For their acclaimed 2020 film, Soul, Pixar began working with VAST in 2018 as it pioneered new animation techniques using volumetric rendering.
Pixar Animation Studios, a subsidiary of the Walt Disney Company, has selected VAST Data as the key data platform collaborator for the company’s data-intensive feature animation production, including its latest, Elemental.
Pixar began working with VAST in 2018 as it first pioneered new animation techniques using volumetric rendering for their acclaimed 2020 film titled, Soul. Its newest feature, Elemental, required a new way to scale these detailed volumetric characters and environments. Unlike the geometric surfaces and materials used in earlier Pixar projects, the broadly-applied volumetric animation methods used in Elemental created six times the data footprint and computational demands for data than that of Soul.
To meet the technical requirements of the Pixar creative team, Pixar turned to the VAST Data Platform to power the demanding render pipeline for Elemental as well as Pixar’s other ongoing and future productions. By moving 7.3 petabytes of data to a single datastore cluster that is managed across one high-performance namespace organized from low-cost flash – VAST provides real-time access to keep Pixar’s renderfarm constantly busy while enabling improved observability and analytics, simplified collaboration and development across multiple productions running at the same time, and laying the foundation to leverage AI and deep learning for future films.
Speaking about the collaboration, Eric Bermender, Head of Data Center & IT Infrastructure at Pixar Animation Studios, said: “Pixar is the world’s leading innovator in animation, and in order to continue to deliver new stories, breath-taking visual environments and memorable characters – we require the industry’s most innovative technologies to help us bring the animators’ vision to life. Elemental is the most technically complex film that Pixar has ever made, but with VAST we were able to build beyond our current level of animation and consider new techniques that no one had ever considered before because we didn’t have the technology in place to support it. VAST’s technology has allowed us to change the way we store and access data while also opening the door to new potential visual pipelines.”
In collaboration with VAST, Pixar has optimised data access, improved operational resilience, engaged audiences with visually stunning storytelling, and built the foundation for future generations of AI-powered cinematography.
The compute requirements for Elemental demanded fast and concurrent data access from hundreds of thousands of processors used in the render pipeline. VAST delivered fast, uninterrupted performance even during the film’s peak rendering usage, requiring nearly two petabytes of capacity at one time (compared to previous films over the last five years using only about 300 to 500 terabytes of capacity).
With different productions in different stages of rendering at any given time, Pixar depends on VAST’s Data Platform to handle the volumetric demands of several films being developed at the same time.
The parallel data access, high-performance and scale of the VAST Data Platform allowed Pixar to render nearly 150,000 volumetric frames in Elemental alone.
Using VAST’s Data Platform, Pixar projects are now available for the types of high-speed data processing required to employ new animation techniques using machine learning and deep learning training models for automated and improved production processes.
Jeff Denworth, Co-Founder of VAST Data, added: “At VAST, we’re so proud to work with Pixar as they create timeless cinematic magic by simultaneously pushing the boundaries of story-telling and technology. For Elemental and future films, we’re delivering a data platform that powers the animation and rendering workflows for their most data-intensive and computationally heavy projects, while enabling its AI and ML pipeline for the future in order to further the ambitions of Pixar artists and the stories they’re able to tell.”
