[AMD][DI][CI] 8/N Add GLM-5.2 MXFP4 1P1D DI/CI recipes (base + MTP + DP8/EP8) (#32120)

2026-08-06 22:56:40 -07:00
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+# MI355X GLM-5.2 (MXFP4) 2-node 1P1D disaggregation recipe.
+#
+# GLM-5.2 uses GlmMoeDsaForCausalLM (DeepSeek Sparse Attention). sglang
+# auto-selects the DSA attention backend for this architecture, so this recipe
+# leaves `attention_backend` unset (empty) and lets the server pick DSA. MXFP4
+# enables SGLANG_DSV4_FP4_EXPERTS in launch_mi355x.sh (driven by PRECISION),
+# same as the DeepSeek-V4 FP4 path.
+#
+# NOTE: the checkpoint on disk is amd/GLM-5.1-MXFP4 (only GLM MXFP4 build
+# currently mirrored on /it-share). model_path in nightly-configs.yaml points at
+# it; the recipe naming tracks the model line we are wiring CI for.
+#
+# 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` and `bench`.
+
+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 (generic launcher path; keeps
+# GLM off the hardcoded DeepSeek-V4 parser branch in launch_mi355x.sh). DSA
+# attention is auto-selected for GlmMoeDsaForCausalLM, so no --attention-backend
+# is set. GLM has a shared expert (n_shared_experts=1); shared-experts-fusion is
+# disabled to mirror the DeepSeek-V4 path.
+model:
+  env:
+    SGLANG_USE_AITER: 1
+  server_args:
+    - --reasoning-parser
+    - glm45
+    - --tool-call-parser
+    - glm45
+    - --disable-shared-experts-fusion
+
+runtime:
+  image: lmsysorg/sglang-rocm:v0.5.15.post1-rocm720-mi35x-20260722
+  # attention_backend intentionally unset: DSA is auto-selected for
+  # GlmMoeDsaForCausalLM.
+  # 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
+  swa_full_tokens_ratio: 0.1
+
+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
+  # (full GSM8K, 8-shot, accuracy > 0.91). A regression here fails the nightly
+  # even when throughput looks fine ("fast but wrong").
+  accuracy:
+    enabled: true
+    num_shots: 8
+    num_questions: 1319    # full GSM8K test set
+    threshold: 0.91