memory: snapshot — GX10 outfitted userspace; bare metal ruled; CUDA works on sm_121

Ruling on the architecture question: bare metal, not Proxmox. Proxmox VE
has no aarch64 build, and more fundamentally the GB10's GPU sits on an
on-package root complex cache-coherent with the CPU over NVLink-C2C,
sharing the same LPDDR5X. Passing it to a guest would mean partitioning
the unified memory that is the entire reason for the box. The fleet's
other GPU hosts are bare metal for the same class of reason.

Installed uv and a venv with torch 2.14.0+cu130 plus the full training
stack, and every one of transformers, accelerate, peft, trl, datasets,
safetensors, huggingface_hub and bitsandbytes imports clean on aarch64.
The per-arch unknowns warning did not materialise for any of them.

CUDA works: sm_121, 121.6 GiB addressable, about 93 TFLOP/s dense bf16
with tensor cores confirmed engaged by the bf16-to-fp32 ratio. That is
A6000-class throughput with two and a half times the memory, so capacity
rather than speed is what this box buys.

Two warnings worth keeping. sm_121 is not in torch's compiled arch list,
so everything runs by PTX JIT from sm_120: first use of every kernel pays
a compile, and any library shipping cubins without PTX will fail outright.
And an unwarmed benchmark read 27 TFLOP/s because it was timing that JIT,
which nearly became a phantom report that tensor cores were broken -- the
playbook's section 4 shape exactly, a run that completes and reports
plausible numbers and is wrong.

The privileged half is blocked: infra-ops has no NOPASSWD sudo on this
box, unlike the rest of the fleet, and no credential is vaulted. That
gates nvcc, the container toolkit and the docker group, but not the
run-3c throughput probe.

persistent-memory.md

@@ -123,6 +123,18 @@ _As of 2026-09-01 — **the GX10 is on the operator's desk, NOT racked. Standing
   cable. ⚠ **Racking is NOT a prerequisite** — the Wi-Fi 7 link measures **67 MB/s over SSH**
   (49 GB base in ~12 min), so the throughput probe can run from the desk today.
   ⚠ `nvidia-smi` FB Memory `N/A` is CORRECT for GB10 unified memory, not a fault.
+  ✅ **OUTFITTED 2026-09-01 (userspace)** — **RULING: BARE METAL, not Proxmox** (no aarch64 PVE
+  build; the GPU is on-package and cache-coherent over NVLink-C2C so passthrough would partition
+  the unified memory that is the whole point; fleet GPU hosts are all bare metal).
+  Installed `uv` 0.12.9 + `~/ml/.venv` with torch **2.14.0+cu130** and the full training stack
+  (transformers/accelerate/peft/trl/datasets/bitsandbytes) — **all import clean on aarch64**.
+  **CUDA WORKS: sm_121, 121.6 GiB addressable, ~93 TFLOP/s bf16** (A6000-class speed, 2.5x the
+  memory). ⚠ **sm_121 is NOT in torch's arch list** — everything JITs from sm_120 PTX, so
+  **first use of every kernel pays a JIT compile** and cubin-only libraries will fail.
+  ⚠⚠ **ALWAYS WARM UP BEFORE TIMING** — an unwarmed benchmark read 27 TFLOP/s (it was timing the
+  JIT) and nearly became a phantom "tensor cores are broken" report.
+  🔴 **BLOCKED ON SUDO** for nvcc / container toolkit / docker group: **infra-ops has NO NOPASSWD
+  sudo on gx10** (fleet exception) and **no credential is vaulted**.
   → `persistent-memory.d/2026-09-01-pfi-gx10-onboarding.md`
 - **▶ ADA INFERENCE SERVER (R750xa `JPJ1ZP3`) — awaiting an iDRAC inventory.** 2× RTX 6000
   Ada to be fitted; ComfyUI's new home at NH3. **Order regardless: 8× `M04W6` RDIMM (restores