Workers on NVIDIA unified-memory hardware (DGX Spark / GB10, Jetson AGX Thor,
Jetson Orin/Xavier/Nano) were reporting `available_vram=0` back to the frontend,
so the Nodes UI showed the node as fully used even when most of the unified
memory was actually free.
Three causes addressed:
* `isTegraDevice` only matched `/sys/devices/soc0/family == "Tegra"`. DGX Spark
(SBSA) reports JEDEC codes there instead — `jep106:0426` for the NVIDIA
manufacturer — so the Tegra/unified-memory fallback never ran. Renamed to
`isNVIDIAIntegratedGPU` and extended to also match `jep106:0426[:*]` via
`/sys/devices/soc0/soc_id`.
* The unified-iGPU code defaulted the device name to `"NVIDIA Jetson"` when
`/proc/device-tree/model` was missing. That's what happens for Thor inside a
docker container, and always on DGX Spark. New `nvidiaIntegratedGPUName`
resolves via dt-model → `/sys/devices/soc0/machine` → `soc_id` lookup
(`jep106:0426:8901` → `"NVIDIA GB10"`) so the Nodes UI labels the box
correctly.
* Worker heartbeat sent `available_vram=0` (or total-as-available) when VRAM
usage was momentarily unknown — e.g. when `nvidia-smi` intermittently failed
with `waitid: no child processes` under containers without `--init`. Each
such heartbeat overwrote the DB and made the UI flip to "fully used".
`heartbeatBody` now omits `available_vram` in that case so the DB keeps its
last good value.
Also updates the commented GPU blocks in both compose files with
`NVIDIA_DRIVER_CAPABILITIES=compute,utility`, `capabilities: [gpu, utility]`,
and `init: true`, and documents the requirement in the distributed-mode and
nvidia-l4t pages. Without `utility`, NVML/`nvidia-smi` are absent inside the
container, which is what put the DGX Spark worker into the buggy fallback in
the first place.
Detection verified on live hardware (dgx.casa / GB10 and 192.168.68.23 / Thor)
by running a cross-compiled probe of the new helpers on both host and inside
the worker container.
Assisted-by: Claude:opus-4.7 [Claude Code]
