Fast approximate nearest neighbor search with the navigating spreading-out graph
Approximate nearest neighbor search (ANNS) is a fundamental problem in databases and
data mining. A scalable ANNS algorithm should be both memory-efficient and fast. Some …
data mining. A scalable ANNS algorithm should be both memory-efficient and fast. Some …
Song: Approximate nearest neighbor search on gpu
Approximate nearest neighbor (ANN) searching is a fundamental problem in computer
science with numerous applications in (eg,) machine learning and data mining. Recent …
science with numerous applications in (eg,) machine learning and data mining. Recent …
Brute-Force k-Nearest Neighbors Search on the GPU
S Li, N Amenta - Similarity Search and Applications: 8th International …, 2015 - Springer
We present a brute-force approach for finding k-nearest neighbors on the GPU for many
queries in parallel. Our program takes advantage of recent advances in fundamental GPU …
queries in parallel. Our program takes advantage of recent advances in fundamental GPU …
GPU enhanced graph model build and scoring engine
TD Harris, Y Li, T Korolevskaya… - US Patent 11,138,516, 2021 - Google Patents
Embodiments are directed to a method for accelerating machine learning using a plurality of
graphics processing units (GPUs), involving receiving data for a graph to generate a plurality …
graphics processing units (GPUs), involving receiving data for a graph to generate a plurality …
Online multimedia retrieval on CPU–GPU platforms with adaptive work partition
Nearest neighbors search is a core operation found in several online multimedia services.
These services have to handle very large databases, while, at the same time, they must …
These services have to handle very large databases, while, at the same time, they must …
A novel approach to accelerate calibration process of a k-nearest neighbours classifier using GPU
General purpose data parallel computing with graphical processing unit (GPU) is much
structured today with NVIDIA® CUDA and other parallel programming frameworks …
structured today with NVIDIA® CUDA and other parallel programming frameworks …
Spatial-aware data partition for distributed memory parallelization of ANN search in multimedia retrieval
G Andrade, R Ferreira, G Teodoro - Parallel Computing, 2023 - Elsevier
Content-based multimedia retrieval (CBMR) applications are becoming very popular in
several online services which handles large volumes of data and are submitted to high …
several online services which handles large volumes of data and are submitted to high …
[HTML][HTML] Region templates: Data representation and management for high-throughput image analysis
We introduce a region template abstraction and framework for the efficient storage,
management and processing of common data types in analysis of large datasets of high …
management and processing of common data types in analysis of large datasets of high …
Haggis: turbocharge a MapReduce based spatial data warehousing system with GPU engine
Spatial query processing involves complex multidimensional objects and compute intensive
spatial operations, and therefore requires a high performance approach to meet the rapid …
spatial operations, and therefore requires a high performance approach to meet the rapid …
Application performance analysis and efficient execution on systems with multi-core CPUs, GPUs and MICs: a case study with microscopy image analysis
We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi
(Many Integrated Core (MIC)) with a microscopy image analysis application. We …
(Many Integrated Core (MIC)) with a microscopy image analysis application. We …