mloss.org bufferkdtreehttp://mloss.orgUpdates and additions to bufferkdtreeenFri, 20 Oct 2017 11:39:59 -0000bufferkdtree 1.3http://mloss.org/software/view/691/<html><p>The bufferkdtree package is a Python library that aims at accelerating nearest neighbor computations using both k-d trees and modern many-core devices such as graphics processing units (GPUs). The implementation is based on OpenCL. </p> <p>The buffer k-d tree technique can be seen as an intermediate version between a standard parallel k-d tree traversal (on multi-core systems) and a massively-parallel brute-force implementation for nearest neighbor search. In particular, it makes use of the top of a standard k-d tree (which induces a spatial subdivision of the space) and resorts to a simple yet efficient brute-force implementation for processing chunks of "big" leaves. The implementation is well-suited for data sets with a large reference set (e.g., 1,000,000 points) and a huge query set (e.g., 10,000,000 points) given a moderate dimensionality of the search space (e.g., from d=5 to d=50). </p></html>fgieseke, christian igel, Cosmin Oancea, Justin HeinermannFri, 20 Oct 2017 11:39:59 -0000http://mloss.org/software/rss/comments/691http://mloss.org/software/view/691/large scalenearest neighborsgpuhigh performance computingbig data