Hardware Setup

Provision the box, choose how inference runs (GPU vs CPU), and wire it into your plant network before installing the software.

Supported hardware

Tier	CPU	GPU	RAM	Inference mode
Lite	8-core x86_64	—	16 GB	CPU-only
Pro	8-core x86_64	NVIDIA T4 / A2	32 GB	TensorRT-ready
Max	16-core x86_64	NVIDIA L4 / A10	64 GB	Multi-model
Edge	NVIDIA Jetson (Orin / Xavier)	integrated	16–32 GB	TensorRT on L4T (arm64)

Edge GPU prerequisites

If the box has an NVIDIA GPU (Pro, Max, or Jetson tiers), the operating-system image must have these in place before you install Xisom:

• A compatible NVIDIA driver for the GPU.
• The NVIDIA Container Toolkit, so containers can access the GPU.
• For Jetson modules: an L4T (arm64) base image with the toolkit wired in.

Note

On a CPU-only (Lite) box you need none of the above — inference runs on the CPU.

Execution-provider modes

The inference runtime picks an execution provider that matches your hardware. You choose the matching profile when you install (see Offline Bundle Install).

TensorRT (GPU)

Best performance. Uses the NVIDIA GPU with TensorRT acceleration for the lowest inference latency. Available on Pro, Max, and Jetson tiers.

• Requires the NVIDIA driver + Container Toolkit on the host.
• The first run compiles a TensorRT engine — expect a 2–3 minute warm-up before the inference service reports healthy.

CUDA (GPU)

GPU acceleration without TensorRT engine compilation. Runs models on the GPU via CUDA. A good fallback when a model is not TensorRT-compatible, or to avoid the first-run compile delay.

• Requires the NVIDIA driver + Container Toolkit on the host.

CPU

No GPU required. Inference runs entirely on the CPU. Use the amd64-cpu install profile on Lite-tier boxes or anywhere a GPU is unavailable.

• Highest portability, higher latency than the GPU modes.

Tip

Pick the GPU mode that matches your model. If a GPU box falls back to CPU unexpectedly, the dashboard shows the active execution provider so you can spot it. See Monitoring.

Network requirements

• One LAN port for management (dashboard + API).
• An optional second port for the OT network where your sensors and PLCs live.
• Outbound HTTPS to your license and update servers, if used (configurable allowlist). Air-gapped sites install from the offline bundle and need no outbound access.

First boot

1. Connect power and both network ports.
2. Browse to https://your-device-ip (replace with the box’s management IP).
3. Sign in with the admin account created during install.
4. Continue to Connect an input datasource.

If something goes wrong

• GPU box falling back to CPU, or stuck unhealthy on first boot — see the Troubleshooting runbook.

Next steps

Install from the offline bundle Air-gapped, USB-shippable install runbook.

Connect a datasource Stream sensor and process data in.