recipes: glm53-flash-nvfp4-lab-4x-r38

recipes/glm53-flash-nvfp4-lab-4x-r38/recipe.toml

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+# GLM-5.3-Flash NVFP4-lab — the lab's NVFP4 quant (2026-09-16 RE-CUT,
+# local-inference-lab/GLM-5.3-Flash-NVFP4), 4× DGX Spark, TP=4.
+#
+# 4-node twin of glm53-flash-nvfp4-lab (2x): same model, same r35 engine,
+# same interim-mode flags — TP=4 halves the per-node weights
+# (199.4 GB / 4 ≈ 46.5 GiB/node), leaving ~55 GiB for the auto-sized KV
+# pool at GMU 0.88 (the 2x lane's ~10 GiB headroom is not a constraint here).
+#
+# Structure (verified from model.safetensors.index.json, identical to the
+# Spark checkpoint): `model.language_model.layers.*` with SPLIT GDN naming
+# (q/k/g_a/g_b/f_a/f_b/b_proj + hc_* hybrid-conv), a `model.visual.*`
+# tower (skipped via --language-model-only), and the MTP head embedded at
+# layer 45 (eh_proj/enorm/hnorm) — no separate drafter download.
+#
+# Image: jovian-judgement:r35-glm53 + VLLM_DISABLED_KERNELS (the small GDN
+# mxfp8 GEMMs reject flashinfer cutlass' min n/k=128 — routed to the b12x
+# Mxfp8 backend; proven on the Spark 4x lane, 161/176).
+#
+# PREREQUISITES: weights on each node's LOCAL hub (the NAS disk died
+# 2026-09-19): /home/kilork/hf-local, ~/.cache/huggingface symlink
+# re-pointed per node. Re-cut re-download on all 4 nodes.
+
+engine = "vllm"
+name = "GLM-5.3-Flash NVFP4-lab re-cut (vLLM, 4x Spark, MTP-3, r38) — C-track deadlock test"
+docker_image = "jovian-judgement:r38"
+docker_image_dir = "jovian-judgement"  # r38 image is a prebuilt node artifact (no profile in the r35 dir)
+
+entrypoint = ["vllm", "serve"]
+model = "local-inference-lab/GLM-5.3-Flash-NVFP4"
+parent_model = "zai-org/GLM-5.3-Flash"
+required_nodes = 4
+tensor_parallel_size = 4
+pipeline_parallel_size = 1
+distributed_backend = "mp"
+shm_size = "32gb"
+
+args = [
+    # Stable served name — quant-agnostic (shared across glm53 quants)
+    "--served-model-name", "glm53",
+    "--trust-remote-code",
+    "--distributed-executor-backend", "mp",
+    # GMU is ONLY a startup guardrail: 0.88 = 107.0 GiB, below any
+    # realistic free-memory dip on GB10's 121.63 GiB (#48140).
+    "--gpu-memory-utilization", "0.88",
+    # no KV pin: ~46.5 GiB weights/rank leaves ~55 GiB — auto-sized pool
+    "--block-size", "256",
+    "--max-model-len", "524288",
+    "--max-num-seqs", "16",
+    "--max-num-batched-tokens", "4096",
+    "--enable-chunked-prefill",
+    "--async-scheduling",
+    "--enable-prefix-caching",
+    # B12X sparse-MLA (required for head-512 on sm_12x)
+    "--attention-backend", "B12X",
+    # pure I/O loader (baked into the r27-lineage images; ~1 min off local NVMe)
+    "--load-format", "instanttensor",
+    # Their proven boot: no flashinfer autotune, no CuTe-DSL warmup
+    "--kernel-config", """
+'{"enable_cutedsl_warmup":false,"enable_flashinfer_autotune":false}'""",
+    # Built-in MTP draft, 3 tokens (layer 45, in-checkpoint). The draft
+    # model's vllm_config takes its attention backend from the SPECULATIVE
+    # config, not the global flag — B12X mirrors the main model.
+    "--speculative-config", """
+'{"method":"mtp","num_speculative_tokens":3,"attention_backend":"B12X"}'""",
+    "--language-model-only",
+    "--tool-call-parser", "glm47",
+    "--enable-auto-tool-choice",
+    "--reasoning-parser", "glm45",
+]
+
+[env]
+HF_HUB_OFFLINE = "1"
+# RoCEnante (b12x one-shot RoCE all-reduce/all-gather) — default on for the
+# r27 lanes since the 2026-09-08 A/B (4x: decode +31..+90%, quality 160 vs
+# 155). Needs the RoCE fabric; single-node serves skip it silently.
+VLLM_ENABLE_ROCE_ALLREDUCE = "1"
+# Route mxfp8 linears away from flashinfer cutlass (rejects small GDN GEMMs: min n/k=128)
+VLLM_DISABLED_KERNELS = "FlashInferCutlassMxfp8LinearKernel"
+# FlashInfer JIT compiles at first boot with N parallel nvcc jobs ->
+# OOM-killed on GB10 while weights+KV are resident; cap the ninja jobs.
+MAX_JOBS = "2"
+# NoPE-MLA rope-pad runtime gate (mod baked into the image lineage)
+VLLM_MLA_NOPE_PAD_ROPE = "1"
+VLLM_ENGINE_READY_TIMEOUT_S = "3600"
+# Upstream launch-script env (memory + compile knobs)
+PYTORCH_CUDA_ALLOC_CONF = "expandable_segments:True"
+VLLM_USE_AOT_COMPILE = "0"
+VLLM_USE_STANDALONE_COMPILE = "1"
+VLLM_USE_FLASHINFER_SAMPLER = "1"
+VLLM_USE_BREAKABLE_CUDAGRAPH = "0"
+TORCH_USE_RTLD_GLOBAL = "1"
+VLLM_NO_USAGE_STATS = "1"
+
+# Architecture (aarch64 / sm_121a DGX Spark)
+TORCH_CUDA_ARCH_LIST = "12.1a"
+FLASHINFER_CUDA_ARCH_LIST = "12.1f"
+CUTE_DSL_ARCH = "sm_121a"
+CMAKE_CUDA_ARCHITECTURES = "121"
+OMP_NUM_THREADS = "2"
+
+# JIT caches persist per-node across serves (cold /root/.cache per container
+# = ~20 min flashinfer/torch recompile every serve)
+[[extra_mounts]]
+host = "~/sm121-cache/glm53-jit-121f/b12x"
+container = "/root/.cache/b12x"
+
+[[extra_mounts]]
+host = "~/sm121-cache/jit-121f/flashinfer"
+container = "/root/.cache/flashinfer"
+
+[[extra_mounts]]
+host = "~/sm121-cache/jit-121f/torchinductor"
+container = "/root/.cache/torchinductor"
+
+[[extra_mounts]]
+host = "~/sm121-cache/jit-121f/vllm"
+container = "/root/.cache/vllm"