# MI355X Kimi-K2.6 (FP8) 2-node 1P1D disaggregation recipe (base).
#
# All Kimi-specific config lives in this recipe's `model:` block (docker env +
# sglang server args) and `runtime` (split attention backends); nothing about
# Kimi is hardcoded in launch_mi355x.sh. Mirrors the single-node registered test
# test/registered/amd/accuracy/mi35x/test_kimi_k26_eval_mi35x.py (TP8, split
# attention backends, multithread loader, GSM8K > 0.92).
#
# Consumed by:
#   * scripts/ci/slurm/process_result.py reads `resources` and
#     `backend.sglang_config` (TP/EP/DP + worker counts) for the summary table.
#   * scripts/ci/slurm/launch_mi355x.sh reads `runtime`, `bench`, `model`, `mtp`.

resources:
  prefill_workers: 1
  decode_workers: 1

backend:
  sglang_config:
    prefill:
      tensor-parallel-size: 8
      expert-parallel-size: 1
      data-parallel-size: 1
    decode:
      tensor-parallel-size: 8
      expert-parallel-size: 1
      data-parallel-size: 1

# Model-specific docker env + sglang server args (written verbatim via
# model_flags.sh). Each server arg + value is a SEPARATE list item.
model:
  env:
    SGLANG_USE_AITER: 1
    SGLANG_ROCM_FUSED_DECODE_MLA: 0
  server_args:
    - --model-loader-extra-config
    - '{"enable_multithread_load": true}'
    - --watchdog-timeout
    - 1200
    - --reasoning-parser
    - kimi_k2
    - --tool-call-parser
    - kimi_k2

runtime:
  image: lmsysorg/sglang-rocm:v0.5.13.post1-rocm720-mi35x-20260623
  # Kimi uses split attention backends (aiter prefill / triton decode), not a
  # single --attention-backend.
  prefill_attention_backend: aiter
  decode_attention_backend: triton
  # RoCE HCAs MORI uses for cross-node KV transfer.
  ib_devices: rdma0,rdma1,rdma2,rdma3
  prefill_port: 30025
  decode_port: 30026
  prefill_bootstrap_port: 8998
  decode_bootstrap_port: 9001
  lb_port: 8000
  mem_fraction_static: 0.90
  page_size: 256
  max_running_requests: 256
  chunked_prefill_size: 8192

bench:
  # bench_serving --max-concurrency sweep; one result JSON per concurrency.
  concurrencies: [1, 8, 16, 32, 64, 128, 256]
  num_prompts_factor: 4      # num-prompts = concurrency * factor
  random_range_ratio: 1.0

  # Correctness gate run through the PD path before the perf sweep. Mirrors the
  # registered single-node Kimi-K2.6 eval (full GSM8K, 8-shot, accuracy > 0.92).
  accuracy:
    enabled: true
    num_shots: 8
    num_questions: 1319    # full GSM8K test set
    threshold: 0.92