Fusion-3D: Integrated Acceleration for Instant 3D Reconstruction and Real-Time Rendering

Recent breakthroughs in Neural Radiance Field (NeRF) based 3D reconstruction and rendering have spurred the possibility of immersive experiences in augmented and virtual reality (AR/VR). However, current NeRF acceleration techniques are still inadequate for real-world AR/VR applications due to: 1) the lack of end-to-end pipeline acceleration support, which causes impractical off-chip bandwidth demands for edge devices, and 2) limited scalability in handling large-scale scenes. To tackle these limitations, we have developed an end-to-end, scalable 3D acceleration framework called Fusion-3D, capable of instant scene reconstruction and real-time rendering. Fusion-3D achieves these goals through two key innovations: 1) an optimized end-to-end processor for all three stages of the NeRF pipeline, featuring dynamic scheduling and hardware-aware sampling in the first stage, and a shared, reconfigurable pipeline with mixed-precision arithmetic in the second and third stages; 2) a multi-chip architecture for handling large-scale scenes, integrating a three-level hierarchical tiling scheme that minimizes inter-chip communication and balances workloads across chips. Extensive experiments validate the effectiveness of Fusion-3D in facilitating real-time, energy-efficient 3D reconstruction and rendering. Specifically, we tape out a prototype chip in 28nm CMOS to evaluate the effectiveness of the proposed end-to-end processor. Extensive simulation based on the on-silicon measurements demonstrates a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{2.5}\times$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{6}\times$</tex> throughput improvement in training and inference, respectively, compared to state-of-the-art accelerators. Furthermore, to assess the multi-chip architecture, we integrate four chips into a single PCB as a prototype. Further simulation results show that the multi-chip system achieves a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{7.3}\times$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{6.5}\times$</tex> throughput improvement in training and inference, respectively, over the Nvidia 2080Ti GPU. To the best of our knowledge, Fusion-3D is the first to achieve both instant (≤ 2 seconds) 3D reconstruction and real-time (≥ 30 FPS) rendering, while only requiring the bandwidth of the most commonly used USB port (0.625 GB/s, 5 Gbps) in edge devices for off-chip communication.

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Publication Details

Published
2024-11-02
DOI
https://doi.org/10.1109/micro61859.2024.00016
Citations
17
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
14.19

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article

Fusion-3D: Integrated Acceleration for Instant 3D Reconstruction and Real-Time Rendering

Bao Guo, Yingyan Lin, Zhifan Ye, Cheng Wan et al.
17 citations
3D Surveying and Cultural Heritage
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article

Fusion-3D: Integrated Acceleration for Instant 3D Reconstruction and Real-Time Rendering

Bao Guo, Yingyan Lin, Zhifan Ye, Cheng Wan, Sixu Li, Chaojian Li, Wenbo Zhu, Jingqun Zhang, Yang Zhao
article en
17 citations

Abstract

Recent breakthroughs in Neural Radiance Field (NeRF) based 3D reconstruction and rendering have spurred the possibility of immersive experiences in augmented and virtual reality (AR/VR). However, current NeRF acceleration techniques are still inadequate for real-world AR/VR applications due to: 1) the lack of end-to-end pipeline acceleration support, which causes impractical off-chip bandwidth demands for edge devices, and 2) limited scalability in handling large-scale scenes. To tackle these limitations, we have developed an end-to-end, scalable 3D acceleration framework called Fusion-3D, capable of instant scene reconstruction and real-time rendering. Fusion-3D achieves these goals through two key innovations: 1) an optimized end-to-end processor for all three stages of the NeRF pipeline, featuring dynamic scheduling and hardware-aware sampling in the first stage, and a shared, reconfigurable pipeline with mixed-precision arithmetic in the second and third stages; 2) a multi-chip architecture for handling large-scale scenes, integrating a three-level hierarchical tiling scheme that minimizes inter-chip communication and balances workloads across chips. Extensive experiments validate the effectiveness of Fusion-3D in facilitating real-time, energy-efficient 3D reconstruction and rendering. Specifically, we tape out a prototype chip in 28nm CMOS to evaluate the effectiveness of the proposed end-to-end processor. Extensive simulation based on the on-silicon measurements demonstrates a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{2.5}\times$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{6}\times$</tex> throughput improvement in training and inference, respectively, compared to state-of-the-art accelerators. Furthermore, to assess the multi-chip architecture, we integrate four chips into a single PCB as a prototype. Further simulation results show that the multi-chip system achieves a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{7.3}\times$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{6.5}\times$</tex> throughput improvement in training and inference, respectively, over the Nvidia 2080Ti GPU. To the best of our knowledge, Fusion-3D is the first to achieve both instant (≤ 2 seconds) 3D reconstruction and real-time (≥ 30 FPS) rendering, while only requiring the bandwidth of the most commonly used USB port (0.625 GB/s, 5 Gbps) in edge devices for off-chip communication.

Georgia Institute of Technology (US)
National Science Foundation
Openalex Percentile: Top 1%
3D Surveying and Cultural Heritage
14.19
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