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    Arches: A Cycle-Level Hardware Simulation Framework for Exploring Massively Parallel Ray Tracing Architectures
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Haydel, Jacob; Bhokare, Gaurav; Zeng, Kunnong; Hong, Pengpei; Kondguli, Sushant; Budge, Brian; Brunvand, Erik; Yuksel, Cem; Knoll, Aaron; Peters, Christoph
    We introduce Arches, a hardware simulation framework designed to explore and evaluate massively parallel ray-tracing architectures. Operating at the cycle level, Arches captures detailed performance metrics, including computational throughput, onchip data movement across processors, caches, and off-chip communication via an accurate memory system model. The framework is modular, allowing flexible configuration and interconnection of processor cores, caches, and custom hardware units, enabling easy exploration of diverse hardware architectures. Arches supports high-performance parallel execution, simulating complex ray tracing workloads to image completion. It leverages the GNU toolchain, allowing users to write C++ software targeting both the simulated architecture and native execution for debugging, including support for custom instructions to control specialized hardware components. The framework provides comprehensive performance instrumentation, offering insights into time-varying statistics across all modules and identifying performance bottlenecks. Our evaluations demonstrate that Arches delivers performance estimates closely matching real hardware, offering faster and more accurate simulations than existing open-source hardware simulators. Its modularity also makes it a valuable tool for exploring alternative parallel computing strategies for high-performance ray tracing, and its extensibility enables adaptation for other workloads or general-purpose computation.
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    Image-Based Spatio-Temporal Upsampling for Split Rendering
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Steiner, Michael; Köhler, Thomas; Radl, Lukas; Budge, Brian; Steinberger, Markus; Knoll, Aaron; Peters, Christoph
    Low-powered devices - such as small form factor head-mounted displays (HMDs) - struggle to deliver a smooth and highquality viewing experience, due to their limited power and rendering capabilities. Cloud rendering attempts to solve the quality issue, but leads to prohibitive latency and bandwidth requirements, hindering use with HMDs over mobile connections or even over Wifi. One solution - split rendering - where frames are partially rendered on the client device, often either requires geometry and rendering hardware, or struggles to generate frames faithfully under viewpoint changes and object motion. Our method enables spatio-temporal interpolation via bidirectional reprojection to efficiently generate intermediate frames in a split rendering setting, while limiting the communication cost and relying purely on image-based rendering. Furthermore, our method is robust to modest connectivity issues and handles effects such as dynamic smooth shadows.