docs: CUDA worker — add Win11 + WSL2 path (recommended, no reinstall)
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>
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# CUDA Worker Setup — T490s + 2080 Ti eGPU on the tailnet
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Goal: a headless Linux box with the RTX 2080 Ti (11GB) eGPU, live on Tailscale, that
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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 a ThinkPad and not the Intel iMac:** no T2 chip = no Secure-Boot/Thunderbolt
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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) — it's a *compatibility*
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box, not a performance one. It will not beat the M3 Ultra at anything the Mac
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already does; it only unlocks the CUDA-locked tail.
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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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## Do this at the shop (once)
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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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1. **Ubuntu 24.04 LTS**, bare metal (dual-boot Win11 or wipe — bare-metal, NOT a VM;
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macOS/Windows hypervisors can't pass a physical GPU through, so a Linux VM can't
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do CUDA on the eGPU).
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---
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2. **Thunderbolt authorize the eGPU** (plug in the Razer Core first):
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```bash
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sudo apt install bolt
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boltctl list # find the enclosure UUID
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boltctl enroll --policy auto <UUID>
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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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3. **NVIDIA driver + CUDA:**
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```bash
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sudo ubuntu-drivers autoinstall # or the latest official driver branch
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sudo apt install nvidia-cuda-toolkit
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sudo reboot
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nvidia-smi # must list the 2080 Ti over Thunderbolt
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[wsl2]
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networkingMode=mirrored
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```
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If it doesn't appear: confirm the eGPU was connected at boot, re-check `boltctl`,
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ensure the `thunderbolt` module loads before `nvidia_drm`.
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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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4. **Tailscale:**
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```bash
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curl -fsSL https://tailscale.com/install.sh | sh
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sudo tailscale up --ssh # --ssh lets the M3 Ultra SSH in over the tailnet
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tailscale ip -4 # note this IP → put it in MODELBEAST settings
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```
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## Path B — Bare-metal Ubuntu (leaner/lower-power, if you'd rather wipe Win11)
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5. **Headless / low-power:** run lid-closed →
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`sudo sed -i 's/#HandleLidSwitch=suspend/HandleLidSwitch=ignore/' /etc/systemd/logind.conf`
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then `sudo systemctl restart systemd-logind`. Enable Wake-on-LAN in BIOS + `ethtool`
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if you want it to sleep and wake on demand.
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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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## MODELBEAST integration (I'll build this when the box exists)
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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 pattern: rsync the input to `cuda_host:~/work/`, `ssh cuda_host` to run the CUDA
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tool in its venv, rsync results back, register as assets. Planned operators:
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- `sugar_mesh` — splat `.ply` → textured mesh (closes the Brush→mesh gap; the Mac can't extract meshes from splats).
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- `gvhmr_mocap` — video → world-grounded SMPL → FBX (research-grade, replaces the cloud/manual path).
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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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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.
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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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Only worth it because the card's already owned. If you were buying, a used RTX 3090
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(24GB, bf16) would be strictly better and unlock FLUX/video too. Turing's runway is
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shrinking (newer 3D wheels drop 20-series), so treat this as "use the free card for
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the CUDA-only leftovers," not a long-term foundation.
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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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