[REVIEW] Random Ball Cover Algorithm for 2D Haversine/Euclidean #213
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cjnolet
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improvement
cjnolet
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cjnolet
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Tentative plan for the random ball cover PoC:
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Removing |
cjnolet
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divyegala
reviewed
Sep 16, 2021
version and all supported configurations (all knn vs separate index/query)
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rerun tests |
wphicks
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Sep 20, 2021
wphicks
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Sep 23, 2021
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All looks great! I'm pre-approving, but I noticed that cpp/test/spatial/ball_cover.cu, is the only file where we still have fixed width types without a corresponding include. Can we get a quick #include <cstdint> and s/uint32_t/std::uint32_t/g?
dantegd
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Sep 23, 2021
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rerun tests |
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@gpucibot merge |
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Sep 29, 2021
This PR integrates the [random ball cover PoC](rapidsai/raft#213) into cuml's brute-force knn for executing the random ball cover algorithm for haversine distance. Authors: - Corey J. Nolet (https://github.com/cjnolet) - Dante Gama Dessavre (https://github.com/dantegd) - Paul Taylor (https://github.com/trxcllnt) Approvers: - AJ Schmidt (https://github.com/ajschmidt8) - Dante Gama Dessavre (https://github.com/dantegd) URL: #4003
vimarsh6739
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Oct 9, 2023
This PR integrates the [random ball cover PoC](rapidsai/raft#213) into cuml's brute-force knn for executing the random ball cover algorithm for haversine distance. Authors: - Corey J. Nolet (https://github.com/cjnolet) - Dante Gama Dessavre (https://github.com/dantegd) - Paul Taylor (https://github.com/trxcllnt) Approvers: - AJ Schmidt (https://github.com/ajschmidt8) - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4003
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This PR is a proof of concept to use the triangle inequality to prune the tree of
exhaustive distance computations into something smaller, such as on the order of 
where c is called an expansion constant, based on the dimensionality.
This should (hopefully) be able to benefit both sparse and dense k-nearest neighbors and all algorithms that use them, hopefully providing a significant speedup for our sparse semirings primitive when only the k-nearest neighbors are desired.
The goal here is to construct a tree out of the random ball cover algorithm such that we can utilize it in algorithms which would otherwise be able to make efficient use of a ball tree. However, there are additional challenges to this algorithm on the GPU, such as being able to batch the tree lookups.