R2E2: Low-Latency Path Tracing of Terabyte-Scale Scenes using Thousands of Cloud CPUs
Channel: Sadjad Fouladi
Date: 2022-11-14

https://r2e2.dev

R2E2 is a research project that explores the viability of path tracing massive scenes using a “supercomputer” constructed on-the-fly from thousands of small cloud computing nodes.

R2E2 is a scene decomposition-based parallel renderer that rapidly acquires thousands of cloud CPU cores, loads scene geometry from a pre-built scene BVH into the aggregate memory of these nodes in parallel, and performs full path-traced global illumination. Scenes with up to a terabyte of geometry and texture data can be path traced using thousands of tiny compute nodes in tens of seconds.

00:00 — Introduction
00:52 — Goals
01:40 — Challenges
03:43 — Architecture
10:30 — Demo
11:55 — Evaluation
14:35 — Summary & Conclusion