Title :
Performance Evaluation of Statistical Functions
Author :
Andr? ;Carla Silva;Paulo Borges;S?rgio ;In?s
Author_Institution :
INESC TEC, Porto, Portugal
Abstract :
Statistical data analysis methods are well known for their difficulty in handling large number of instances or large number of parameters. This is most noticeable in the presence of "big data", i.e., of data that are heterogeneous, and come from several sources, which makes their volume increase very rapidly. In this paper, we study popular and well-known statistical functions generally applied to data analysis, and assess their performance using our own implementation (DataIP) 1, MatLab and R. We show that DataIP outperforms MatLab and R by several orders of magnitude and that the design and implementation of these functions need to be rethought to adapt to today´s data challenges.
Keywords :
"MATLAB","Multicore processing","Correlation","Instruction sets","Data analysis","Statistical analysis","Complexity theory"
Conference_Titel :
Smart City/SocialCom/SustainCom (SmartCity), 2015 IEEE International Conference on
DOI :
10.1109/SmartCity.2015.159