What is a render farm?
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What is a render farm?
Definition Render Farm
A render farm is a network of many computers (nodes) that process render jobs in parallel. Instead of calculating hundreds of stills or animation frames one after the other on a workstation, tasks are distributed across many machines - production becomes calculable and fast. This is essential for series visuals and animations in furniture & interiors; we show examples and workflows in the 3D render studio and the 3D animation studio.
Types: On-Prem, Cloud, Hybrid
How a render farm works (practice)
- Job is broken down into tasks (e.g. 240 frames).
- Queue Manager distributes, monitors, prioritizes - common solutions are AWS Thinkbox Deadline, Pixar Tractor and the open source project OpenCue.
- Renderer run via CLI (robust & automatable): Arnold via kick or Redshift via Command-Line Rendering.
- Distributed Rendering (DBR) for heavy stills: An image is distributed to several nodes - documented in Chaos V-Ray - Distributed Rendering.
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Learn more nowCPU vs. GPU - which is faster?
* Feature parity is engine-dependent. Before starting the project, render the desired AOVs/volumes/hair/dispersion as a test and check with your ACES/EXR setup (color space & layer structure).
Brief conclusion:
- Fast & iterative (series stills, variants, previews) → GPU has an advantage.
- Large & complex (lots of geometry/volumes, long sequences) → CPU or hybrid.
- For consistent campaign looks: Set up a clean color space/compositing (ACES + OpenEXR) and maintain material standards (PBR).
Pipeline fit for furniture & interior
Series with variants (fabrics, woods, handles), 360° spins or milieu campaigns benefit massively because their timing remains predictable. You can find practical references in our cases on Natuzzi, Bretz and interlübke.
Ensure quality: Color, formats, materials
- Standardize color space & tone mapping with ACES - Academy Color Encoding System for consistent looks across campaigns, devices and renderers.
- Ensure compositing flexibility with OpenEXR (multi-layer EXR for passes/lightmix).
- PBR material standard (Albedo/Roughness/Metalness) for repeatable results - basics in our glossary articles on PBR - Physically Based Rendering and Metalness Map.
Realistically calculate costs & planning
- Billing in node hours (CPU/GPU), plus manager license, render licenses, storage/traffic.
- Saving tips for batch jobs: AWS EC2 Spot Instances and Google Compute Engine Spot VMs offer significant discounts if your queue tolerates interruptions.
- Allow a buffer (10-20%) for re-renders (look tweaks) and transfers for cloud setups.
Selection checklist for brands & manufacturers
FAQ - Render Farm
How can I tell if our jobs are GPU- or VRAM-limited?
During the rendering process nvidia-smi provides you with live values on utilization and available graphics memory; if the memory utilization reaches the limit, VRAM is the bottleneck.
Which denoiser is suitable for farm pipelines with high image quality?
For CPU-side denoising Intel Open Image Denoise has proven itself; the denoiser can be easily automated and is integrated in many DCCs/renderers.
How do I keep color and tone mapping consistent across all render nodes?
Central color management with OpenColorIO ensures that workstations and farms use the same config - so looks remain stable across campaigns and renderers.
Which exchange format is the most robust for large productions?
Scaled for scene-based exchange and layout/lighting OpenUSD scales very well; references, variants and layering can be versioned cleanly.
Does headless rendering work reliably without a GUI?
Yes - automated queue jobs run stable via command line; the Blender render arguments show typical switches for frames, devices and output.
How do I control dependencies and batches in complex pipelines?
Procedural task graphs simplify orchestration; PDG/TOPs in Houdini models dependencies, distributes caches and renders in parallel on the farm.
How do I avoid "dependency hell" with tool versions?
Align your environment with the VFX Reference Platform ; the vintage stack (including compiler, Python, Qt) ensures reproducible builds in mixed toolchains.
Does multi-GPU with NVLink provide more usable memory?
NVIDIA NVLink does not bundle VRAM into a single pool, but accelerates peer-to-peer transfers between GPUs - helpful for workloads that require a lot of data exchange between cards.