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Bigger Buffer k-d Trees on Multi-Many-Core Systems [article]

Fabian Gieseke and Cosmin Eugen Oancea and Ashish Mahabal and Christian Igel and Tom Heskes
2015 arXiv   pre-print
A buffer k-d tree is a k-d tree variant for massively-parallel nearest neighbor search.  ...  While providing valuable speed-ups on modern many-core devices in case both a large number of reference and query points are given, buffer k-d trees are limited by the amount of points that can fit on  ...  Conclusions We provide a modified workflow for processing huge amounts of nearest neighbor queries using buffer k-d trees.  ... 
arXiv:1512.02831v1 fatcat:ct36idp44fhozhlsvh2bx2zpcq

Parallel Batch-Dynamic kd-Trees [article]

Rahul Yesantharao
2021 arXiv   pre-print
34.8× (28.4× on average) for batch insertions, up to 35.5× (27.2× on average) for batch deletions, and up to 46.1× (40.0× on average) for k-nearest neighbor queries.  ...  In this paper, we present BDL-tree, a parallel, batch-dynamic implementation of a kd-tree that allows for efficient parallel k-NN queries over dynamically changing point sets.  ...  It outperforms both in the 1) k-NN Search using the kd-tree: Given a query coordinate dynamic setting where k-NN queries and batched updates are q, a k-NN query finds the k nearest neighbors  ... 
arXiv:2112.06188v1 fatcat:e5bje74lg5hbnlxanqkhubpqli

Real-time KD-tree construction on graphics hardware

Kun Zhou, Qiming Hou, Rui Wang, Baining Guo
2008 ACM SIGGRAPH Asia 2008 papers on - SIGGRAPH Asia '08  
We present an algorithm for constructing kd-trees on GPUs. This algorithm achieves real-time performance by exploiting the GPU's streaming architecture at all stages of kd-tree construction.  ...  Our algorithm provides a general way for handling dynamic scenes on the GPU.  ...  GPU Photon Mapping We implemented GPU photon mapping, in which photon tracing, photon kd-tree construction and nearest photon query are all performed on the GPU on the fly (Section 5).  ... 
doi:10.1145/1457515.1409079 fatcat:5osvvoz545a75nyhozb4gfu5ey

Real-time KD-tree construction on graphics hardware

Kun Zhou, Qiming Hou, Rui Wang, Baining Guo
2008 ACM Transactions on Graphics  
We present an algorithm for constructing kd-trees on GPUs. This algorithm achieves real-time performance by exploiting the GPU's streaming architecture at all stages of kd-tree construction.  ...  Our algorithm provides a general way for handling dynamic scenes on the GPU.  ...  GPU Photon Mapping We implemented GPU photon mapping, in which photon tracing, photon kd-tree construction and nearest photon query are all performed on the GPU on the fly (Section 5).  ... 
doi:10.1145/1409060.1409079 fatcat:wtbt3lxbgvfillhcyybowndlhm

GPU-Accelerated Nearest Neighbor Search for 3D Registration [chapter]

Deyuan Qiu, Stefan May, Andreas Nüchter
2009 Lecture Notes in Computer Science  
The approach exploits the concept of general purpose computation on graphics processing units (GPGPU) and is compared to parallel processing on CPU.  ...  Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for real-time capability.  ...  Our massively parallel nearest neighbor search algorithm, GPU-NNS, is implemented on the CUDA architecture.  ... 
doi:10.1007/978-3-642-04667-4_20 fatcat:whxo3lqw5jhntcr6bxwzbth23m

GGNN: Graph-based GPU Nearest Neighbor Search [article]

Fabian Groh, Lukas Ruppert, Patrick Wieschollek, Hendrik P.A. Lensch
2021 arXiv   pre-print
In this paper, we propose a novel search structure based on nearest neighbor graphs and information propagation on graphs.  ...  Since PQT and FAISS started to leverage the massive parallelism offered by GPUs, GPU-based implementations are a crucial resource for today's state-of-the-art ANN methods.  ...  known point d best k , i.e. if d next > d best k + ξ = d best k + τ • min{d + nn1 , d best1 } (2) holds, where d + nn1 denotes the maximum distance of the data points to their closest neighbor within  ... 
arXiv:1912.01059v3 fatcat:zbewjskznrhexkvt2zc6vacnqy

A Hardware Processing Unit for Point Sets [article]

Simon Heinzle, Gaël Guennebaud, Mario Botsch, Markus Gross
2008 Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware - HWWS '04  
Our design is focused on fundamental and computationally expensive operations on point sets including k-nearest neighbors search, moving least squares approximation, and others.  ...  A key component of our design is the spatial search unit based on a kd-tree performing both kNN and eN searches.  ...  Assume we query the kNN of the point q i (Figure 2a ). Instead of looking for the k nearest neighbors, we compute the k + 1 nearest neighbors N i = {p 1 , ..., p k+1 }.  ... 
doi:10.2312/eggh/eggh08/021-031 fatcat:n3epuivc45csrop227lqubkqkm

Hybrid Indexing for Parallel Analysis of Spatiotemporal Point Patterns

Alexander Hohl, Irene Casas, Eric Delmelle, Wenwu Tang
2016 International Conference on GIScience Short Paper Proceedings  
We perform adaptive octree decomposition of the spatiotemporal domain and build local k-d trees to accelerate nearest neighbour search for space-time kernel density estimation (STKDE).  ...  A single index method for spatiotemporal data processing lacks retrieval efficiency for massive computation.  ...  We use k-d tree index to accelerate the kNN search for each voxel for STKDE (blue crosses in Figure 1 ), resulting in massive queries.  ... 
doi:10.21433/b3114824r3wg fatcat:nqs4jzffhjhpjgcqdbiitsqr5u

Hybrid KNN-Join: Parallel Nearest Neighbor Searches Exploiting CPU and GPU Architectural Features [article]

Michael Gowanlock
2020 arXiv   pre-print
K Nearest Neighbor (KNN) joins are used in scientific domains for data analysis, and are building blocks of several well-known algorithms. KNN-joins find the KNN of all points in a dataset.  ...  We propose optimizations that (i) maximize GPU query throughput by assigning the GPU large batches of work; (ii) increase workload granularity to optimize GPU utilization; and, (iii) limit load imbalance  ...  nearest K neighbors.  ... 
arXiv:1810.04758v2 fatcat:t4t44mwcfzbfdm7uds5uvz45ey

Accelerating Exact Similarity Search on CPU-GPU Systems

Takazumi Matsumoto, Man Lung Yiu
2015 2015 IEEE International Conference on Data Mining  
Similarity search, also known as k-nearest neighbor search, is a key part of data mining applications and is used also extensively in applications such as multimedia search, where only a small subset of  ...  With modern processors integrating both CPUs and GPUs, it is also important to consider what tasks benefit from GPU processing and which do not, and apply a heterogeneous processing approach to improve  ...  On a small sample, initial distance computation with Q can be done quickly, with the k-th nearest neighbor d T extracted as the threshold value.  ... 
doi:10.1109/icdm.2015.125 dblp:conf/icdm/MatsumotoY15 fatcat:i5rzgrm2cfek5jdudloi4ndt6q

PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures

Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter Sadowski, Evan Racah, Suren Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey
2016 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)  
Computing k-Nearest Neighbors (KNN) is one of the core kernels used in many machine learning, data mining and scientific computing applications.  ...  In addition, we showcase performance and scalability on the recently released Intel Xeon Phi processor showing that our algorithm scales well even on massively parallel architectures.  ...  A variant of the classical kd-tree (called buffered kd-tree) has been proposed recently [18] , which parallelizes querying on GPUs given a kd-tree.  ... 
doi:10.1109/ipdps.2016.57 dblp:conf/ipps/PatwarySSLSRBTB16 fatcat:uf3a5ibozngntcthepaut7frgi

Tigris

Tiancheng Xu, Boyuan Tian, Yuhao Zhu
2019 Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture - MICRO '52  
This paper focuses on point cloud registration, a key primitive of 3D data processing widely used in high-level tasks such as odometry, simultaneous localization and mapping, and 3D reconstruction.  ...  Overall, Tigris achieves 77.2× speedup and 7.4× power reduction in KD-tree search over an RTX 2080 Ti GPU, which translates to a 41.7 improvements and 3.0× power reduction.  ...  Specifically, we inject errors into the nearest neighbor (NN) search by replacing the return result, i.e., the nearest neighbor to the query, with a point that is the k t h nearest neighbor to the query  ... 
doi:10.1145/3352460.3358259 dblp:conf/micro/XuTZ19 fatcat:24e5qeghdfalrci47ebdocq5tm

Automatically enhancing locality for tree traversals with traversal splicing

Youngjoon Jo, Milind Kulkarni
2012 SIGPLAN notices  
Focusing on a subset of irregular programs, namely, tree traversal algorithms like Barnes-Hut and nearest neighbor, previous work has proposed point blocking, a technique analogous to loop tiling in regular  ...  However point blocking is highly dependent on point sorting, a technique to reorder points so that consecutive points will have similar traversals.  ...  We are grateful to Bruce Walter for providing the Ray Tracing benchmark code, and Vijay Pai and his students for providing support for machines on which our tests were conducted.  ... 
doi:10.1145/2398857.2384643 fatcat:tdol27zys5gildfgri2jr4y2d4

Automatically enhancing locality for tree traversals with traversal splicing

Youngjoon Jo, Milind Kulkarni
2012 Proceedings of the ACM international conference on Object oriented programming systems languages and applications - OOPSLA '12  
Focusing on a subset of irregular programs, namely, tree traversal algorithms like Barnes-Hut and nearest neighbor, previous work has proposed point blocking, a technique analogous to loop tiling in regular  ...  However point blocking is highly dependent on point sorting, a technique to reorder points so that consecutive points will have similar traversals.  ...  We are grateful to Bruce Walter for providing the Ray Tracing benchmark code, and Vijay Pai and his students for providing support for machines on which our tests were conducted.  ... 
doi:10.1145/2384616.2384643 dblp:conf/oopsla/JoK12 fatcat:bfg27lfvjvdf3bn6h6yfu4wy7e

Approximate similarity search for online multimedia services on distributed CPU–GPU platforms

George Teodoro, Eduardo Valle, Nathan Mariano, Ricardo Torres, Wagner Meira, Joel H. Saltz
2013 The VLDB journal  
In this work, we address these challenges with Hypercurves, a flexible framework for answering approximate k-nearest neighbor (kNN) queries for very large multimedia databases.  ...  Hypercurves executes in hybrid CPU-GPU environments and is  ...  Objects' dissimilarity is used to establish various types of similarity queries [12] : range, nearest neighbor, k nearest neighbors (kNN), inverse k-nearest neighbors, etc.  ... 
doi:10.1007/s00778-013-0329-7 fatcat:rpcxwmr5hvdwll73wvvnuxirke
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