From 9b0d1c283c0121dfa3dfc89e4100539ea2ced866 Mon Sep 17 00:00:00 2001
From: Claude <claude@anthropic.com>
Date: Sat, 1 Aug 2026 13:12:59 +0000
Subject: [PATCH] =?UTF-8?q?docs:=20add=20competition=20server=20profile=20?=
 =?UTF-8?q?(4=C3=97BI-V100,=20Qwen3.6-35B-A3B)?=
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Hardware: 4× Iluvatar BI-V100 32GB, Xeon Gold 6530, 503GB RAM
Software: vllm 0.6.3+corex.3.2.3, torch 2.1.0+corex.3.2.3
Model: Qwen3.6-35B-A3B at /root/public-storage/models/Qwen/
Benchmark: benchmark_server_v0.5.0.py with automated sweeps
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+# Competition Server Profile
+**Captured**: 2026-08-01
+
+## Hardware
+- **GPU**: 4× Iluvatar BI-V100 32GB HBM each (128GB total)
+  - Clock: SM 1500MHz / Mem 1200MHz
+  - Driver: 3.2.1, COREX 10.2
+  - Power: 250W TDP per card
+- **CPU**: Intel Xeon Gold 6530
+- **RAM**: 503GB DDR
+- **Disk**: 3.5TB overlay, 100GB JuiceFS (public-storage)
+
+## Software
+- **OS**: Ubuntu 20.04.6 LTS, kernel 5.15.0-119
+- **COREX**: 3.2.3 at `/usr/local/corex`
+- **torch**: 2.1.0+corex.3.2.3
+- **vllm**: 0.6.3+corex.3.2.3
+- **transformers**: 4.51.3
+
+## Model
+- **Path**: `/root/public-storage/models/Qwen/Qwen3.6-35B-A3B/`
+- **Name**: Qwen3.6-35B-A3B (MoE, 35B total, 3B active)
+- **Note**: 4 cards × 32GB = 128GB total, model fits
+
+## Key Paths
+- `/root/llm-infer/` — benchmark scripts, README
+- `/root/public-storage/models/Qwen/` — model weights
+- `/root/apps/llm-modelzoo/benchmark/vllm/` — benchmark tools
+- `/share/fshare/common/models/` — shared model storage (NFS)
+
+## Benchmark Tools
+- `benchmark_server_v0.5.0.py` — automated server benchmark
+  - Sweeps: max-num-seqs=[128,256] × num-prompts=[1,128] × input=[128,1024] × output=[128,1024]
+- `benchmark_server_v0.5.0.sh` — launches vllm server + benchmark client
+  - Sets `NCCL_FORCESYNC_DISABLE=1`
+  - Auto-cleanup of vllm processes
+- `benchmark_serving_tokens.py` — online serving benchmark client
+
+## Scoring Formula
+`Output TPS × 16.796 + Input TPS × 2.799 + Cache TPS × 0.56`
+- Threshold: ≥ 8000 weighted score
+- Output TPS weight: 83% of total score