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.
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