On the public citation graph

Efficient Selection Algorithm for Fast k-NN Search on GPUs

https://doi.org/10.1109/ipdps.2015.115

0 signed · 34 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-23400-2_35openalex-snapshot

kNN Query Processing in Metric Spaces Using GPUs

inferredcites →https://doi.org/10.1007/s11227-011-0672-7openalex-snapshot

Parallel data mining techniques on Graphics Processing Unit with Compute Unified Device Architecture (CUDA)

inferredcites →https://doi.org/10.1057/jors.1991.155openalex-snapshot

Introduction to Algorithms

inferredcites →https://doi.org/10.1109/hpec.2012.6408667openalex-snapshot

Parallel search of k-nearest neighbors with synchronous operations

inferredcites →https://doi.org/10.1109/icip.2010.5654017openalex-snapshot

K-nearest neighbor search: Fast GPU-based implementations and application to high-dimensional feature matching

inferredcites →https://doi.org/10.1109/ipdps.2009.5161005openalex-snapshot

Designing efficient sorting algorithms for manycore GPUs

inferredcites →https://doi.org/10.1109/ipdps.2010.5470444openalex-snapshot

GPU sample sort

inferredcites →https://doi.org/10.1109/ipdps.2012.30openalex-snapshot

A Novel Sorting Algorithm for Many-core Architectures Based on Adaptive Bitonic Sort

inferredcites →https://doi.org/10.1145/2001269.2001293openalex-snapshot

Building Rome in a day

inferredcites →https://doi.org/10.1145/2018323.2018338openalex-snapshot

Randomized selection on the GPU

inferredcites →https://doi.org/10.1145/2093973.2094002openalex-snapshot

Fast GPU-based locality sensitive hashing for k-nearest neighbor computation

inferredcites →https://doi.org/10.1145/2133803.2345676openalex-snapshot

Fast k -selection algorithms for graphics processing units

inferredcites →https://doi.org/10.1145/2304576.2304621openalex-snapshot

GPU merge path

inferredcites →https://doi.org/10.1145/2600212.2600710openalex-snapshot

Data filtering for scalable high-dimensional k-NN search on multicore systems

inferredcites →https://doi.org/10.1371/journal.pone.0044000openalex-snapshot

GPU-FS-kNN: A Software Tool for Fast and Scalable kNN Computation Using GPUs

inferredcites →https://doi.org/10.1371/journal.pone.0092409openalex-snapshot

Fast k-NNG Construction with GPU-Based Quick Multi-Select

inferredcites →https://doi.org/10.2312/eggh/hpg12/039-047openalex-snapshot

kANN on the GPU with Shifted Sorting

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-08337-2_10openalex-snapshot

Hybrid (CPU/GPU) Exact Nearest Neighbors Search in High-Dimensional Spaces

inferred← citeshttps://doi.org/10.1007/s10115-026-02891-2openalex-snapshot

DistTDT: distributed terminological decision tree learning

inferred← citeshttps://doi.org/10.1007/s11227-021-03975-2openalex-snapshot

Fast kNN query processing over a multi-node GPU environment

inferred← citeshttps://doi.org/10.1109/cvpr.2018.00517openalex-snapshot

Efficient Large-Scale Approximate Nearest Neighbor Search on OpenCL FPGA

inferred← citeshttps://doi.org/10.1109/icpp.2016.69openalex-snapshot

GFlink: An In-Memory Computing Architecture on Heterogeneous CPU-GPU Clusters for Big Data

inferred← citeshttps://doi.org/10.1109/ipdps54959.2023.00088openalex-snapshot

SelB-k-NN: A Mini-Batch K-Nearest Neighbors Algorithm on AI Processors

inferred← citeshttps://doi.org/10.1109/ipdpsw63119.2024.00119openalex-snapshot

Towards Accelerating k-NN with MPI and Near-Memory Processing

inferred← citeshttps://doi.org/10.1109/sccc51225.2020.9281231openalex-snapshot

An exhaustive algorithm based on GPU to process a kNN query

inferred← citeshttps://doi.org/10.1109/tbdata.2019.2921572openalex-snapshot

Billion-Scale Similarity Search with GPUs

inferred← citeshttps://doi.org/10.1111/cgf.14177openalex-snapshot

Optimizing LBVH‐Construction and Hierarchy‐Traversal to accelerate kNN Queries on Point Clouds using the GPU

inferred← citeshttps://doi.org/10.1145/3122788openalex-snapshot

Exploiting Sparsity to Accelerate Fully Connected Layers of CNN-Based Applications on Mobile SoCs

inferred← citeshttps://doi.org/10.1145/3219819.3220018openalex-snapshot

Recurrent Binary Embedding for GPU-Enabled Exhaustive Retrieval from Billion-Scale Semantic Vectors

inferred← citeshttps://doi.org/10.1145/3524059.3532368openalex-snapshot

Efficient exact K-nearest neighbor graph construction for billion-scale datasets using GPUs with tensor cores

inferred← citeshttps://doi.org/10.1145/3581784.3607062openalex-snapshot

Parallel Top-K Algorithms on GPU: A Comprehensive Study and New Methods

inferred← citeshttps://doi.org/10.1145/3721145.3730415openalex-snapshot

CLOVER: A GPU-native, Spatio-graph-based Approach to Exact kNN

inferred← citeshttps://doi.org/10.14778/3704965.3704974openalex-snapshot

Steiner -Hardness: A Query Hardness Measure for Graph-Based ANN Indexes

inferred← citeshttps://doi.org/10.5220/0006105903860393openalex-snapshot

Parallelized Flight Path Prediction using a Graphics Processing Unit

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.