Improving data clustering performance
Main Article Content
Abstract
The algorithm for clustering, which improves the performance of data clustering through the use of computational power of modern GPUs with CUDA technology and multicore CPUs.
Article Details
![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
Inderjit S. Dhillon, Dharmendra S. Modha. A Data-Clustering Algorithm on Distributed Memory Multiprocessors // Revised Papers from Large-Scale Parallel Data Mining, Work- shop on Large-Scale Parallel KDD Systems, SIGKDD. – 1999. – Р. 17.
Fazilah Othman, Rosni Abdullah, Nur’Aini Ab- dul Rashid, Rosalina Abdul Salam. Parallel K- Means Clustering Algorithm on DNA Dataset // Parallel and Distributed Computing: Applica- tions and Technologies. Lecture Notes in Computer Science. – 2005. – Volume 3320/2005. – Р. 248-251.
Jian Wan, Wenming Yu1, Xianghua Xu. De- sign and Implement of Distributed Document Clustering Based on MapReduce // Proceed- ings of the Second Symposium International Computer Science and Computational Tech- nology (ISCSCT ’09). – 2009. – Р. 278-280.