8fc7b407f3
T490s already runs Win11, so keep it: WSL2 gives clean Linux CUDA env with eGPU passthrough where the Linux-first 3D repos build properly. Bare-metal Ubuntu kept as the leaner Path B. Covers mirrored WSL networking, headless/lid + Windows Update settings for an always-on worker. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
72 lines
3.9 KiB
Markdown
72 lines
3.9 KiB
Markdown
# CUDA Worker Setup — T490s + 2080 Ti eGPU on the tailnet
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Goal: a headless box with the RTX 2080 Ti (11GB) eGPU, live on Tailscale, that
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MODELBEAST (on the M3 Ultra) offloads the CUDA-only jobs the Mac can't run —
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gaussian-splat → mesh extraction (SuGaR/2DGS), research-grade video mocap
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(GVHMR/WHAM/TRAM), NeRF/tiny-cuda-nn, nvdiffrast/PyTorch3D.
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**Why the T490s and not the Intel iMac:** no T2 chip = no Secure-Boot/Thunderbolt
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fight; laptop idles ~6–10W (+ ~20W eGPU) vs ~55–75W for the iMac; battery = built-in
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UPS. The 2080 Ti is EOL-ish (Turing: no bf16/fp8, 11GB) — a *compatibility* box, not
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a performance one. It won't beat the M3 Ultra at anything the Mac already does; it
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only unlocks the CUDA-locked tail.
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**A physical GPU can't be passed to a VM on a Mac/Windows consumer hypervisor** — so
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the CUDA OS must have direct hardware access. On this ThinkPad that's either native
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Windows (already installed) or WSL2 (a real Linux env Windows gives GPU access to).
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NOT a Linux VM on macOS.
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---
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## Path A — Keep Windows 11 + WSL2 (RECOMMENDED: Win11 already runs, no reinstall)
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Windows drives the eGPU; WSL2 gives a clean Ubuntu where the Linux-first 3D repos
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build properly (native-Windows builds of their custom CUDA kernels are a pain).
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1. **NVIDIA Windows driver** (Studio or Game Ready) with the 2080 Ti plugged in.
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Confirm Device Manager → Display adapters shows the 2080 Ti. This one driver is
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all WSL2 needs — do NOT install a driver inside WSL.
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2. **WSL2 + Ubuntu** (admin PowerShell): `wsl --install -d Ubuntu` → reboot.
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3. **CUDA toolkit INSIDE WSL** (the `wsl-ubuntu` package — toolkit only, no driver),
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per NVIDIA's "CUDA on WSL" guide. Then verify: `nvidia-smi` inside Ubuntu lists
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the 2080 Ti. (If empty: update the Windows driver; ensure eGPU present at boot.)
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4. **Reach WSL from the tailnet cleanly** — create `C:\Users\<you>\.wslconfig`:
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```
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[wsl2]
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networkingMode=mirrored
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```
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(Win11 22H2+; makes WSL share the host's network so Tailscale/SSH reach it.)
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5. **Tailscale** on the Windows host: install, sign in, `tailscale ip -4` → note it.
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6. **Headless Windows settings:** Power → "when I close the lid: do nothing" + never
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sleep; enable **OpenSSH Server** (Settings → Optional Features); set Windows Update
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active hours wide / pause auto-reboots so it never reboots mid-job.
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7. Access model: MODELBEAST SSHes to the Windows host over Tailscale and runs CUDA
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tools via `wsl bash -lc "..."`, or SSH straight into WSL with mirrored networking.
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## Path B — Bare-metal Ubuntu (leaner/lower-power, if you'd rather wipe Win11)
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1. Ubuntu 24.04 LTS bare metal.
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2. `sudo ubuntu-drivers autoinstall && sudo apt install nvidia-cuda-toolkit && sudo reboot`; `nvidia-smi` must show the 2080 Ti.
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3. `curl -fsSL https://tailscale.com/install.sh | sh && sudo tailscale up --ssh`.
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4. Lid-closed headless: set `HandleLidSwitch=ignore` in `/etc/systemd/logind.conf`.
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(No Thunderbolt-authorization dance needed on a non-Mac — it enumerates on boot.)
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---
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## MODELBEAST integration (I'll build this once the box is on the tailnet)
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The operator framework already shells out to tools; a **remote-CUDA operator** wraps
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that: rsync the input to the worker, `ssh` (→ `wsl` on Path A) to run the CUDA tool
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in its env, rsync results back, register as assets. Add a `cuda_host` setting (tailnet
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IP + user) to the vault. Planned:
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- `sugar_mesh` — splat `.ply` → textured mesh (closes the Brush→mesh gap; the Mac can't extract meshes from splats). ~5–6GB, fits 11GB.
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- `gvhmr_mocap` — video → world-grounded SMPL → FBX (research-grade; replaces the cloud/manual path). Light.
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Does NOT fit 11GB: FLUX, 20B+ models — those stay on the Mac.
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## Reality check
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Worth it only because the card's already owned. If buying, a used RTX 3090 (24GB,
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bf16) is strictly better and unlocks FLUX/video too. Turing's runway is shrinking
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(newer 3D wheels drop 20-series). Use the free card for the CUDA-only leftovers, not
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as a foundation.
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