ILLIXR: Enabling End-to-End Extended Reality Research
Muhammad Huzaifa, Rishi Desai, Samuel Grayson, Xutao Jiang, Ying Jing, Jae Lee, Lu Fang, Yihan Pang, Joseph Ravichandran, Finn Sinclair, Boyuan Tian, Hengzhi Yuan, Jeffrey Zhang, Sarita V. Adve
Abstract
An increasing number of edge systems have large computational demands, stringent resource constraints, and end-to-end quality-driven goodness metrics. Architects have embraced domain-specific accelerators to meet the demands of such systems. We make the case for research that shifts emphasis from domain-specific accelerators to domain-specific systems, with a consequent shift from evaluations using benchmarks that are collections of independent applications to those using testbeds that are full integrated systems. We describe extended reality (XR) as an exciting domain motivating such domain-specific systems research, but hampered by the lack of an end-to-end evaluation testbed. We present ILLIXR (Illinois Extended Reality testbed), the first fully open source XR system and research testbed. ILLIXR enables system innovations with end-to-end co-designed hardware, compiler, OS, and algorithm, and driven by end-user perceived quality-of-experience (QoE) metrics. Using ILLIXR, we perform the first comprehensive quantitative analysis of performance, power, and QoE for a complete XR system and its individual components. We describe several implications of our results that propel new directions in architecture, systems, and algorithm research for domain-specific systems in general, and XR in particular, all enabled by ILLIXR.