# TP×DP matrix experiment for GLM-5.2 on Ascend 910C (8 NPUs / 16 dies) using vLLM-Ascend.
# Tests vLLM with three parallel configurations:
#   TP=2, DP=4  -> 2 dies per replica, 4 replicas
#   TP=4, DP=2  -> 4 dies per replica, 2 replicas
#   TP=8, DP=1  -> 8 dies, no data parallelism
#
# Platform: ascend_910c (see platforms/ascend_910c.env).
# Host: 910c.1 / NPU-NODE61, openEuler 22.03 SP4 aarch64, driver 25.5.2, CANN 9.0.0.
# Image: vllm-ascend; load the tarball from /mnt/models first (see envs/ASCEND_910C_ENV_SETUP.md).

EXPERIMENT="glm52_910c_vllm_tp_dp_matrix"
MODEL_NAME="GLM-5.2"
# GLM-5.2 ships two quantized variants on this host; w4a8c8 is the default.
# Switch to /mnt/models/GLM-5.2-w8a8 by overriding MODEL_PATH if needed.
MODEL_PATH="${MODEL_PATH:-/mnt/models/GLM-5.2-w4a8c8}"
SERVED_MODEL_NAME="glm-5.2"

VLLM_PORT="${VLLM_PORT:-30050}"

# Dedicated container name so this experiment never touches other 910c runs.
CONTAINER_NAME="${CONTAINER_NAME:-vllm-ascend-glm52-910c}"

# Python interpreter for the benchmark client inside the vllm-ascend container.
CONTAINER_PYTHON="${CONTAINER_PYTHON:-/usr/local/bin/python}"

# vllm-ascend image. Override with the exact tag after `docker load`-ing one of:
#   /mnt/models/vllm-ascend-glm5.2-a3-openeuler.tar          (GLM5.2-tuned, recommended)
#   /mnt/models/vllm-ascend-v0.23.0rc1-a3-openeuler.tar      (general v0.23)
USE_DOCKER="${USE_DOCKER:-1}"
DOCKER_IMAGE="${DOCKER_IMAGE:-vllm-ascend:glm5.2-a3-openeuler}"

# Benchmark client Docker image. vLLM's image does not include sglang.bench_serving;
# reuse the vllm-ascend container itself for the client via `docker exec` (see
# run_adaptive_concurrency_add16.sh), so this is only used if USE_DOCKER_CLIENT=1
# with an external sglang image. Default off on 910c.
DOCKER_CLIENT_IMAGE="${DOCKER_CLIENT_IMAGE:-lmsysorg/sglang:latest}"
USE_DOCKER_CLIENT="${USE_DOCKER_CLIENT:-0}"

# Device selection. ASCEND_VISIBLE_DEVICES selects NPU cards 0..7; the Ascend
# Docker Runtime (default runtime on this host) injects the matching dies.
export ASCEND_VISIBLE_DEVICES="${ASCEND_VISIBLE_DEVICES:-0,1,2,3,4,5,6,7}"
# Keep CUDA_VISIBLE_DEVICES for parity with the shared library; vllm-ascend
# ignores it on NPU but some helper code reads it.
export CUDA_VISIBLE_DEVICES="${CUDA_VISIBLE_DEVICES:-0,1,2,3,4,5,6,7}"

# Runtime working directory for logs, pid files, and tmp.
RUNTIME_BASE="${RUNTIME_BASE:-${SCRIPT_DIR}/runtime}"

# Parallel configurations to test. Format: "TP DP"
# Each Ascend910 card has 2 dies; TP addresses dies, so TP=8 uses 8 dies across
# 4 cards and leaves room for DP. TP=2/DP=4 and TP=4/DP=2 and TP=8/DP=1 all fit
# within 8 cards (16 dies). Override via PARALLEL_CONFIGS_STR="8,1".
if [[ -n "${PARALLEL_CONFIGS_STR:-}" ]]; then
  declare -a PARALLEL_CONFIGS=()
  for pair in $PARALLEL_CONFIGS_STR; do
    PARALLEL_CONFIGS+=("${pair//,/ }")
  done
else
  declare -a PARALLEL_CONFIGS=(
    "2 4"
    "4 2"
    "8 1"
  )
fi

# vLLM-Ascend server settings for GLM-5.2 (w4a8c8).
# Notes:
#   - KV cache dtype fp8 is supported on 910C; fall back to fp16 if the image rejects it.
#   - block-size 128 matches Ascend page semantics (P99 of H20 uses 256; 910C favors 128).
#   - MAX_MODEL_LEN: GLM-5.2 supports up to 128K context; cap at 131072.
#   - gpu-memory-utilization maps to NPU HBM fraction on vllm-ascend (0.9 mirrors H20).
GPU_MEMORY_UTILIZATION="${GPU_MEMORY_UTILIZATION:-0.9}"
KV_CACHE_DTYPE="${KV_CACHE_DTYPE:-fp8}"
BLOCK_SIZE="${BLOCK_SIZE:-128}"
MAX_MODEL_LEN="${MAX_MODEL_LEN:-131072}"
MAX_NUM_SEQS="${MAX_NUM_SEQS:-256}"

# vLLM-Ascend-specific launch flags injected by start_vllm_docker.sh.
# attention backend for 910C: use the fused/atb attention path. Adjust per image.
VLLM_ASCEND_ATTENTION_BACKEND="${VLLM_ASCEND_ATTENTION_BACKEND:-atb}"

# Dataset used by sglang.bench_serving --dataset-name random.
DATASET_PATH="${DATASET_PATH:-${ROOT_DIR}/datasets/ShareGPT_V3_unfiltered_cleaned_split.json}"

# Matrix and concurrency rules are defined in matrix.json by default.
MATRIX_FILE="${MATRIX_FILE:-${SCRIPT_DIR:-.}/matrix.json}"
MATRIX_MODE="${MATRIX_MODE:-Y}"

export CONCURRENCY_SAMPLES="${CONCURRENCY_SAMPLES:-2}"

SCENARIO_TIMEOUT_S="${SCENARIO_TIMEOUT_S:-1800}"
GPU_MEM_SAMPLE_INTERVAL_S="${GPU_MEM_SAMPLE_INTERVAL_S:-1}"

DRY_RUN="${DRY_RUN:-0}"
GRID_LIMIT="${GRID_LIMIT:-0}"