bench: orchestrate a multi-card campaign without touching the measurement path

campaign.sh fans a screened operator list across cards, one ab_repeat.sh per
card, serial within a card. It does no measuring: ab_repeat.sh is the path that
produced the four operator verdicts already on record, and it stays byte for
byte as it was.

Each card gets its own AB_ROOT. Eight ab_repeat.sh started in the same second
would otherwise compute the same timestamped directory name and two cards would
write into one.

ZL_ISOLATE_TUNER_CACHE=1 is forced, since eight processes on one sqlite is the
thing to avoid. The cost is that pinned configs differ from a shared-cache
batch, so absolute latencies cannot be quoted across the two; the caliber guard
refuses such comparisons on its own, which is why this is a note and not a
warning someone has to remember.

partition.py's shell output gained the per-card weight, because EXTRA_OPS has
to land on the lightest card and counting operators gets that wrong — one heavy
operator outweighs three light ones. It writes through stdout.buffer: Python
turns "\n" into CRLF on Windows, and the trailing \r then rides into the last
field and breaks the numeric comparison that picks the card.

README.md

@@ -137,6 +137,29 @@ ttgir 关键设计：
 - **命名 = 组内有区分度的参数**：同一 (shape, kernel) 组内取值相同的 constexpr 不进文件名；多词参数缩写为首字母（`BLOCK_SIZE_M` → `BSM`，图例见 naming.md）；同名冲突依次用 dtype（`__fp16`）、参数对齐特化（`__EMdiv16`）、hash 前缀消歧。
 - **崩溃也能拿到 IR**：dump 挂在进程 atexit 上，CUDA crash 后仍会落盘已编译部分。
 
+## 多卡跑一批：campaign.sh
+
+`ab_repeat.sh` 是单卡串行的。一批算子要并行时用 `campaign.sh` 编排——它只分活，
+测量仍然全部由 `ab_repeat.sh` 做，那个脚本一行不动。
+
+```bash
+SWITCH=FLAGTREE_MUSA_RLC_ENHANCE DEVICES=0,1,2,3,4,5,6,7   SCREEN=runs/ab_rlc_XXX/screen.tsv ZL_BACKEND=musa   FLAGGEMS_DIR=/path/to/FlagGems DRY_RUN=1 bash campaign.sh
+```
+
+`DRY_RUN=1` 先看方案，确认了再去掉它起跑。
+
+- **只取筛选表里 `IR_CHANGED` 的算子**——第一步的判定在这里生效
+- **按实测耗时贪心分片**（`partition.py`），不是 hash 取模。S5000 上 16 个算子实测：
+  hash 分片关键路径 120 分钟、有一张卡空转；贪心 70 分钟。**下界由最重的单个算子
+  决定**（`topk` 一个就 70.6 分钟），加卡不解决，分片只保证别的卡不空等
+- **每卡独立 `AB_ROOT`**——八个 `ab_repeat.sh` 同一秒启动，默认的时间戳目录名会撞
+- **强制 `ZL_ISOLATE_TUNER_CACHE=1`**。8 个进程写同一个 sqlite 是要避开的事。代价是
+  pin 的 config 与共享缓存批次不同，**两批的绝对延迟不可互引**——口径守卫会自己拒绝
+- `EXTRA_OPS` 追加筛选表里没有的算子（如 benchmark 刚修好的），放到**负载最小**的卡上
+- 跑完合并各卡 `status.tsv`（首列是卡号），并统计非零退出的格与三个标记的总数
+
+设备可见性变量名从 backends 层取，不写死 `MUSA_VISIBLE_DEVICES`。
+
 ## 两步：先筛选，再实测
 
 跑一个算子的六轮 A/B 要 13~44 分钟（S5000 实测：`rand` 15 shape 13.0 分钟，