- Who this is for
- Users with laptops or multi-GPU workstations troubleshooting device choice.
- Best fit
- Use this when the render should use a specific GPU, or when one GPU is reserved for display work.
Workflow
- Export or collect the V-Ray Standalone scene files you want to render, usually .vrscene or .vrs files.
- Confirm that the V-Ray Standalone executable path is configured and valid on the machine that will render.
- Add the scene files to the queue, check output settings, and put jobs in the order they should run.
- Choose the useful safeguards for the job, such as frame range, skip existing frames, resumable rendering, output format, and log review.
- Start the local queue and monitor status, logs, and completed outputs from one dashboard.
Where it fits
A local queue can show logs for each job so GPU selection problems are easier to catch.
- GPU device check
- Log confirmation
- Multi-GPU workflow
This is for local V-Ray Standalone queues. It does not provide worker provisioning, central asset sync, accounting, cloud bursting, or facility-wide scheduling.
FAQ
Why is V-Ray using the wrong GPU?
On multi-GPU workstations, V-Ray GPU device selection can depend on environment and platform settings. Run a small test and confirm the log before queueing.
Is this a cloud render farm?
No. V-Raykally is designed for local V-Ray Standalone queues on the artist workstation or a local render machine.
What kind of V-Ray files does this workflow target?
The workflow targets V-Ray Standalone scene files such as .vrscene and .vrs, with output and frame options handled around the local V-Ray executable.