Exploring Extended Reality with ILLIXR: A New Playground for Architecture Research [article]

Muhammad Huzaifa, Rishi Desai, Samuel Grayson, Xutao Jiang, Ying Jing, Jae Lee, Fang Lu, Yihan Pang, Joseph Ravichandran, Finn Sinclair, Boyuan Tian, Hengzhi Yuan (+2 others)
<span title="2021-03-03">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
As we enter the era of domain-specific architectures, systems researchers must understand the requirements of emerging application domains. Augmented and virtual reality (AR/VR) or extended reality (XR) is one such important domain. This paper presents ILLIXR, the first open source end-to-end XR system (1) with state-of-the-art components, (2) integrated with a modular and extensible multithreaded runtime, (3) providing an OpenXR compliant interface to XR applications (e.g., game engines), and
more &raquo; ... 4) with the ability to report (and trade off) several quality of experience (QoE) metrics. We analyze performance, power, and QoE metrics for the complete ILLIXR system and for its individual components. Our analysis reveals several properties with implications for architecture and systems research. These include demanding performance, power, and QoE requirements, a large diversity of critical tasks, inter-dependent execution pipelines with challenges in scheduling and resource management, and a large tradeoff space between performance/power and human perception related QoE metrics. ILLIXR and our analysis have the potential to propel new directions in architecture and systems research in general, and impact XR in particular. ILLIXR is open-source and available at https://illixr.github.io
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