# CUDA Worker Setup — T490s + 2080 Ti eGPU on the tailnet

Goal: a headless Linux box with the RTX 2080 Ti (11GB) eGPU, live on Tailscale, that
MODELBEAST (on the M3 Ultra) offloads the CUDA-only jobs the Mac can't run —
gaussian-splat → mesh extraction (SuGaR/2DGS), research-grade video mocap
(GVHMR/WHAM/TRAM), NeRF/tiny-cuda-nn, nvdiffrast/PyTorch3D.

**Why a ThinkPad and not the Intel iMac:** no T2 chip = no Secure-Boot/Thunderbolt
fight; laptop idles ~6–10W (+ ~20W eGPU) vs ~55–75W for the iMac; battery = built-in
UPS. The 2080 Ti is EOL-ish (Turing: no bf16/fp8, 11GB) — it's a *compatibility*
box, not a performance one. It will not beat the M3 Ultra at anything the Mac
already does; it only unlocks the CUDA-locked tail.

## Do this at the shop (once)

1. **Ubuntu 24.04 LTS**, bare metal (dual-boot Win11 or wipe — bare-metal, NOT a VM;
   macOS/Windows hypervisors can't pass a physical GPU through, so a Linux VM can't
   do CUDA on the eGPU).

2. **Thunderbolt authorize the eGPU** (plug in the Razer Core first):
   ```bash
   sudo apt install bolt
   boltctl list                      # find the enclosure UUID
   boltctl enroll --policy auto <UUID>
   ```

3. **NVIDIA driver + CUDA:**
   ```bash
   sudo ubuntu-drivers autoinstall   # or the latest official driver branch
   sudo apt install nvidia-cuda-toolkit
   sudo reboot
   nvidia-smi                        # must list the 2080 Ti over Thunderbolt
   ```
   If it doesn't appear: confirm the eGPU was connected at boot, re-check `boltctl`,
   ensure the `thunderbolt` module loads before `nvidia_drm`.

4. **Tailscale:**
   ```bash
   curl -fsSL https://tailscale.com/install.sh | sh
   sudo tailscale up --ssh          # --ssh lets the M3 Ultra SSH in over the tailnet
   tailscale ip -4                   # note this IP → put it in MODELBEAST settings
   ```

5. **Headless / low-power:** run lid-closed →
   `sudo sed -i 's/#HandleLidSwitch=suspend/HandleLidSwitch=ignore/' /etc/systemd/logind.conf`
   then `sudo systemctl restart systemd-logind`. Enable Wake-on-LAN in BIOS + `ethtool`
   if you want it to sleep and wake on demand.

## MODELBEAST integration (I'll build this when the box exists)

The operator framework already shells out to tools; a **remote-CUDA operator** wraps
that pattern: rsync the input to `cuda_host:~/work/`, `ssh cuda_host` to run the CUDA
tool in its venv, rsync results back, register as assets. Planned operators:
- `sugar_mesh` — splat `.ply` → textured mesh (closes the Brush→mesh gap; the Mac can't extract meshes from splats).
- `gvhmr_mocap` — video → world-grounded SMPL → FBX (research-grade, replaces the cloud/manual path).

Add a `cuda_host` setting (the tailnet IP + user) to the vault so these operators know where to reach it. Fits in 11GB: SuGaR/2DGS/gsplat (~5-6GB), GVHMR/WHAM (light). Does NOT fit: FLUX, 20B+ models — those stay on the Mac.

## Reality check
Only worth it because the card's already owned. If you were buying, a used RTX 3090
(24GB, bf16) would be strictly better and unlock FLUX/video too. Turing's runway is
shrinking (newer 3D wheels drop 20-series), so treat this as "use the free card for
the CUDA-only leftovers," not a long-term foundation.