research-article

Active thread compaction for GPU path tracing

Author:

Ingo WaldAuthors Info & Claims

HPG '11: Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics

Pages 51 - 58

https://doi.org/10.1145/2018323.2018331

Published: 05 August 2011 Publication History

Abstract

Modern GPUs like NVidia's Fermi internally operate in a SIMD manner by ganging multiple (32) scalar threads together into SIMD warps; if a warp's threads diverge, the warp serially executes both branches, temporarily disabling threads that are not on that path. In this paper, we explore and thoroughly analyze the concept of active thread compaction---i.e., the process of taking multiple partially-filled warps and compacting them to fewer but fully utilized warps---in the context of a CUDA path tracer. Our results show that this technique can indeed lead to significant improvements in SIMD utilization, and corresponding savings in the amount of work performed; however, they also show that certain inadequacies of today's hardware wipe out most of the achieved gains, leaving bottom-up speed-ups of a mere 12--16%. We believe our analysis of why this is the case will provide insight to other researchers experimenting with this technique in different contexts.

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Cited By

Xiang WLiu FTan ZLi DXu PLiu MKou Q(2024)Faster Ray Tracing through Hierarchy Cut CodeComputer Graphics Forum10.1111/cgf.1522643:7Online publication date: 24-Oct-2024
https://doi.org/10.1111/cgf.15226
Damani SStephenson MRangan RJohnson DKulkami RKeckler S(2022)GPU Subwarp Interleaving2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA53966.2022.00090(1184-1197)Online publication date: Apr-2022
https://doi.org/10.1109/HPCA53966.2022.00090
Liu LChang WDemoullin FChou YSaed MPankratz DNowicki TAamodt T(2021)Intersection Prediction for Accelerated GPU Ray TracingMICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3466752.3480097(709-723)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3466752.3480097
Show More Cited By

Index Terms

Active thread compaction for GPU path tracing
1. Computing methodologies
  1. Computer graphics
    1. Rendering
      1. Ray tracing

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Information

Published In

cover image ACM Conferences

HPG '11: Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics

August 2011

185 pages

ISBN:9781450308960

DOI:10.1145/2018323

Editor:
Stephen N. Spencer
University of Washington
,
General Chairs:
John Owens
University of California at Davis
,
Matt Pharr
Intel
,
Program Chairs:
Carsten Dachsbacher
Karlsruhe Institute of Technology
,
William Mark
Intel
,
Jacopo Pantaleoni
NVIDIA

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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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: 05 August 2011

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HPG '11: High Performance Graphics

August 5 - 7, 2011

British Columbia, Vancouver, Canada

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Overall Acceptance Rate 15 of 44 submissions, 34%

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Cited By

Xiang WLiu FTan ZLi DXu PLiu MKou Q(2024)Faster Ray Tracing through Hierarchy Cut CodeComputer Graphics Forum10.1111/cgf.1522643:7Online publication date: 24-Oct-2024
https://doi.org/10.1111/cgf.15226
Damani SStephenson MRangan RJohnson DKulkami RKeckler S(2022)GPU Subwarp Interleaving2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA53966.2022.00090(1184-1197)Online publication date: Apr-2022
https://doi.org/10.1109/HPCA53966.2022.00090
Liu LChang WDemoullin FChou YSaed MPankratz DNowicki TAamodt T(2021)Intersection Prediction for Accelerated GPU Ray TracingMICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3466752.3480097(709-723)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3466752.3480097
Pankratz DNowicki TEltantawy AAmaral JLee J(2021)Vulkan visionProceedings of the 2021 IEEE/ACM International Symposium on Code Generation and Optimization10.1109/CGO51591.2021.9370320(137-149)Online publication date: 27-Feb-2021
https://dl.acm.org/doi/10.1109/CGO51591.2021.9370320
Meister DBoksansky JGuthe MBittner J(2020)On Ray Reordering Techniques for Faster GPU Ray TracingSymposium on Interactive 3D Graphics and Games10.1145/3384382.3384534(1-9)Online publication date: 5-May-2020
https://dl.acm.org/doi/10.1145/3384382.3384534
Köster MGroß JKrüger A(2020)Massively Parallel Rule-Based Interpreter Execution on GPUs Using Thread CompactionInternational Journal of Parallel Programming10.1007/s10766-020-00670-2Online publication date: 24-Jun-2020
https://doi.org/10.1007/s10766-020-00670-2
Kao CTseng LHsu W(2018)A pipeline-based heterogeneous framework for efficient synthetic light field renderingACM SIGAPP Applied Computing Review10.1145/3212069.321207118:1(19-29)Online publication date: 30-Apr-2018
https://dl.acm.org/doi/10.1145/3212069.3212071
Khorasani FEsfeden HAbu-Ghazaleh NSarkar VOskin MInoue K(2018)In-register parameter caching for dynamic neural nets with virtual persistent processor specializationProceedings of the 51st Annual IEEE/ACM International Symposium on Microarchitecture10.1109/MICRO.2018.00038(377-389)Online publication date: 20-Oct-2018
https://dl.acm.org/doi/10.1109/MICRO.2018.00038
Kao CHsu W(2018)Exploring hidden coherency of Ray-Tracing for heterogeneous systems using online feedback methodologyThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-017-1403-834:5(633-643)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1007/s00371-017-1403-8
Zellmann SLang UHullin MKlein RSchultz TYao A(2017)C++ compile time polymorphism for ray tracingProceedings of the conference on Vision, Modeling and Visualization10.2312/vmv.20171268(129-136)Online publication date: 25-Sep-2017
https://dl.acm.org/doi/10.2312/vmv.20171268
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