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GTC ON-DEMAND

Developer - Algorithms
Presentation
Media
Superfast Nearest Neighbor Searches Using a Minimal kd-tree
Speakers:
Shawn Brown
Abstract:

Learn how to adapt a kd-tree spatial data structure for efficient nearest neighbor (NN) searches on a GPU. Although the kd-tree is not a natural fit for GPU implementation, it can still be effective with the right engineering decisions. By bounding the maximum height of the kd-tree, minimizing the memory footprint of data structures, and optimizing the GPU kernel code, multi-core GPU NN searches with tens of thousands to tens of millions of points run 10-40 times faster than the equivalent single-core CPU NN searches.

 
Topics:
Developer - Algorithms, Artificial Intelligence and Deep Learning, Databases, Data Mining, Business Intelligence
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
S102140
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