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

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arxiv 2004.04643 v2 pith:K65DWOJW submitted 2020-03-26 cs.DC cs.ET

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

classification cs.DC cs.ET
keywords illixrarchitecturemetricsperformancepowerrealityresearchsystems
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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 (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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