Randomized selection on the GPU

By Laura Monroe, Joanne Wendelberger, Sarah Ellen Michalak. 2011

26 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Statistics and Probability, ML Systems & Hardware, Algorithms & Complexity

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Matthijs Douze
2. Herv'e J'egou
3. Minyi Guo
4. Jeff Johnson
5. Hugo Touvron
6. Armand Joulin
7. Holger Schwenk
8. Quoc V. Le

In Computational Theory and Mathematics

1. Herv'e J'egou
2. Jeff Johnson
3. Matthijs Douze

In Statistics and Probability

1. Herv'e J'egou
2. Matthijs Douze

In ML Systems & Hardware

1. Jeff Johnson

In Algorithms & Complexity

1. Herv'e J'egou
2. Jeff Johnson
3. Matthijs Douze

Citations in the corpus

• Billion-Scale Similarity Search with GPUs (2017, background): “k -selection algorithms, often for arbitrarily large (cid:96) and k , can be translated to a GPU, including radix selection and bucket selection [1], probabilistic selection [33], quick-select [14], and truncated sorts [40].”
• Efficient Selection Algorithm for Fast k-NN Search on GPUs (2015, background): “To avoid the worst-case performance, sample select [11] chooses the best pivot by taking samples.”