Exactly what is a Render farm?

A render farm is a high-performance computer system, e.g. a computer cluster, intended to render computer-generated imagery (CGI), typically for film and television visual effects.

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Origin of the term

The term render farm was made through the production of the Autodesk 3D Studio animated short The Bored Room in July 1990 when, to meet up an unrealistic deadline, an area filled up with Compaq 386 computers was configured to accomplish the rendering. At that period the machine wasn’t networked so each computer needed to be set up yourself to render a particular animation sequence. The rendered images would then be ‘harvested’ with a rolling platform to a large-format optical storage drive, then loaded frame by frame to a Sony CRV disc.

The Autodesk technician assigned to regulate this early render farm (Jamie Clay) had a standard habit of wearing farmer’s overalls and the item manager for this program (Bob Bennett) joked that what Clay was doing was farming the frames and in those days he named the range of computers a render farm. Within the next release of this program, Autodesk introduced network rendering, making the work of owning a render farm significantly easier. A BTS of The Bored Room doesn’t show Clay in the overalls but does provide a glimpse of the production environment.

A render farm differs from a render wall, which is a networked, tiled display used for real-time rendering. The rendering of images can be an extremely parallelizable activity, as frames and sometimes tiles could possibly be calculated independently of others, with the principal communication between processors being the upload of the original source material, such as for example models and textures, and the download of the finished images.

Render capacity

Over the decades, advances in computer capability have allowed a graphic to take less time to render. However, the increased computation is normally appropriated to meet up demands to accomplish state-of-the-art image quality. While simple images could be produced rapidly, even more realistic and complicated higher-resolution images is now able to be stated in more reasonable quantities of time. The period spent producing images can be limited by production time-lines and deadlines, and the desire to create high-quality work drives the need for increased computing power, rather than simply wanting the same images created faster. Project like the Big and Ugly Rendering Project have been available for rendering images using Blender across both widely distributed networks and local networks.


To regulate large farms, one must introduce a queue manager that automatically distributes processes to a variety of processors. Each “process” could be the rendering of just one 1 full image, a few images, or simply a sub-section (or tile) of a graphic. The program is generally a client-server package that facilitates communication in the middle of your processors and the queue manager, even though some queues have no central manager. Some typically common top features of queue managers are: re-prioritization of the queue, management of software licenses, and algorithms to best optimize throughput predicated on numerous kinds of hardware in the farm. Software licensing handled by a queue manager might involve dynamic allocation of licenses to available CPUs or even cores within CPUs. A tongue-in-cheek job title for systems engineers who work primarily in the maintenance and monitoring of a render farm is a render wrangler to help expand the “farm” theme. This job title is seen in film credits.

Beyond on-site render farms, cloud-based render farm options have been facilitated by the rise of high-speed Usage of the web. Many cloud computing services, including some centered on rendering, offer render farm services which bill limited to processor period used. Understanding the cost or processing time required to complete rendering is unpredictable so render farms bill using GHz per hour. Those considering outsourcing their renders to a farm or to the cloud can do a number of things to improve their predictions and reduce their costs. These services eliminate the need for a customer to build and maintain their own rendering solution. Another phenomenon is collaborative rendering, in which users join a network of animators who contribute their processing power to the group. However, this offers technological and security limitations.