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An energy and bandwidth efficient ray tracing architecture

Authors:

Konstantin Shkurko,

Al DavisAuthors Info & Claims

HPG '13: Proceedings of the 5th High-Performance Graphics Conference

Pages 121 - 128

https://doi.org/10.1145/2492045.2492058

Published: 19 July 2013 Publication History

Abstract

We propose two hardware mechanisms to decrease energy consumption on massively parallel graphics processors for ray tracing while keeping performance high. First, we use a streaming data model and configure part of the L2 cache into a ray stream memory to enable efficient data processing through ray reordering. This increases the L1 hit rate and reduces off-chip memory accesses substantially. Second, we employ reconfigurable special-purpose pipelines than are constructed dynamically under program control. These pipelines use shared execution units (XUs) that can be configured to support the common compute kernels that are the foundation of the ray tracing algorithm, such as acceleration structure traversal and triangle intersection. This reduces the overhead incurred by memory and register accesses. These two synergistic features yield a ray tracing architecture that significantly reduces both power consumption and off-chip memory traffic when compared to a more traditional cache only approach.

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Cited By

Vasiou EShkurko KBrunvand EYuksel C(2022)Mach-RT: A Many Chip Architecture for High Performance Ray TracingIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.302104828:3(1585-1596)Online publication date: 1-Mar-2022
https://doi.org/10.1109/TVCG.2020.3021048
Meister DOgaki SBenthin CDoyle MGuthe MBittner J(2021)A Survey on Bounding Volume Hierarchies for Ray TracingComputer Graphics Forum10.1111/cgf.14266240:2(683-712)Online publication date: 4-Jun-2021
https://doi.org/10.1111/cgf.142662
Lin DVasiou EYuksel CKopta DBrunvand E(2020)Hardware-Accelerated Dual-Split TreesProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/34061853:2(1-21)Online publication date: 26-Aug-2020
https://dl.acm.org/doi/10.1145/3406185
Show More Cited By

Index Terms

An energy and bandwidth efficient ray tracing architecture
1. Computing methodologies
  1. Computer graphics
    1. Graphics systems and interfaces
    2. Rendering
      1. Ray tracing
  2. Parallel computing methodologies

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Information & Contributors

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Published In

cover image ACM Conferences

HPG '13: Proceedings of the 5th High-Performance Graphics Conference

July 2013

149 pages

ISBN:9781450321358

DOI:10.1145/2492045

General Chairs:
Steve Molnar
NVIDIA
,
Jens Krüger
IVDA Saarland University, Germany
,
Program Chairs:
Tim Purcell
NVIDIA
,
Warren Hunt
Google

Copyright © 2013 ACM.

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
EUROGRAPHICS: The European Association for Computer Graphics

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2013

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Division of Computer and Network Systems

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HPG '13

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SIGGRAPH
EUROGRAPHICS

HPG '13: High Performance Graphics

July 19 - 21, 2013

California, Anaheim

Acceptance Rates

HPG '13 Paper Acceptance Rate 15 of 44 submissions, 34%;

Overall Acceptance Rate 15 of 44 submissions, 34%

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Cited By

Vasiou EShkurko KBrunvand EYuksel C(2022)Mach-RT: A Many Chip Architecture for High Performance Ray TracingIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.302104828:3(1585-1596)Online publication date: 1-Mar-2022
https://doi.org/10.1109/TVCG.2020.3021048
Meister DOgaki SBenthin CDoyle MGuthe MBittner J(2021)A Survey on Bounding Volume Hierarchies for Ray TracingComputer Graphics Forum10.1111/cgf.14266240:2(683-712)Online publication date: 4-Jun-2021
https://doi.org/10.1111/cgf.142662
Lin DVasiou EYuksel CKopta DBrunvand E(2020)Hardware-Accelerated Dual-Split TreesProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/34061853:2(1-21)Online publication date: 26-Aug-2020
https://dl.acm.org/doi/10.1145/3406185
Санжаров ВSanzharov VГорбоносов АGorbonosov AФролов ВFrolov VВолобой АVoloboy A(2019)Examination of the Nvidia RTXGraphiCon'2019 Proceedings. Volume 210.30987/graphicon-2019-2-7-12(7-12)Online publication date: 5-Nov-2019
https://doi.org/10.30987/graphicon-2019-2-7-12
Vasiou EShkurko KBrunvand EYuksel C(2019)Mach-RTProceedings of the Conference on High-Performance Graphics10.2312/hpg.20191188(1-6)Online publication date: 8-Jul-2019
https://dl.acm.org/doi/10.2312/hpg.20191188
Vasiou EShkurko KMallett IBrunvand EYuksel C(2018)A detailed study of ray tracing performanceThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-018-1532-834:6-8(875-885)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s00371-018-1532-8
Lü YHuang LShen LWang ZHunter HMoreno JEmer JSanchez D(2017)Unleashing the power of GPU for physically-based rendering via dynamic ray shufflingProceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3123939.3124532(560-573)Online publication date: 14-Oct-2017
https://dl.acm.org/doi/10.1145/3123939.3124532
Shkurko KGrant TKopta DMallett IYuksel CBrunvand EMcGuire MPatney A(2017)Dual streaming for hardware-accelerated ray tracingProceedings of High Performance Graphics10.1145/3105762.3105771(1-11)Online publication date: 28-Jul-2017
https://dl.acm.org/doi/10.1145/3105762.3105771
Deng YNi YLi ZMu SZhang W(2017)Toward Real-Time Ray TracingACM Computing Surveys10.1145/310406750:4(1-41)Online publication date: 30-Aug-2017
https://dl.acm.org/doi/10.1145/3104067
Kopta DBrunvand E(2017)Power and energy implications of misunderstanding DRAM2017 Eighth International Green and Sustainable Computing Conference (IGSC)10.1109/IGCC.2017.8323589(1-6)Online publication date: Oct-2017
https://doi.org/10.1109/IGCC.2017.8323589
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