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RT-kNNS Unbound: Using RT Cores to Accelerate Unrestricted Neighbor Search

Authors:

Vani Nagarajan,

Durga Mandarapu,

Milind KulkarniAuthors Info & Claims

ICS '23: Proceedings of the 37th International Conference on Supercomputing

Pages 289 - 300

https://doi.org/10.1145/3577193.3593738

Published: 21 June 2023 Publication History

Abstract

The problem of identifying the k-Nearest Neighbors (kNNS) of a point has proven to be very useful both as a standalone application and as a subroutine in larger applications. Given its far-reaching applicability in areas such as machine learning and point clouds, extensive research has gone into leveraging GPU acceleration to solve this problem. Recent work has shown that using Ray Tracing cores in recent GPUs to accelerate kNNS is much more efficient compared to traditional acceleration using shader cores. However, the existing translation of kNNS to a ray tracing problem imposes a constraint on the search space for neighbors. Due to this, we can only use RT cores to accelerate fixed-radius kNNS, which requires the user to set a search radius a priori and hence can miss neighbors. In this work, we propose TrueKNN, the first unbounded RT-accelerated neighbor search. TrueKNN adopts an iterative approach where we incrementally grow the search space until all points have found their k neighbors. We show that our approach is orders of magnitude faster than existing approaches and can even be used to accelerate fixed-radius neighbor searches.

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Cited By

Lv YZhang KWang ZZhang XLee RHe ZJing YWang X(2024)RTScan: Efficient Scan with Ray Tracing CoresProceedings of the VLDB Endowment10.14778/3648160.364818317:6(1460-1472)Online publication date: 3-May-2024
https://dl.acm.org/doi/10.14778/3648160.3648183
Wang ZZhang KLv YWang YZhao ZHe ZJing YWang X(2024)RTOD: Efficient Outlier Detection With Ray Tracing CoresIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.345390136:12(9192-9204)Online publication date: Dec-2024
https://doi.org/10.1109/TKDE.2024.3453901
Ha DLiu LChou YGo SRo WTseng HAamodt T(2024)Generalizing Ray Tracing Accelerators for Tree Traversals on GPUs2024 57th IEEE/ACM International Symposium on Microarchitecture (MICRO)10.1109/MICRO61859.2024.00080(1041-1057)Online publication date: 2-Nov-2024
https://doi.org/10.1109/MICRO61859.2024.00080
Show More Cited By

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RT-kNNS Unbound: Using RT Cores to Accelerate Unrestricted Neighbor Search

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Published In

cover image ACM Conferences

ICS '23: Proceedings of the 37th ACM International Conference on Supercomputing

June 2023

505 pages

ISBN:9798400700569

DOI:10.1145/3577193

Chair:
Kyle Gallivan,
Co-chair:
Efstratios Gallopoulos,
Program Co-chairs:
Dimitrios S. Nikolopoulos,
Ramon Beivide

Copyright © 2023 Owner/Author(s).

This work is licensed under a Creative Commons Attribution International 4.0 License.

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SIGARCH: ACM Special Interest Group on Computer Architecture

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 June 2023

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ICS '23

Sponsor:

SIGARCH

ICS '23: 37th International Conference on Supercomputing

June 21 - 23, 2023

FL, Orlando, USA

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Overall Acceptance Rate 629 of 2,180 submissions, 29%

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Cited By

Lv YZhang KWang ZZhang XLee RHe ZJing YWang X(2024)RTScan: Efficient Scan with Ray Tracing CoresProceedings of the VLDB Endowment10.14778/3648160.364818317:6(1460-1472)Online publication date: 3-May-2024
https://dl.acm.org/doi/10.14778/3648160.3648183
Wang ZZhang KLv YWang YZhao ZHe ZJing YWang X(2024)RTOD: Efficient Outlier Detection With Ray Tracing CoresIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.345390136:12(9192-9204)Online publication date: Dec-2024
https://doi.org/10.1109/TKDE.2024.3453901
Ha DLiu LChou YGo SRo WTseng HAamodt T(2024)Generalizing Ray Tracing Accelerators for Tree Traversals on GPUs2024 57th IEEE/ACM International Symposium on Microarchitecture (MICRO)10.1109/MICRO61859.2024.00080(1041-1057)Online publication date: 2-Nov-2024
https://doi.org/10.1109/MICRO61859.2024.00080
Feng YLiu ZLeng JGuo MZhu Y(2024)Cicero: Addressing Algorithmic and Architectural Bottlenecks in Neural Rendering by Radiance Warping and Memory Optimizations2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA)10.1109/ISCA59077.2024.00096(1293-1308)Online publication date: 29-Jun-2024
https://doi.org/10.1109/ISCA59077.2024.00096

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