Add code long-context attention profiling grid

runs/frontier-code-trace-v0/run_flashattn_code_longctx.sh

@@ -0,0 +1,80 @@
+#!/usr/bin/env bash
+# Long-context FlashAttention profile grid for the code-trace campaign.
+
+set -euo pipefail
+
+TP="${TP:?TP must be set to 1, 2, or 4}"
+case "${TP}" in
+  1|2|4) ;;
+  *) echo "ERROR: invalid TP=${TP}" >&2; exit 1 ;;
+esac
+
+OUTPUT_ROOT="${OUTPUT_ROOT:?OUTPUT_ROOT must be set}"
+MAX_MODEL_LEN="${MAX_MODEL_LEN:-147456}"
+VENV_ROOT="${VENV_ROOT:-/home/admin/cpfs/wjh/venvs/vllm-0.20.0-cu129-workload-regime-v2}"
+VLLM_SOURCE="${VLLM_SOURCE:-/home/admin/cpfs/wjh/agentic-kv/third_party/vllm_v20_build}"
+MODEL="${MODEL:-/home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B}"
+CAMPAIGN_ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PROFILE_SCRIPT="${CAMPAIGN_ROOT}/../frontier-qwen30-vllm020-profile-v1/profile_vllm020_flashattn.py"
+
+# Development window:
+#   ISL p90=88,224, p99=125,803; sampled rho<=0.0032 max total=137,016.
+# Tail query distribution modulo 8192:
+#   p10=495, p25=1477, p50=3594, p75=5917, p90=7246.
+# The full-chunk grid reaches 131,072 tokens of existing context; tail shapes
+# cover query-size variation at representative long contexts.
+BATCH_SPECS=(
+  q8ks48k q8ks64k q8ks80k q8ks96k q8ks112k q8ks128k q8ks136k
+  q512s128k q2ks66k q4ks100k q6ks134k
+  q1ks8k q512s4k
+)
+
+mkdir -p "${OUTPUT_ROOT}/logs" "${OUTPUT_ROOT}/provenance" "${OUTPUT_ROOT}/raw"
+exec > >(tee -a "${OUTPUT_ROOT}/logs/code-longctx-grid.log") 2>&1
+
+IFS=',' read -r -a GPU_IDS <<< "${CUDA_VISIBLE_DEVICES:?one allocated fleet GPU is required}"
+if [[ "${#GPU_IDS[@]}" -ne 1 ]]; then
+  echo "ERROR: expected exactly one GPU, got ${CUDA_VISIBLE_DEVICES}" >&2
+  exit 1
+fi
+
+test -x "${VENV_ROOT}/bin/python"
+test -f "${VLLM_SOURCE}/benchmarks/attention_benchmarks/runner.py"
+test -f "${MODEL}/config.json"
+test -f "${PROFILE_SCRIPT}"
+
+echo "PROFILE_LAUNCH_ECHO host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES} tp=${TP} max_model_len=${MAX_MODEL_LEN} specs=${BATCH_SPECS[*]}"
+date -u +"START_UTC=%Y-%m-%dT%H:%M:%SZ"
+nvidia-smi --query-gpu=index,name,driver_version,memory.used,utilization.gpu \
+  --format=csv,noheader
+git -C "${CAMPAIGN_ROOT}/../.." rev-parse HEAD \
+  > "${OUTPUT_ROOT}/provenance/aituner.commit"
+git -C "${VLLM_SOURCE}" rev-parse HEAD \
+  > "${OUTPUT_ROOT}/provenance/vllm-source.commit"
+sha256sum "${PROFILE_SCRIPT}" "${BASH_SOURCE[0]}" \
+  > "${OUTPUT_ROOT}/provenance/source.sha256"
+uv pip freeze --python "${VENV_ROOT}/bin/python" \
+  > "${OUTPUT_ROOT}/provenance/pip-freeze.txt"
+printf '%s\n' "${BATCH_SPECS[@]}" \
+  > "${OUTPUT_ROOT}/provenance/batch-specs.txt"
+printf '%s\n' "${MAX_MODEL_LEN}" \
+  > "${OUTPUT_ROOT}/provenance/max-model-len.txt"
+
+timeout --signal=TERM --kill-after=30s 1800 \
+  "${VENV_ROOT}/bin/python" "${PROFILE_SCRIPT}" \
+  --vllm-source "${VLLM_SOURCE}" \
+  --model "${MODEL}" \
+  --output "${OUTPUT_ROOT}/raw/flashattn-code-longctx-tp${TP}.json" \
+  --tp "${TP}" \
+  --batch-specs "${BATCH_SPECS[@]}" \
+  --warmup-iters 5 \
+  --repeats 10 \
+  --max-model-len "${MAX_MODEL_LEN}" \
+  --profile-kv-update
+
+test -s "${OUTPUT_ROOT}/raw/flashattn-code-longctx-tp${TP}.json"
+sha256sum "${OUTPUT_ROOT}/raw/flashattn-code-longctx-tp${TP}.json" \
+  "${OUTPUT_ROOT}/provenance"/* > "${OUTPUT_ROOT}/artifacts.sha256"
+nvidia-smi --query-gpu=index,name,memory.used,utilization.gpu --format=csv,noheader
+date -u +"END_UTC=%Y-%m-%dT%H:%M:%SZ"
+echo "FLASHATTN_CODE_LONGCTX_COMPLETE tp=${TP} cases=${#BATCH_SPECS[@]}"