# baseline.muh — Competition reference configuration
# Corresponds to: dev.modelhub.org.cn EngineX-Iluvatar/enginex-vllm-bi100-qwen36
#
# This is the starting point. All tuning values are pending BI-V100 benchmarks.
# Child .muh files use 'extends: baseline.muh' to override specific algorithms.

# --- Hardware description ---
hardware:
  name: Iluvatar-BI-V100-50c-200G
  gpu_count: 4
  # These need to be confirmed on actual hardware:
  warp_size: 32
  max_threads_per_block: 1024
  max_shared_memory_per_block: 49152
  max_registers_per_thread: 255
  l2_cache_size_bytes: 6291456
  memory_bandwidth_gbps: 900
  compute_capability: iluvatar_bi100

# --- vllm launch configuration ---
# Maps directly to computility-run.yaml command
vllm:
  model_path: /model
  served_model_name: llm
  max_model_len: 100000
  gpu_memory_utilization: 0.9
  tensor_parallel: 4
  max_num_seqs: 1
  max_num_batched_tokens: 8192
  max_seq_len_to_capture: 32768
  trust_remote_code: true
  disable_log_requests: true
  disable_frontend_multiprocessing: true
  enable_chunked_prefill: true
  enable_auto_tool_choice: true
  tool_call_parser: qwen3_coder
  reasoning_parser: qwen3
  enable_prefix_caching: true

# --- Concurrency ---
concurrency: 1

# --- Environment ---
env:
  VLLM_ENGINE_ITERATION_TIMEOUT_S: 3600

# --- Tuning overrides (per CCCL algorithm) ---
# Each key corresponds to a tuning_*.cuh schema in muh/schema/
# Values are TBD until we run benchmarks on BI-V100
#
# Priority order (by competition score impact):
#   1. reduce   — attention reduction (Output TPS × 16.796)
#   2. topk     — sampling top-k/top-p (Output TPS × 16.796)
#   3. scan     — prefix scan in paged attention
#   4. transform — activation kernels (SiLU, GELU)
#   5. batch_memcpy — KV cache management (Cache TPS × 0.56)
#   6. for      — RoPE position encoding

tuning:
  reduce:
    _priority: P0
    _vllm_impact: attention_reduction
    _score_weight: Output TPS × 16.796
    # CCCL SM90 reference: threads=128, items=24, vec_size=4
    # CCCL SM100 reference: threads varies by accum_size
    threads_per_block: null
    items_per_thread: null
    vec_size: null

  topk:
    _priority: P0
    _vllm_impact: sampling_decode
    _score_weight: Output TPS × 16.796
    # CCCL reference: threads=512, items=4, bits_per_pass=11
    threads_per_block: null
    items_per_thread: null
    bits_per_pass: null

  scan:
    _priority: P0
    _vllm_impact: paged_attention_prefix_scan
    _score_weight: Input TPS × 2.799
    # CCCL SM90 lookback: threads=128, items=24, delay=fixed(688, 1140) for float32
    # CCCL SM100 lookback: threads=384, items=22, delay=exponential_backon(1904, 830)
    # CCCL SM100 lookahead: warps=4, items=80-1, lookahead_items=3
    threads_per_block: null
    items_per_thread: null
    load_algorithm: null
    store_algorithm: null
    scan_algorithm: null

  transform:
    _priority: P1
    _vllm_impact: activation_elementwise
    _score_weight: Output TPS × 16.796
    threads_per_block: null
    items_per_thread: null

  batch_memcpy:
    _priority: P1
    _vllm_impact: kv_cache_copy
    _score_weight: Cache TPS × 0.56
    threads_per_block: null

  for:
    _priority: P2
    _vllm_impact: rope_position_encoding
    threads_per_block: null
    items_per_thread: null

  radix_sort:
    _priority: P2
    _vllm_impact: beam_search_token_sort
    threads_per_block: null
    items_per_thread: null
    radix_bits: null

  merge:
    _priority: P2
    _vllm_impact: sequence_merging
    threads_per_block: null
    items_per_thread: null