABLE_SPECULATIVE}" == "1" ]]; then
-  SPECULATIVE_ARGS+=(
-    --speculative-algorithm EAGLE
-    --speculative-num-steps "${SPECULATIVE_NUM_STEPS}"
-    --speculative-eagle-topk "${SPECULATIVE_EAGLE_TOPK}"
-    --speculative-num-draft-tokens "${SPECULATIVE_NUM_DRAFT_TOKENS}"
-  )
-fi

 test -f "${MODEL_DIR}/config.json"
 test -f "${DATASET}"
@ -64,23 +44,22 @@ docker run -d \
    --trust-remote-code \
    --disable-custom-all-reduce \
    --disable-shared-experts-fusion \
-    --chunked-prefill-size ${CHUNKED_PREFILL_SIZE} \
+    --chunked-prefill-size 32768 \
    --page-size 64 \
-    --mem-fraction-static ${MEM_FRACTION_STATIC} \
-    --max-prefill-tokens ${MAX_PREFILL_TOKENS} \
-    --max-running-requests ${MAX_RUNNING_REQUESTS} \
+    --mem-fraction-static 0.82 \
+    --max-prefill-tokens 32768 \
+    --max-running-requests 64 \
    --tp-size 8 \
    --ep-size 8 \
    --quantization w4a8_int4 \
-    --kv-cache-dtype ${KV_CACHE_DTYPE} \
-    --cuda-graph-max-bs ${CUDA_GRAPH_MAX_BS} \
+    --kv-cache-dtype int8 \
+    --cuda-graph-max-bs 8 \
    --disable-cuda-graph-padding \
    --watchdog-timeout 3000000 \
    --tool-call-parser glm47 \
    --reasoning-parser glm45 \
    --json-model-override-args '{\"index_topk_freq\": 4}' \
    --allow-auto-truncate \
-    --enable-metrics \
-    ${SPECULATIVE_ARGS[*]}"
+    --enable-metrics"

-echo "container=${CONTAINER} port=${PORT} speculative=${ENABLE_SPECULATIVE} graph_bs=${CUDA_GRAPH_MAX_BS} chunk=${CHUNKED_PREFILL_SIZE} max_prefill=${MAX_PREFILL_TOKENS} mem_fraction=${MEM_FRACTION_STATIC}"
+echo "container=${CONTAINER} port=${PORT}"