fleet redo 2026-08-17: retire PP+NPU, new topology

- Move all previous scripts to old/scripts/ (retired PP/NPU-era)
- frank-default-large: llama.cpp FastMTP on dankserver (HauhauCS
  Qwen3.8-27B IQ4_XS + FastMTP 32K draft + ngram-mod, K q8_0/V f16,
  128K ctx, batch 2048/ubatch 1024, port 7770)
- frank-default-small: vLLM ROCm on dankclaw (Avesed Qwen3.6-35B-A3B
  INT8 W8A8, full 262144 ctx, no KV quant, 4 seqs, batch 16384,
  ngram spec, port 52625)
- retarget deploy.sh (dankserver/dankclaw, inline sudo, no helpers)
- docs: deployment + index + AGENTS.md + README for new topology,
  superseded banners on retired docs, add frank-redo-2026-08-17 runbook

old/scripts/pp-bench.py

@@ -0,0 +1,103 @@
+#!/usr/bin/env python3
+"""pp-bench.py — drive the PP head API and report server-side timings.
+
+Runs on the HEAD machine (Dankclaw). Targets the running PP head
+(serve-pp-head.sh, port from argument). Builds a ~Nk-token prose prompt,
+sends one warmup completion, then REPS measured completions, and reads the
+authoritative `slot print_timing` lines from the head log.
+
+Usage:
+    python3 pp-bench.py <prompt_k> <out_tokens> <reps> <port> <head_log>
+"""
+import json
+import re
+import sys
+import time
+import urllib.request
+
+prompt_k, out_tokens, reps, port, head_log = sys.argv[1:6]
+out_tokens = int(out_tokens)
+reps = int(reps)
+target = int(prompt_k) * 1000
+
+# ~38 tokens per 160-char prose unit; size the filler to hit the target.
+unit = ("The careful study of natural language reveals patterns of meaning "
+        "that emerge from the deliberate arrangement of words and phrases. ")
+approx = max(1, target // 38)
+prompt = unit * approx + (
+    "\n\nNow, in a detailed and flowing paragraph, "
+    "continue this essay about the philosophy of "
+    "language and its influence on modern computation. "
+)
+
+
+def req(n):
+    body = json.dumps({"prompt": prompt, "max_tokens": n,
+                       "temperature": 0.0, "stream": False}).encode()
+    r = urllib.request.Request(
+        f"http://127.0.0.1:{port}/v1/completions",
+        data=body, headers={"Content-Type": "application/json"})
+    with urllib.request.urlopen(r, timeout=7200) as resp:
+        return json.load(resp)
+
+
+def log_timings():
+    try:
+        lines = open(head_log, encoding="utf-8", errors="ignore").read().splitlines()
+    except OSError:
+        return []
+    out = []
+    for l in lines:
+        if re.search(r"prompt eval time|eval time|draft acceptance", l):
+            out.append(l.strip())
+    return out
+
+
+GEN_RE = re.compile(
+    r"eval time =\s+([\d.]+) ms /\s+(\d+) tokens.*?([\d.]+) tokens per second")
+PRE_RE = re.compile(
+    r"prompt eval time =\s+([\d.]+) ms /\s+(\d+) tokens.*?([\d.]+) tokens per second")
+ACC_RE = re.compile(r"draft acceptance = ([\d.]+)")
+
+# warmup (first run pays graph-compile / JIT costs)
+warm = req(16)
+print(f"warmup: prompt_tokens={warm['usage']['prompt_tokens']} "
+      f"completion_tokens={warm['usage']['completion_tokens']}")
+
+gen_rates, prefill_rates, accepts = [], [], []
+for i in range(reps):
+    t0 = time.time()
+    out = req(out_tokens)
+    dt = time.time() - t0
+    u = out["usage"]
+    pt, ct = u["prompt_tokens"], u["completion_tokens"]
+    gen = pre = acc = None
+    for l in log_timings():
+        if "prompt eval" not in l:
+            m = GEN_RE.search(l)
+            if m:
+                gen = float(m.group(3))
+        m = PRE_RE.search(l)
+        if m:
+            pre = float(m.group(3))
+        m = ACC_RE.search(l)
+        if m:
+            acc = float(m.group(1))
+    gen_rates.append(gen if gen is not None else ct / dt)
+    if pre is not None:
+        prefill_rates.append(pre)
+    if acc is not None:
+        accepts.append(acc)
+    print(f"rep {i + 1}: prompt={pt} gen={ct} wall={dt:.1f}s "
+          f"gen={gen_rates[-1]:.2f} t/s "
+          f"prefill={f'{pre:.1f}' if pre is not None else 'n/a'} t/s "
+          f"acceptance={f'{acc:.3f}' if acc is not None else 'n/a'}")
+
+print("== RESULT pp ==")
+print(f"avg gen tok/s   = {sum(gen_rates) / len(gen_rates):.2f}")
+if prefill_rates:
+    print(f"avg prefill t/s = {sum(prefill_rates) / len(prefill_rates):.1f}")
+if accepts:
+    print(f"avg acceptance  = {sum(accepts) / len(accepts):.3f}")
+for l in log_timings()[-3:]:
+    print("  " + l)