27ce69782d
Ready-to-follow checklist for standing up a headless Linux + eGPU CUDA node to offload the CUDA-only 3D/mocap jobs the Mac can't run (splat->mesh, GVHMR mocap). Bare-metal Linux required (no VM GPU passthrough on Mac hosts). Planned remote-CUDA operators: sugar_mesh, gvhmr_mocap. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
64 lines
3.2 KiB
Markdown
64 lines
3.2 KiB
Markdown
# 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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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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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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## Do this at the shop (once)
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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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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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```
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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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```
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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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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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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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## MODELBEAST integration (I'll build this when the box exists)
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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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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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## 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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