[AMD][DI][CI] 3/N Add Kimi K2.6 FP8 MI355X 1P1D nightly recipes (#29855)

Co-authored-by: bingxche <bingxche@amd.com>
This commit is contained in:
Zhaoyi Li
2026-07-04 21:05:12 -07:00
committed by GitHub
co-authored by bingxche
parent a37bc2456d
commit 67361ff91b
4 changed files with 303 additions and 22 deletions
@@ -0,0 +1,75 @@
# 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